predicting cancer outcome: Topics by WorldWideScience.org

Sample records for predicting cancer outcome

Network information improves cancer outcome prediction.

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Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

2014-07-01

Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Androgen receptor profiling predicts prostate cancer outcome

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S. Stelloo (Suzan); E. Nevedomskaya (Ekaterina); H.G. van der Poel (Henk G.); J. de Jong (Jeroen); G.J.H.L. Leenders (Geert); G.W. Jenster (Guido); L. Wessels (Lodewyk); A.M. Bergman (Andries); W. Zwart (Wilbert)

2015-01-01

textabstractProstate cancer is the second most prevalent malignancy in men. Biomarkers for outcome prediction are urgently needed, so that high-risk patients could be monitored more closely postoperatively. To identify prognostic markers and to determine causal players in prostate cancer
FERAL : Network-based classifier with application to breast cancer outcome prediction

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Allahyar, A.; De Ridder, J.

2015-01-01

Motivation: Breast cancer outcome prediction based on gene expression profiles is an important strategy for personalize patient care. To improve performance and consistency of discovered markers of the initial molecular classifiers, network-based outcome prediction methods (NOPs) have been proposed.
Hadamard Kernel SVM with applications for breast cancer outcome predictions.

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Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

2017-12-21

Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.
Module-based outcome prediction using breast cancer compendia.

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Martin H van Vliet

Full Text Available BACKGROUND: The availability of large collections of microarray datasets (compendia, or knowledge about grouping of genes into pathways (gene sets, is typically not exploited when training predictors of disease outcome. These can be useful since a compendium increases the number of samples, while gene sets reduce the size of the feature space. This should be favorable from a machine learning perspective and result in more robust predictors. METHODOLOGY: We extracted modules of regulated genes from gene sets, and compendia. Through supervised analysis, we constructed predictors which employ modules predictive of breast cancer outcome. To validate these predictors we applied them to independent data, from the same institution (intra-dataset, and other institutions (inter-dataset. CONCLUSIONS: We show that modules derived from single breast cancer datasets achieve better performance on the validation data compared to gene-based predictors. We also show that there is a trend in compendium specificity and predictive performance: modules derived from a single breast cancer dataset, and a breast cancer specific compendium perform better compared to those derived from a human cancer compendium. Additionally, the module-based predictor provides a much richer insight into the underlying biology. Frequently selected gene sets are associated with processes such as cell cycle, E2F regulation, DNA damage response, proteasome and glycolysis. We analyzed two modules related to cell cycle, and the OCT1 transcription factor, respectively. On an individual basis, these modules provide a significant separation in survival subgroups on the training and independent validation data.
Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes.

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Christof Winter

Full Text Available Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.
Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models

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Nilsaz-Dezfouli, Hamid; Abu-Bakar, Mohd Rizam; Arasan, Jayanthi; Adam, Mohd Bakri; Pourhoseingholi, Mohamad Amin

2017-01-01

In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been a long-standing topic of interest. Current statistical methods for survival analysis offer the possibility of modelling cancer survivability but require unrealistic assumptions about the survival time distribution or proportionality of hazard. Therefore, attention must be paid in developing nonlinear models with less restrictive assumptions. Artificial neural network (ANN) models are primarily useful in prediction when nonlinear approaches are required to sift through the plethora of available information. The applications of ANN models for prognostic and diagnostic classification in medicine have attracted a lot of interest. The applications of ANN models in modelling the survival of patients with gastric cancer have been discussed in some studies without completely considering the censored data. This study proposes an ANN model for predicting gastric cancer survivability, considering the censored data. Five separate single time-point ANN models were developed to predict the outcome of patients after 1, 2, 3, 4, and 5 years. The performance of ANN model in predicting the probabilities of death is consistently high for all time points according to the accuracy and the area under the receiver operating characteristic curve. PMID:28469384
Identification of a robust gene signature that predicts breast cancer outcome in independent data sets

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Korkola, James E; Waldman, Frederic M; Blaveri, Ekaterina; DeVries, Sandy; Moore, Dan H II; Hwang, E Shelley; Chen, Yunn-Yi; Estep, Anne LH; Chew, Karen L; Jensen, Ronald H

2007-01-01

Breast cancer is a heterogeneous disease, presenting with a wide range of histologic, clinical, and genetic features. Microarray technology has shown promise in predicting outcome in these patients. We profiled 162 breast tumors using expression microarrays to stratify tumors based on gene expression. A subset of 55 tumors with extensive follow-up was used to identify gene sets that predicted outcome. The predictive gene set was further tested in previously published data sets. We used different statistical methods to identify three gene sets associated with disease free survival. A fourth gene set, consisting of 21 genes in common to all three sets, also had the ability to predict patient outcome. To validate the predictive utility of this derived gene set, it was tested in two published data sets from other groups. This gene set resulted in significant separation of patients on the basis of survival in these data sets, correctly predicting outcome in 62–65% of patients. By comparing outcome prediction within subgroups based on ER status, grade, and nodal status, we found that our gene set was most effective in predicting outcome in ER positive and node negative tumors. This robust gene selection with extensive validation has identified a predictive gene set that may have clinical utility for outcome prediction in breast cancer patients
Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

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Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

2008-10-20

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic
CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes.

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Kong, Hualei; Tong, Pan; Zhao, Xiaodong; Sun, Jielin; Li, Hua

2018-03-01

In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and
Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

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Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.
Predictive Factors and Treatment Outcomes of Tuberculous Pleural Effusion in Patients With Cancer and Pleural Effusion.

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Lee, Jaehee; Lee, Yong Dae; Lim, Jae Kwang; Lee, Deok Heon; Yoo, Seung Soo; Lee, Shin Yup; Cha, Seung Ick; Park, Jae Yong; Kim, Chang Ho

2017-08-01

Patients with cancer are at an increased risk of tuberculosis. As pleural effusion has great clinical significance in patients with cancer, the differential diagnosis between tuberculous pleural effusion (TPE) and malignant pleural effusion (MPE) is important. However, the predictive factors and treatment outcomes of TPE in patients with cancer have rarely been studied. Confirmed TPE cases identified at cancer diagnosis and during anticancer management from 2008-2015 were retrospectively investigated. Patients in the study included coexisting TPE and cancer (n = 20), MPE (n = 40) and TPE without cancer (n = 40). Control groups were patients with MPE, and patients with TPE without cancer. Clinical, laboratory and pleural fluid characteristics were compared among groups. Treatment outcomes were compared between patients with TPE with and without cancer. In the final analysis, serum C-reactive protein (S-CRP) ≥3.0mg/dL and pleural fluid adenosine deaminase (ADA) ≥40U/L were independent predictors for identifying TPE in patients with cancer having pleural effusion. The combination of S-CRP with pleural fluid ADA using an "or" rule achieved a sensitivity of 100%, whereas both parameters combined in an "and" rule had a specificity of 98%. Treatment outcomes were not different between the TPE groups with and without cancer. S-CRP and pleural fluid ADA levels may be helpful for predicting TPE in patients with cancer with pleural effusion. The combination of these biomarkers provides better information for distinguishing between TPE and MPE in these patients. Treatment outcomes of TPE in patients with cancer are comparable to those in patients without cancer. Copyright © 2017 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.
MO-AB-BRA-10: Cancer Therapy Outcome Prediction Based On Dempster-Shafer Theory and PET Imaging

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Lian, C [Sorbonne University, University of Technology of Compiegne, CNRS, UMR 7253 Heudiasyc, 60205 Compiegne (France); University of Rouen, QuantIF - EA 4108 LITIS, 76000 Rouen (France); Li, H; Chen, H; Robinson, C. [Washington University School of Medicine, Saint Louis, MO (United States); Denoeux, T [Sorbonne University, University of Technology of Compiegne, CNRS, UMR 7253 Heudiasyc, 60205 Compiegne (France); Vera, P [Centre Henri-Becquerel, 76038 Rouen (France); University of Rouen, QuantIF - EA 4108 LITIS, 76000 Rouen (France); Ruan, S [University of Rouen, QuantIF - EA 4108 LITIS, 76000 Rouen (France)

2015-06-15

Purpose: In cancer therapy, utilizing FDG-18 PET image-based features for accurate outcome prediction is challenging because of 1) limited discriminative information within a small number of PET image sets, and 2) fluctuant feature characteristics caused by the inferior spatial resolution and system noise of PET imaging. In this study, we proposed a new Dempster-Shafer theory (DST) based approach, evidential low-dimensional transformation with feature selection (ELT-FS), to accurately predict cancer therapy outcome with both PET imaging features and clinical characteristics. Methods: First, a specific loss function with sparse penalty was developed to learn an adaptive low-rank distance metric for representing the dissimilarity between different patients’ feature vectors. By minimizing this loss function, a linear low-dimensional transformation of input features was achieved. Also, imprecise features were excluded simultaneously by applying a l2,1-norm regularization of the learnt dissimilarity metric in the loss function. Finally, the learnt dissimilarity metric was applied in an evidential K-nearest-neighbor (EK- NN) classifier to predict treatment outcome. Results: Twenty-five patients with stage II–III non-small-cell lung cancer and thirty-six patients with esophageal squamous cell carcinomas treated with chemo-radiotherapy were collected. For the two groups of patients, 52 and 29 features, respectively, were utilized. The leave-one-out cross-validation (LOOCV) protocol was used for evaluation. Compared to three existing linear transformation methods (PCA, LDA, NCA), the proposed ELT-FS leads to higher prediction accuracy for the training and testing sets both for lung-cancer patients (100+/−0.0, 88.0+/−33.17) and for esophageal-cancer patients (97.46+/−1.64, 83.33+/−37.8). The ELT-FS also provides superior class separation in both test data sets. Conclusion: A novel DST- based approach has been proposed to predict cancer treatment outcome using PET
Predicting Adverse Health Outcomes in Long-Term Survivors of a Childhood Cancer

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Chaya S. Moskowitz

2014-07-01

Full Text Available More than 80% of children and young adults diagnosed with invasive cancer will survive five or more years beyond their cancer diagnosis. This population has an increased risk for serious illness- and treatment-related morbidity and premature mortality. A number of these adverse health outcomes, such as cardiovascular disease and some second primary neoplasms, either have modifiable risk factors or can be successfully treated if detected early. Absolute risk models that project a personalized risk of developing a health outcome can be useful in patient counseling, in designing intervention studies, in forming prevention strategies, and in deciding upon surveillance programs. Here, we review existing absolute risk prediction models that are directly applicable to survivors of a childhood cancer, discuss the concepts and interpretation of absolute risk models, and examine ways in which these models can be used applied in clinical practice and public health.
Microsatellite Instability Predicts Clinical Outcome in Radiation-Treated Endometrioid Endometrial Cancer

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Bilbao, Cristina; Lara, Pedro Carlos; Ramirez, Raquel; Henriquez-Hernandez, Luis Alberto; Rodriguez, German; Falcon, Orlando; Leon, Laureano; Perucho, Manuel

2010-01-01

Purpose: To elucidate whether microsatellite instability (MSI) predicts clinical outcome in radiation-treated endometrioid endometrial cancer (EEC). Methods and Materials: A consecutive series of 93 patients with EEC treated with extrafascial hysterectomy and postoperative radiotherapy was studied. The median clinical follow-up of patients was 138 months, with a maximum of 232 months. Five quasimonomorphic mononucleotide markers (BAT-25, BAT-26, NR21, NR24, and NR27) were used for MSI classification. Results: Twenty-five patients (22%) were classified as MSI. Both in the whole series and in early stages (I and II), univariate analysis showed a significant association between MSI and poorer 10-year local disease-free survival, disease-free survival, and cancer-specific survival. In multivariate analysis, MSI was excluded from the final regression model in the whole series, but in early stages MSI provided additional significant predictive information independent of traditional prognostic and predictive factors (age, stage, grade, and vascular invasion) for disease-free survival (hazard ratio [HR] 3.25, 95% confidence interval [CI] 1.01-10.49; p = 0.048) and cancer-specific survival (HR 4.20, 95% CI 1.23-14.35; p = 0.022) and was marginally significant for local disease-free survival (HR 3.54, 95% CI 0.93-13.46; p = 0.064). Conclusions: These results suggest that MSI may predict radiotherapy response in early-stage EEC.
Predicting physical activity and outcome expectations in cancer survivors: an application of Self-Determination Theory.

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Wilson, Philip M; Blanchard, Chris M; Nehl, Eric; Baker, Frank

2006-07-01

The purpose of this study was to examine the contributions of autonomous and controlled motives drawn from Self-Determination Theory (SDT; Intrinsic Motivation and Self-determination in Human Behavior. Plenum Press: New York, 1985; Handbook of Self-determination Research. University of Rochester Press: New York, 2002) towards predicting physical activity behaviours and outcome expectations in adult cancer survivors. Participants were cancer-survivors (N=220) and a non-cancer comparison cohort (N=220) who completed an adapted version of the Treatment Self-Regulation Questionnaire modified for physical activity behaviour (TSRQ-PA), an assessment of the number of minutes engaged in moderate-to-vigorous physical activity (MVPA) weekly, and the anticipated outcomes expected from regular physical activity (OE). Simultaneous multiple regression analyses indicated that autonomous motives was the dominant predictor of OEs across both cancer and non-cancer cohorts (R(2adj)=0.29-0.43), while MVPA was predicted by autonomous (beta's ranged from 0.21 to 0.34) and controlled (beta's ranged from -0.04 to -0.23) motives after controlling for demographic considerations. Cancer status (cancer versus no cancer) did not moderate the motivation-physical activity relationship. Collectively, these findings suggest that the distinction between autonomous and controlled motives is useful and compliments a growing body of evidence supporting SDT as a framework for understanding motivational processes in physical activity contexts with cancer survivors.
Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer

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Bychkov, Dmitrii; Turkki, Riku; Haglund, Caj; Linder, Nina; Lundin, Johan

2016-03-01

Recent advances in computer vision enable increasingly accurate automated pattern classification. In the current study we evaluate whether a convolutional neural network (CNN) can be trained to predict disease outcome in patients with colorectal cancer based on images of tumor tissue microarray samples. We compare the prognostic accuracy of CNN features extracted from the whole, unsegmented tissue microarray spot image, with that of CNN features extracted from the epithelial and non-epithelial compartments, respectively. The prognostic accuracy of visually assessed histologic grade is used as a reference. The image data set consists of digitized hematoxylin-eosin (H and E) stained tissue microarray samples obtained from 180 patients with colorectal cancer. The patient samples represent a variety of histological grades, have data available on a series of clinicopathological variables including long-term outcome and ground truth annotations performed by experts. The CNN features extracted from images of the epithelial tissue compartment significantly predicted outcome (hazard ratio (HR) 2.08; CI95% 1.04-4.16; area under the curve (AUC) 0.66) in a test set of 60 patients, as compared to the CNN features extracted from unsegmented images (HR 1.67; CI95% 0.84-3.31, AUC 0.57) and visually assessed histologic grade (HR 1.96; CI95% 0.99-3.88, AUC 0.61). As a conclusion, a deep-learning classifier can be trained to predict outcome of colorectal cancer based on images of H and E stained tissue microarray samples and the CNN features extracted from the epithelial compartment only resulted in a prognostic discrimination comparable to that of visually determined histologic grade.
Improved prediction of breast cancer outcome by identifying heterogeneous biomarkers.

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Choi, Jonghwan; Park, Sanghyun; Yoon, Youngmi; Ahn, Jaegyoon

2017-11-15

Identification of genes that can be used to predict prognosis in patients with cancer is important in that it can lead to improved therapy, and can also promote our understanding of tumor progression on the molecular level. One of the common but fundamental problems that render identification of prognostic genes and prediction of cancer outcomes difficult is the heterogeneity of patient samples. To reduce the effect of sample heterogeneity, we clustered data samples using K-means algorithm and applied modified PageRank to functional interaction (FI) networks weighted using gene expression values of samples in each cluster. Hub genes among resulting prioritized genes were selected as biomarkers to predict the prognosis of samples. This process outperformed traditional feature selection methods as well as several network-based prognostic gene selection methods when applied to Random Forest. We were able to find many cluster-specific prognostic genes for each dataset. Functional study showed that distinct biological processes were enriched in each cluster, which seems to reflect different aspect of tumor progression or oncogenesis among distinct patient groups. Taken together, these results provide support for the hypothesis that our approach can effectively identify heterogeneous prognostic genes, and these are complementary to each other, improving prediction accuracy. https://github.com/mathcom/CPR. jgahn@inu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Clinical Nomogram for Predicting Survival Outcomes in Early Mucinous Breast Cancer.

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Jianfei Fu

Full Text Available The features related to the prognosis of patients with mucinous breast cancer (MBC remain controversial. We aimed to explore the prognostic factors of MBC and develop a nomogram for predicting survival outcomes.The Surveillance, Epidemiology, and End Results (SEER database was searched to identify 139611 women with resectable breast cancer from 1990 to 2007. Survival curves were generated using Kaplan-Meier methods. The 5-year and 10-year cancer-specific survival (CSS rates were calculated using the Life-Table method. Based on Cox models, a nomogram was constructed to predict the probabilities of CSS for an individual patient. The competing risk regression model was used to analyse the specific survival of patients with MBC.There were 136569 (97.82% infiltrative ductal cancer (IDC patients and 3042 (2.18% MBC patients. Patients with MBC had less lymph node involvement, a higher frequency of well-differentiated lesions, and more estrogen receptor (ER-positive tumors. Patients with MBC had significantly higher 5 and10-year CSS rates (98.23 and 96.03%, respectively than patients with IDC (91.44 and 85.48%, respectively. Univariate and multivariate analyses showed that MBC was an independent factor for better prognosis. As for patients with MBC, the event of death caused by another disease exceeded the event of death caused by breast cancer. A competing risk regression model further showed that lymph node involvement, poorly differentiated grade and advanced T-classification were independent factors of poor prognosis in patients with MBC. The Nomogram can accurately predict CSS with a high C-index (0.816. Risk scores developed from the nomogram can more accurately predict the prognosis of patients with MBC (C-index = 0.789 than the traditional TNM system (C-index = 0.704, P< 0.001.Patients with MBC have a better prognosis than patients with IDC. Nomograms could help clinicians make more informed decisions in clinical practice. The competing risk
A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer

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C. Staiger (Christine); S. Cadot; R Kooter; M. Dittrich (Marcus); T. Müller (Tobias); G.W. Klau (Gunnar); L.F.A. Wessels (Lodewyk)

2012-01-01

htmlabstractRecently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically

Prognostic Value of Histology and Lymph Node Status in Bilharziasis-Bladder Cancer: Outcome Prediction Using Neural Networks

National Research Council Canada - National Science Library

Ji, W

2001-01-01

.... Throughout the analysis of the prognostic feature combinations, two features, histological type and lymph node status, have been identified as the important indicators for outcome prediction of this type of cancer...
Incidence, predictive factors, and clinical outcomes of acute kidney injury after gastric surgery for gastric cancer.

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Chang Seong Kim

Full Text Available BACKGROUND: Postoperative acute kidney injury (AKI, a serious surgical complication, is common after cardiac surgery; however, reports on AKI after noncardiac surgery are limited. We sought to determine the incidence and predictive factors of AKI after gastric surgery for gastric cancer and its effects on the clinical outcomes. METHODS: We conducted a retrospective study of 4718 patients with normal renal function who underwent partial or total gastrectomy for gastric cancer between June 2002 and December 2011. Postoperative AKI was defined by serum creatinine change, as per the Kidney Disease Improving Global Outcomes guideline. RESULTS: Of the 4718 patients, 679 (14.4% developed AKI. Length of hospital stay, intensive care unit admission rates, and in-hospital mortality rate (3.5% versus 0.2% were significantly higher in patients with AKI than in those without. AKI was also associated with requirement of renal replacement therapy. Multivariate analysis revealed that male gender; hypertension; chronic obstructive pulmonary disease; hypoalbuminemia (<4 g/dl; use of diuretics, vasopressors, and contrast agents; and packed red blood cell transfusion were independent predictors for AKI after gastric surgery. Postoperative AKI and vasopressor use entailed a high risk of 3-month mortality after multiple adjustments. CONCLUSIONS: AKI was common after gastric surgery for gastric cancer and associated with adverse outcomes. We identified several factors associated with postoperative AKI; recognition of these predictive factors may help reduce the incidence of AKI after gastric surgery. Furthermore, postoperative AKI in patients with gastric cancer is an important risk factor for short-term mortality.
Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study.

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Ho, Samuel M Y; Ho, Judy W C; Bonanno, George A; Chu, Annie T W; Chan, Emily M S

2010-06-11

Genetic testing for hereditary colorectal cancer (HCRC) had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer Registry to determine psychological outcomes after genetic testing. Self-completed questionnaires were administered immediately before (pre-disclosure baseline) and 2 weeks, 4 months and 1 year after result disclosure. Using validated psychological inventories, the cognitive style of hope was measured at baseline, and the psychological distress of depression and anxiety was measured at all time points. Of the 76 participating subjects, 71 individuals (43 men and 28 women; mean age 38.9 +/- 9.2 years) from nine FAP and 24 HNPCC families completed the study, including 39 mutated gene carriers. Four patterns of outcome trajectories were created using established norms for the specified outcome measures of depression and anxiety. These included chronic dysfunction (13% and 8.7%), recovery (0% and 4.3%), delayed dysfunction (13% and 15.9%) and resilience (76.8% and 66.7%). Two logistic regression analyses were conducted using hope at baseline to predict resilience, with depression and anxiety employed as outcome indicators. Because of the small number of participants, the chronic dysfunction and delayed dysfunction groups were combined into a non-resilient group for comparison with the resilient group in all subsequent analysis. Because of low frequencies, participants exhibiting a recovery trajectory (n = 3 for anxiety and n = 0 for depression) were excluded from further analysis. Both regression equations were significant. Baseline hope was a significant predictor of a resilience outcome trajectory for depression
Boolean network model for cancer pathways: predicting carcinogenesis and targeted therapy outcomes.

Directory of Open Access Journals (Sweden)

Herman F Fumiã

Full Text Available A Boolean dynamical system integrating the main signaling pathways involved in cancer is constructed based on the currently known protein-protein interaction network. This system exhibits stationary protein activation patterns--attractors--dependent on the cell's microenvironment. These dynamical attractors were determined through simulations and their stabilities against mutations were tested. In a higher hierarchical level, it was possible to group the network attractors into distinct cell phenotypes and determine driver mutations that promote phenotypic transitions. We find that driver nodes are not necessarily central in the network topology, but at least they are direct regulators of central components towards which converge or through which crosstalk distinct cancer signaling pathways. The predicted drivers are in agreement with those pointed out by diverse census of cancer genes recently performed for several human cancers. Furthermore, our results demonstrate that cell phenotypes can evolve towards full malignancy through distinct sequences of accumulated mutations. In particular, the network model supports routes of carcinogenesis known for some tumor types. Finally, the Boolean network model is employed to evaluate the outcome of molecularly targeted cancer therapies. The major find is that monotherapies were additive in their effects and that the association of targeted drugs is necessary for cancer eradication.
Role of nutritional status in predicting quality of life outcomes in cancer--a systematic review of the epidemiological literature.

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Lis, Christopher G; Gupta, Digant; Lammersfeld, Carolyn A; Markman, Maurie; Vashi, Pankaj G

2012-04-24

Malnutrition is a significant factor in predicting cancer patients' quality of life (QoL). We systematically reviewed the literature on the role of nutritional status in predicting QoL in cancer. We searched MEDLINE database using the terms "nutritional status" in combination with "quality of life" together with "cancer". Human studies published in English, having nutritional status as one of the predictor variables, and QoL as one of the outcome measures were included. Of the 26 included studies, 6 investigated head and neck cancer, 8 gastrointestinal, 1 lung, 1 gynecologic and 10 heterogeneous cancers. 24 studies concluded that better nutritional status was associated with better QoL, 1 study showed that better nutritional status was associated with better QoL only in high-risk patients, while 1 study concluded that there was no association between nutritional status and QoL. Nutritional status is a strong predictor of QoL in cancer patients. We recommend that more providers implement the American Society of Parenteral and Enteral Nutrition (ASPEN) guidelines for oncology patients, which includes nutritional screening, nutritional assessment and intervention as appropriate. Correcting malnutrition may improve QoL in cancer patients, an important outcome of interest to cancer patients, their caregivers, and families.
Peripheral lymphocyte subset variation predicts prostate cancer carbon ion radiotherapy outcomes

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Shi, Ze-Liang; Li, Bing-Xin; Wu, Xian-Wei; Li, Ping; Zhang, Qing; Wei, Xun-Bin; Fu, Shen

2016-01-01

The immune system plays a complementary role in the cytotoxic activity of radiotherapy. Here, we examined changes in immune cell subsets after heavy ion therapy for prostate cancer. The lymphocyte counts were compared with acute radiotherapy-related toxicity, defined according to the Common Terminology Criteria for Adverse Events, and short-term local efficacy, defined based on prostate-specific antigen concentrations. Confirmed prostate cancer patients who had not received previous radiotherapy were administered carbon ion radiotherapy (CIR) in daily fractions of 2.74 GyE with a total dose of 63-66 GyE. Lymphocyte subset counts were investigated before, during and after radiotherapy, and at a 1 month follow-up. Most notable among our findings, the CD4/CD8 ratio and CD19+ cell counts were consistently higher in patients with a complete response (CR) or partial response (PR) to CIR than in those classified in the stable disease (SD) group (P<0.05 for both). But CD3+ and CD8+ cell counts were lower in the CR and PR groups than in the SD group. These results indicate that variations in peripheral lymphocyte subpopulations are predictive of outcome after CIR for prostate cancer. PMID:27029063
Method of tumor volume evaluation using magnetic resonance imaging for outcome prediction in cervical cancer treated with concurrent chemotherapy and radiotherapy

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Kim, Hun Jung; Kim, Woo Chul [Inha University Hospital, Inha University School of Medicine, Seoul (Korea, Republic of)

2012-06-15

To evaluate the patterns of tumor shape and to compare tumor volume derived from simple diameter-based ellipsoid measurement with that derived from tracing the entire tumor contour using region of interest (ROI)-based 3D volumetry with respect to the prediction outcome in cervical cancer patients treated with concurrent chemotherapy and radiotherapy. Magnetic resonance imaging was performed in 98 patients with cervical cancer (stage IB-IIIB). The tumor shape was classified into two categories: ellipsoid and non-ellipsoid shape. ROI-based volumetry was derived from each magnetic resonance slice on the work station. For the diameter-based surrogate 'ellipsoid volume,' the three orthogonal diameters were measured to calculate volume as an ellipsoid. The more than half of tumor (55.1%) had a non-ellipsoid configuration. The predictions for outcome were consistent between two volume groups, with overall survival of 93.6% and 87.7% for small tumor (<20 mL), 62.9% and 69.1% for intermediate-size tumor (20-39 mL), and 14.5% and 16.7% for large tumors ({>=}40 mL) using ROI and diameter based measurement, respectively. Disease-free survival was 93.8% and 90.6% for small tumor, 54.3% and 62.7% for intermediate-size tumor, and 13.7% and 10.3% for large tumor using ROI and diameter based method, respectively. Differences in outcome between size groups were statistically significant, and the differences in outcome predicted by the tumor volume by two different methods. Our data suggested that large numbers of cervical cancers are not ellipsoid. However, simple diameter-based tumor volume measurement appears to be useful in comparison with ROI-based volumetry for predicting outcome in cervical cancer patients.
Method of tumor volume evaluation using magnetic resonance imaging for outcome prediction in cervical cancer treated with concurrent chemotherapy and radiotherapy

International Nuclear Information System (INIS)

Kim, Hun Jung; Kim, Woo Chul

2012-01-01

To evaluate the patterns of tumor shape and to compare tumor volume derived from simple diameter-based ellipsoid measurement with that derived from tracing the entire tumor contour using region of interest (ROI)-based 3D volumetry with respect to the prediction outcome in cervical cancer patients treated with concurrent chemotherapy and radiotherapy. Magnetic resonance imaging was performed in 98 patients with cervical cancer (stage IB-IIIB). The tumor shape was classified into two categories: ellipsoid and non-ellipsoid shape. ROI-based volumetry was derived from each magnetic resonance slice on the work station. For the diameter-based surrogate 'ellipsoid volume,' the three orthogonal diameters were measured to calculate volume as an ellipsoid. The more than half of tumor (55.1%) had a non-ellipsoid configuration. The predictions for outcome were consistent between two volume groups, with overall survival of 93.6% and 87.7% for small tumor (<20 mL), 62.9% and 69.1% for intermediate-size tumor (20-39 mL), and 14.5% and 16.7% for large tumors (≥40 mL) using ROI and diameter based measurement, respectively. Disease-free survival was 93.8% and 90.6% for small tumor, 54.3% and 62.7% for intermediate-size tumor, and 13.7% and 10.3% for large tumor using ROI and diameter based method, respectively. Differences in outcome between size groups were statistically significant, and the differences in outcome predicted by the tumor volume by two different methods. Our data suggested that large numbers of cervical cancers are not ellipsoid. However, simple diameter-based tumor volume measurement appears to be useful in comparison with ROI-based volumetry for predicting outcome in cervical cancer patients.
Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study

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Chu Annie TW

2010-06-01

Full Text Available Abstract Background - Genetic testing for hereditary colorectal cancer (HCRC had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. Methods - A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer Registry to determine psychological outcomes after genetic testing. Self-completed questionnaires were administered immediately before (pre-disclosure baseline and 2 weeks, 4 months and 1 year after result disclosure. Using validated psychological inventories, the cognitive style of hope was measured at baseline, and the psychological distress of depression and anxiety was measured at all time points. Results - Of the 76 participating subjects, 71 individuals (43 men and 28 women; mean age 38.9 ± 9.2 years from nine FAP and 24 HNPCC families completed the study, including 39 mutated gene carriers. Four patterns of outcome trajectories were created using established norms for the specified outcome measures of depression and anxiety. These included chronic dysfunction (13% and 8.7%, recovery (0% and 4.3%, delayed dysfunction (13% and 15.9% and resilience (76.8% and 66.7%. Two logistic regression analyses were conducted using hope at baseline to predict resilience, with depression and anxiety employed as outcome indicators. Because of the small number of participants, the chronic dysfunction and delayed dysfunction groups were combined into a non-resilient group for comparison with the resilient group in all subsequent analysis. Because of low frequencies, participants exhibiting a recovery trajectory (n = 3 for anxiety and n = 0 for depression were excluded from further analysis. Both regression equations were significant. Baseline hope was a significant
Method and timing of tumor volume measurement for outcome prediction in cervical cancer using magnetic resonance imaging

International Nuclear Information System (INIS)

Mayr, Nina A.; Taoka, Toshiaki; Yuh, William T.C.; Denning, Leah M.; Zhen, Weining K.; Paulino, Arnold C.; Gaston, Robert C.; Sorosky, Joel I.; Meeks, Sanford L.; Walker, Joan L.; Mannel, Robert S.; Buatti, John M.

2002-01-01

Purpose: Recently, imaging-based tumor volume before, during, and after radiation therapy (RT) has been shown to predict tumor response in cervical cancer. However, the effectiveness of different methods and timing of imaging-based tumor size assessment have not been investigated. The purpose of this study was to compare the predictive value for treatment outcome derived from simple diameter-based ellipsoid tumor volume measurement using orthogonal diameters (with ellipsoid computation) with that derived from more complex contour tracing/region-of-interest (ROI) analysis 3D tumor volumetry. Methods and Materials: Serial magnetic resonance imaging (MRI) examinations were prospectively performed in 60 patients with advanced cervical cancer (Stages IB 2 -IVB/recurrent) at the start of RT, during early RT (20-25 Gy), mid-RT (45-50 Gy), and at follow-up (1-2 months after RT completion). ROI-based volumetry was derived by tracing the entire tumor region in each MR slice on the computer work station. For the diameter-based surrogate ''ellipsoid volume,'' the three orthogonal diameters (d 1 , d 2 , d 3 ) were measured on film hard copies to calculate volume as an ellipsoid (d 1 x d 2 x d 3 x π/6). Serial tumor volumes and regression rates determined by each method were correlated with local control, disease-free and overall survival, and the results were compared between the two measuring methods. Median post-therapy follow-up was 4.9 years (range, 2.0-8.2 years). Results: The best method and time point of tumor size measurement for the prediction of outcome was the tumor regression rate in the mid-therapy MRI examination (at 45-50 Gy) using 3D ROI volumetry. For the pre-RT measurement both the diameter-based method and ROI volumetry provided similar predictive accuracy, particularly for patients with small ( 3 ) and large (≥100 cm 3 ) pre-RT tumor size. However, the pre-RT tumor size measured by either method had much less predictive value for the intermediate-size (40
T cell subpopulations in lymph nodes may not be predictive of patient outcome in colorectal cancer

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Yoon Han-Seung

2011-08-01

Full Text Available Abstract Background The immune response has been proposed to be an important factor in determining patient outcome in colorectal cancer (CRC. Previous studies have concentrated on characterizing T cell populations in the primary tumour where T cells with regulatory effect (Foxp3+ Tregs have been identified as both enhancing and diminishing anti-tumour immune responses. No previous studies have characterized the T cell response in the regional lymph nodes in CRC. Methods Immunohistochemistry was used to analyse CD4, CD8 or Foxp3+ T cell populations in the regional lymph nodes of patients with stage II CRC (n = 31, with (n = 13 or without (n = 18 cancer recurrence after 5 years of follow up, to determine if the priming environment for anti-tumour immunity was associated with clinical outcome. Results The proportions of CD4, CD8 or Foxp3+ cells in the lymph nodes varied widely between and within patients, and there was no association between T cell populations and cancer recurrence or other clinicopathological characteristics. Conclusions These data indicate that frequency of these T cell subsets in lymph nodes may not be a useful tool for predicting patient outcome.
Role of nutritional status in predicting quality of life outcomes in cancer – a systematic review of the epidemiological literature

Science.gov (United States)

2012-01-01

Malnutrition is a significant factor in predicting cancer patients’ quality of life (QoL). We systematically reviewed the literature on the role of nutritional status in predicting QoL in cancer. We searched MEDLINE database using the terms “nutritional status” in combination with “quality of life” together with “cancer”. Human studies published in English, having nutritional status as one of the predictor variables, and QoL as one of the outcome measures were included. Of the 26 included studies, 6 investigated head and neck cancer, 8 gastrointestinal, 1 lung, 1 gynecologic and 10 heterogeneous cancers. 24 studies concluded that better nutritional status was associated with better QoL, 1 study showed that better nutritional status was associated with better QoL only in high-risk patients, while 1 study concluded that there was no association between nutritional status and QoL. Nutritional status is a strong predictor of QoL in cancer patients. We recommend that more providers implement the American Society of Parenteral and Enteral Nutrition (ASPEN) guidelines for oncology patients, which includes nutritional screening, nutritional assessment and intervention as appropriate. Correcting malnutrition may improve QoL in cancer patients, an important outcome of interest to cancer patients, their caregivers, and families. PMID:22531478
Gene Expression Profiling to Predict Clinical Outcome of Breast Cancer: reproducing, analyzing and extending the Nature publication by vhVeer et al

NARCIS (Netherlands)

Li R.; Visser, H.M.

2010-01-01

Chemotherapy and hormonal therapy as adjuvant systemic therapies to inhibit breast cancer recurrence are not necessary for each patient. In Veer's paper "Gene expression profiling predicts clinical outcome of breast cancer" (Nature 2002, PMID: 11823860), they introduced a method based on DNA
Magnetic resonance imaging-detected tumor response for locally advanced rectal cancer predicts survival outcomes: MERCURY experience.

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Patel, Uday B; Taylor, Fiona; Blomqvist, Lennart; George, Christopher; Evans, Hywel; Tekkis, Paris; Quirke, Philip; Sebag-Montefiore, David; Moran, Brendan; Heald, Richard; Guthrie, Ashley; Bees, Nicola; Swift, Ian; Pennert, Kjell; Brown, Gina

2011-10-01

To assess magnetic resonance imaging (MRI) and pathologic staging after neoadjuvant therapy for rectal cancer in a prospectively enrolled, multicenter study. In a prospective cohort study, 111 patients who had rectal cancer treated by neoadjuvant therapy were assessed for response by MRI and pathology staging by T, N and circumferential resection margin (CRM) status. Tumor regression grade (TRG) was also assessed by MRI. Overall survival (OS) was estimated by using the Kaplan-Meier product-limit method, and Cox proportional hazards models were used to determine associations between staging of good and poor responders on MRI or pathology and survival outcomes after controlling for patient characteristics. On multivariate analysis, the MRI-assessed TRG (mrTRG) hazard ratios (HRs) were independently significant for survival (HR, 4.40; 95% CI, 1.65 to 11.7) and disease-free survival (DFS; HR, 3.28; 95% CI, 1.22 to 8.80). Five-year survival for poor mrTRG was 27% versus 72% (P = .001), and DFS for poor mrTRG was 31% versus 64% (P = .007). Preoperative MRI-predicted CRM independently predicted local recurrence (LR; HR, 4.25; 95% CI, 1.45 to 12.51). Five-year survival for poor post-treatment pathologic T stage (ypT) was 39% versus 76% (P = .001); DFS for the same was 38% versus 84% (P = .001); and LR for the same was 27% versus 6% (P = .018). The 5-year survival for involved pCRM was 30% versus 59% (P = .001); DFS, 28 versus 62% (P = .02); and LR, 56% versus 10% (P = .001). Pathology node status did not predict outcomes. MRI assessment of TRG and CRM are imaging markers that predict survival outcomes for good and poor responders and provide an opportunity for the multidisciplinary team to offer additional treatment options before planning definitive surgery. Postoperative histopathology assessment of ypT and CRM but not post-treatment N status were important postsurgical predictors of outcome.
Biomarkers for predicting complete debulking in ovarian cancer

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Fagö-Olsen, Carsten Lindberg; Ottesen, Bent; Christensen, Ib Jarle

2014-01-01

AIM: We aimed to construct and validate a model based on biomarkers to predict complete primary debulking surgery for ovarian cancer patients. PATIENTS AND METHODS: The study consisted of three parts: Part I: Biomarker data obtained from mass spectrometry, baseline data and, surgical outcome were...... used to construct predictive indices for complete tumour resection; Part II: sera from randomly selected patients from part I were analyzed using enzyme-linked immunosorbent assay (ELISA) to investigate the correlation to mass spectrometry; Part III: the indices from part I were validated in a new.......64. CONCLUSION: Our validated model based on biomarkers was unable to predict surgical outcome for patients with ovarian cancer....
The effects of lymph node status on predicting outcome in ER+ /HER2- tamoxifen treated breast cancer patients using gene signatures

International Nuclear Information System (INIS)

Cockburn, Jessica G.; Hallett, Robin M.; Gillgrass, Amy E.; Dias, Kay N.; Whelan, T.; Levine, M. N.; Hassell, John A.; Bane, Anita

2016-01-01

Lymph node (LN) status is the most important prognostic variable used to guide ER positive (+) breast cancer treatment. While a positive nodal status is traditionally associated with a poor prognosis, a subset of these patients respond well to treatment and achieve long-term survival. Several gene signatures have been established as a means of predicting outcome of breast cancer patients, but the development and indication for use of these assays varies. Here we compare the capacity of two approved gene signatures and a third novel signature to predict outcome in distinct LN negative (-) and LN+ populations. We also examine biological differences between tumours associated with LN- and LN+ disease. Gene expression data from publically available data sets was used to compare the ability of Oncotype DX and Prosigna to predict Distant Metastasis Free Survival (DMFS) using an in silico platform. A novel gene signature (Ellen) was developed by including patients with both LN- and LN+ disease and using Prediction Analysis of Microarrays (PAM) software. Gene Set Enrichment Analysis (GSEA) was used to determine biological pathways associated with patient outcome in both LN- and LN+ tumors. The Oncotype DX gene signature, which only used LN- patients during development, significantly predicted outcome in LN- patients, but not LN+ patients. The Prosigna gene signature, which included both LN- and LN+ patients during development, predicted outcome in both LN- and LN+ patient groups. Ellen was also able to predict outcome in both LN- and LN+ patient groups. GSEA suggested that epigenetic modification may be related to poor outcome in LN- disease, whereas immune response may be related to good outcome in LN+ disease. We demonstrate the importance of incorporating lymph node status during the development of prognostic gene signatures. Ellen may be a useful tool to predict outcome of patients regardless of lymph node status, or for those with unknown lymph node status. Finally we
Clinical Significance of the Prognostic Nutritional Index for Predicting Short- and Long-Term Surgical Outcomes After Gastrectomy: A Retrospective Analysis of 7781 Gastric Cancer Patients.

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Lee, Jee Youn; Kim, Hyoung-Il; Kim, You-Na; Hong, Jung Hwa; Alshomimi, Saeed; An, Ji Yeong; Cheong, Jae-Ho; Hyung, Woo Jin; Noh, Sung Hoon; Kim, Choong-Bai

2016-05-01

To evaluate the predictive and prognostic significance of the prognostic nutritional index (PNI) in a large cohort of gastric cancer patients who underwent gastrectomy.Assessing a patient's immune and nutritional status, PNI has been reported as a predictive marker for surgical outcomes in various types of cancer.We retrospectively reviewed data from a prospectively maintained database of 7781 gastric cancer patients who underwent gastrectomy from January 2001 to December 2010 at a single center. From this data, we analyzed clinicopathologic characteristics, PNI, and short- and long-term surgical outcomes for each patient. We used the PNI value for the 10th percentile (46.70) of the study cohort as a cut-off for dividing patients into low and high PNI groups.Regarding short-term outcomes, multivariate analysis showed a low PNI (odds ratio [OR] = 1.505, 95% CI = 1.212-1.869, P cancer recurrence.
Immunological tumor status may predict response to neoadjuvant chemotherapy and outcome after radical cystectomy in bladder cancer.

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Tervahartiala, Minna; Taimen, Pekka; Mirtti, Tuomas; Koskinen, Ilmari; Ecke, Thorsten; Jalkanen, Sirpa; Boström, Peter J

2017-10-04

Bladder cancer (BC) is the ninth most common cancer worldwide. Radical cystectomy (RC) with neoadjuvant chemotherapy (NAC) is recommended for muscle-invasive BC. The challenge of the neoadjuvant approach relates to challenges in selection of patients to chemotherapy that are likely to respond to the treatment. To date, there are no validated molecular markers or baseline clinical characteristics to identify these patients. Different inflammatory markers, including tumor associated macrophages with their plastic pro-tumorigenic and anti-tumorigenic functions, have extensively been under interests as potential prognostic and predictive biomarkers in different cancer types. In this immunohistochemical study we evaluated the predictive roles of three immunological markers, CD68, MAC387, and CLEVER-1, in response to NAC and outcome of BC. 41% of the patients had a complete response (pT0N0) to NAC. Basic clinicopathological variables did not predict response to NAC. In contrast, MAC387 + cells and CLEVER-1 + macrophages associated with poor NAC response, while CLEVER-1 + vessels associated with more favourable response to NAC. Higher counts of CLEVER-1 + macrophages associated with poorer overall survival and CD68 + macrophages seem to have an independent prognostic value in BC patients treated with NAC. Our findings point out that CD68, MAC387, and CLEVER-1 may be useful prognostic and predictive markers in BC.
Tumor vascularity evaluated by transrectal color Doppler US in predicting therapy outcome for low-lying rectal cancer

International Nuclear Information System (INIS)

Barbaro, Brunella; Valentini, Vincenzo; Coco, Claudio; Mancini, Anna Paola; Gambacorta, Maria Antonietta; Vecchio, Fabio Maria; Bonomo, Lorenzo

2005-01-01

Purpose: To evaluate the impact on T downstaging of the vasculature supplying blood flow to rectal cancer evaluated by color Doppler ultrasound. Methods and Materials: Color Doppler images were graded in 29 T3-staged rectal carcinoma patients sonographically just before chemoradiation. Any arterial vessels detected in rectal masses were assigned one of two grades: vascularity was considered as grade 1 for vessels feeding the periphery and as grade 2 for vessels coursing in all rectal masses within its peripheral and central portions. The pulsatility indices (PI = peak systolic velocity - end-diastolic velocity/time-averaged maximum velocity) were calculated in the central and peripheral portions. Results: The pathologic observations showed a change in stage in 15 of the 23 patients graded 2, positive predictive value 65.2% (p = 0.047), and in one of the six rectal cancers graded 1 (negative predictive value, 83.3%). The minimal peripheral PI values in rectal cancer graded 2 were higher in nonresponding (2.2 ± 1.3) than in responding lesions (1.6 ± 0.7) p = 0.01. Conclusion: Vascularity graded 2 associated with low peripheral PI values are indicators of therapy outcome. Vascularity graded 1 and high peripheral PI values in graded 2 have negative predictive value
Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

International Nuclear Information System (INIS)

Mayr, Nina A.; Huang Zhibin; Wang, Jian Z.; Lo, Simon S.; Fan, Joline M.; Grecula, John C.; Sammet, Steffen; Sammet, Christina L.; Jia Guang; Zhang Jun; Knopp, Michael V.; Yuh, William T.C.

2012-01-01

Purpose: Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. Methods and Materials: DCE-MRI was performed in 102 stage IB 2 –IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity ( 20, >13, and >5 cm 3 , respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 × 10 −8 , 2.0 × 10 −8 ) and disease-specific survival (p = 1.9 × 10 −4 , 2.1 × 10 −6 , 2.5 × 10 −7 , respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. Discussion: Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2–5 weeks into treatment.

Combined-modality treatment and organ preservation in bladder cancer. Do molecular markers predict outcome?

International Nuclear Information System (INIS)

Weiss, C.; Roedel, F.; Wolf, I.; Sauer, R.; Roedel, C.; Papadopoulos, T.; Engehausen, D.G.; Schrott, K.M.

2005-01-01

Purpose: in invasive bladder cancer, several groups have reported the value of organ preservation by a combined-treatment approach, including transurethral resection (TUR-BT) and radiochemotherapy (RCT). As more experience is acquired with this organ-sparing treatment, patient selection needs to be optimized. Clinical factors are limited in their potential to identify patients most likely to respond to RCT, thus, additional molecular markers for predicting treatment response of individual lesions are sorely needed. Patients and methods: the apoptotic index (AI) and Ki-67 index were evaluated by immunohistochemistry on pretreatment biopsies of 134 patients treated for bladder cancer by TUR-BT and RCT. Expression of each marker as well as clinicopathologic factors were then correlated with initial response, local control and cancer-specific survival with preserved bladder in univariate and multivariate analysis. Results: the median AI for all patients was 1.5% (range 0.2-7.4%). The percentage of Ki-67-positive cells in the tumors ranged from 0.2% to 85% with a median of 14.2%. A significant correlation was found for AI and tumor differentiation (G1/2: AI = 1.3% vs. G3/4: AI = 1.6%; p = 0.01). A complete response at restaging TUR-BT was achieved in 76% of patients. Factors predictive of complete response included T-category (p < 0.0001), resection status (p = 0.02), lymphovascular invasion (p = 0.01), and Ki-67 index (p = 0.02). For local control, AI (p = 0.04) and Ki-67 index (p = 0.05) as well as T-category (p = 0.005), R-status (p = 0.05), and lymphatic vessel invasion (p = 0.05) reached statistical significance. Out of the molecular markers only high Ki-67 levels were associated to cause-specific survival with preserved bladder. On multivariate analysis, T-category was the strongest independent factor for initial response, local control and cancer-specific survival with preserved bladder. Conclusion: The indices of pretreatment apoptosis and Ki-67 predict a
Predicting an optimal outcome after radical prostatectomy: the trifecta nomogram.

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Eastham, James A; Scardino, Peter T; Kattan, Michael W

2008-06-01

The optimal outcome after radical prostatectomy for clinically localized prostate cancer is freedom from biochemical recurrence along with the recovery of continence and erectile function, a so-called trifecta. We evaluated our series of open radical prostatectomy cases to determine the likelihood of this outcome and develop a nomogram predicting the trifecta. We reviewed the records of patients undergoing open radical prostatectomy for clinical stage T1c-T3a prostate cancer at our center during 2000 to 2006. Men were excluded if they received preoperative hormonal therapy, chemotherapy or radiation therapy, if pretreatment prostate specific antigen was more than 50 ng/ml, or if they were impotent or incontinent before radical prostatectomy. A total of 1,577 men were included in the study. Freedom from biochemical recurrence was defined as post-radical prostatectomy prostate specific antigen less than 0.2 ng/ml. Continence was defined as not having to wear any protective pads. Potency was defined as erection adequate for intercourse upon most attempts with or without phosphodiesterase-5 inhibitor. Mean patient age was 58 years and mean pretreatment prostate specific antigen was 6.4 ng/ml. A trifecta outcome (cancer-free status with recovery of continence and potency) was achieved in 62% of patients. In a nomogram developed to predict the likelihood of the trifecta baseline prostate specific antigen was the major predictive factor. Area under the ROC curve for the nomogram was 0.773 and calibration appeared excellent. A trifecta (optimal) outcome can be achieved in most men undergoing radical prostatectomy. The nomogram permits patients to estimate preoperatively their likelihood of an optimal outcome after radical prostatectomy.
A comprehensive review of nongenetic prognostic and predictive factors influencing the heterogeneity of outcomes in advanced non-small-cell lung cancer

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Cuyún Carter G

2014-10-01

Full Text Available Gebra Cuyún Carter,1 Amy M Barrett,2 James A Kaye,3 Astra M Liepa,1 Katherine B Winfree,1 William J John1 1Eli Lilly and Company, Indianapolis, IN, USA; 2RTI Health Solutions, Research Triangle Park, NC, USA; 3RTI Health Solutions, Waltham, MA, USA Abstract: While there have been advances in treatment options for those with advanced non-small-cell lung cancer, unmet medical needs remain, partly due to the heterogeneity of treatment effect observed among patients. The goals of this literature review were to provide updated information to complement past reviews and to identify a comprehensive set of nongenetic prognostic and predictive baseline factors that may account for heterogeneity of outcomes in advanced non-small-cell lung cancer. A review of the literature between 2000 and 2010 was performed using PubMed, Embase, and Cochrane Library. All relevant studies that met the inclusion criteria were selected and data elements were abstracted. A classification system was developed to evaluate the level of evidence for each study. A total of 54 studies were selected for inclusion. Patient-related factors (eg, performance status, sex, and age were the most extensively researched nongenetic prognostic factors, followed by disease stage and histology. Moderately researched prognostic factors were weight-related variables and number or site of metastases, and the least studied were comorbidities, previous therapy, smoking status, hemoglobin level, and health-related quality of life/symptom severity. The prognostic factors with the most consistently demonstrated associations with outcomes were performance status, number or site of metastases, previous therapy, smoking status, and health-related quality of life. Of the small number of studies that assessed predictive factors, those that were found to be significantly predictive of outcomes were performance status, age, disease stage, previous therapy, race, smoking status, sex, and histology. These
Degradation Rate of 5-Fluorouracil in Metastatic Colorectal Cancer: A New Predictive Outcome Biomarker?

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Andrea Botticelli

Full Text Available 5-FU based chemotherapy is the most common first line regimen used for metastatic colorectal cancer (mCRC. Identification of predictive markers of response to chemotherapy is a challenging approach for drug selection. The present study analyzes the predictive role of 5-FU degradation rate (5-FUDR and genetic polymorphisms (MTHFR, TSER, DPYD on survival.Genetic polymorphisms of MTHFR, TSER and DPYD, and the 5-FUDR of homogenous patients with mCRC were retrospectively studied. Genetic markers and the 5-FUDR were correlated with clinical outcome.133 patients affected by mCRC, treated with fluoropyrimidine-based chemotherapy from 2009 to 2014, were evaluated. Patients were classified into three metabolic classes, according to normal distribution of 5-FUDR in more than 1000 patients, as previously published: poor-metabolizer (PM with 5-FU-DR ≤ 0,85 ng/ml/106 cells/min (8 pts; normal metabolizer with 0,85 < 5-FU-DR < 2,2 ng/ml/106 cells/min (119 pts; ultra-rapid metabolizer (UM with 5-FU-DR ≥ 2,2 ng/ml/106 cells/min (6 pts. PM and UM groups showed a longer PFS respect to normal metabolizer group (14.5 and 11 months respectively vs 8 months; p = 0.029. A higher G3-4 toxicity rate was observed in PM and UM, respect to normal metabolizer (50% in both PM and UM vs 18%; p = 0.019. No significant associations between genes polymorphisms and outcomes or toxicities were observed.5-FUDR seems to be significantly involved in predicting survival of patients who underwent 5-FU based CHT for mCRC. Although our findings require confirmation in large prospective studies, they reinforce the concept that individual genetic variation may allow personalized selection of chemotherapy to optimize clinical outcomes.
Cytoplasmic localization of alteration/deficiency in activation 3 (ADA3) predicts poor clinical outcome in breast cancer patients.

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Mirza, Sameer; Rakha, Emad A; Alshareeda, Alaa; Mohibi, Shakur; Zhao, Xiangshan; Katafiasz, Bryan J; Wang, Jun; Gurumurthy, Channabasavaiah Basavaraju; Bele, Aditya; Ellis, Ian O; Green, Andrew R; Band, Hamid; Band, Vimla

2013-02-01

Transcriptional activation by estrogen receptor (ER) is a key step to breast oncogenesis. Given previous findings that ADA3 is a critical component of HAT complexes that regulate ER function and evidence that overexpression of other ER coactivators such as SRC-3 is associated with clinical outcomes in breast cancer, the current study was designed to assess the potential significance of ADA3 expression/localization in human breast cancer patients. In this study, we analyzed ADA3 expression in breast cancer tissue specimens and assessed the correlation of ADA3 staining with cancer progression and patient outcome. Tissue microarrays prepared from large series of breast cancer patients with long-term follow-ups were stained with anti-ADA3 monoclonal antibody using immunohistochemistry. Samples were analyzed for ADA3 expression followed by correlation with various clinicopathological parameters and patients' outcomes. We report that breast cancer specimens show predominant nuclear, cytoplasmic, or mixed nuclear + cytoplasmic ADA3 staining patterns. Predominant nuclear ADA3 staining correlated with ER+ status. While predominant cytoplasmic ADA3 staining negatively correlated with ER+ status, but positively correlated with ErbB2, EGFR, and Ki67. Furthermore, a positive correlation of cytoplasmic ADA3 was observed with higher histological grade, mitotic counts, Nottingham Prognostic Index, and positive vascular invasion. Patients with nuclear ADA3 and ER positivity have better breast cancer specific survival and distant metastasis free survival. Significantly, cytoplasmic expression of ADA3 showed a strong positive association with reduced BCSS and DMFS in ErbB2+/EGFR+ patients. Although in multivariate analyses ADA3 expression was not an independent marker of survival, predominant nuclear ADA3 staining in breast cancer tissues correlates with ER+ expression and together serves as a marker of good prognosis, whereas predominant cytoplasmic ADA3 expression correlates with
Prediction of metastasis from low-malignant breast cancer by gene expression profiling

DEFF Research Database (Denmark)

Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja

2007-01-01

examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients...... with different characteristics and risk, expression-based classification specifically developed in low-risk patients have higher predictive power in this group.......Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...
Circulating cell death products predict clinical outcome of colorectal cancer patients

International Nuclear Information System (INIS)

Koelink, Pim J; Lamers, Cornelis BHW; Hommes, Daan W; Verspaget, Hein W

2009-01-01

Tumor cell death generates products that can be measured in the circulation of cancer patients. CK18-Asp396 (M30 antigen) is a caspase-degraded product of cytokeratin 18 (CK18), produced by apoptotic epithelial cells, and is elevated in breast and lung cancer patients. We determined the CK18-Asp396 and total CK18 levels in plasma of 49 colorectal cancer patients, before and after surgical resection of the tumor, by ELISA. Correlations with patient and tumor characteristics were determined by Kruskal-Wallis H and Mann-Whitney U tests. Disease-free survival was determined using Kaplan-Meier methodology with Log Rank tests, and univariate and multivariate Cox proportional hazard analysis. Plasma CK18-Asp396 and total CK18 levels in colorectal cancer patients were related to disease stage and tumor diameter, and were predictive of disease-free survival, independent of disease-stage, with hazard ratios (HR) of patients with high levels (> median) compared to those with low levels (≤ median) of 3.58 (95% CI: 1.17–11.02) and 3.58 (95% CI: 0.97–7.71), respectively. The CK18-Asp396/CK18 ratio, which decreased with tumor progression, was also predictive of disease-free survival, with a low ratio (≤ median) associated with worse disease-free survival: HR 2.78 (95% CI: 1.06–7.19). Remarkably, the plasma CK18-Asp396 and total CK18 levels after surgical removal of the tumor were also predictive of disease-free survival, with patients with high levels having a HR of 3.78 (95% CI: 0.77–18.50) and 4.12 (95% CI: 0.84–20.34), respectively, indicating that these parameters can be used also to monitor patients after surgery. CK18-Asp396 and total CK18 levels in the circulation of colorectal cancer patients are predictive of tumor progression and prognosis and might be helpful for treatment selection and monitoring of these patients
Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria

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Kimmel Marek

2011-05-01

Full Text Available Abstract Background Volunteering participants in disease studies tend to be healthier than the general population partially due to specific enrollment criteria. Using modeling to accurately predict outcomes of cohort studies enrolling volunteers requires adjusting for the bias introduced in this way. Here we propose a new method to account for the effect of a specific form of healthy volunteer bias resulting from imposing disease status-related eligibility criteria, on disease-specific mortality, by explicitly modeling the length of the time interval between the moment when the subject becomes ineligible for the study, and the outcome. Methods Using survival time data from 1190 newly diagnosed lung cancer patients at MD Anderson Cancer Center, we model the time from clinical lung cancer diagnosis to death using an exponential distribution to approximate the length of this interval for a study where lung cancer death serves as the outcome. Incorporating this interval into our previously developed lung cancer risk model, we adjust for the effect of disease status-related eligibility criteria in predicting the number of lung cancer deaths in the control arm of CARET. The effect of the adjustment using the MD Anderson-derived approximation is compared to that based on SEER data. Results Using the adjustment developed in conjunction with our existing lung cancer model, we are able to accurately predict the number of lung cancer deaths observed in the control arm of CARET. Conclusions The resulting adjustment was accurate in predicting the lower rates of disease observed in the early years while still maintaining reasonable prediction ability in the later years of the trial. This method could be used to adjust for, or predict the duration and relative effect of any possible biases related to disease-specific eligibility criteria in modeling studies of volunteer-based cohorts.
A new nomogram to predict pathologic outcome following radical prostatectomy

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Alexandre Crippa

2006-04-01

Full Text Available OBJECTIVE: To develop a preoperative nomogram to predict pathologic outcome in patients submitted to radical prostatectomy for clinical localized prostate cancer. MATERIALS AND METHODS: Nine hundred and sixty patients with clinical stage T1 and T2 prostate cancer were evaluated following radical prostatectomy, and 898 were included in the study. Following a multivariate analysis, nomograms were developed incorporating serum PSA, biopsy Gleason score, and percentage of positive biopsy cores in order to predict the risks of extraprostatic tumor extension, and seminal vesicle involvement. RESULTS: In univariate analysis there was a significant association between percentage of positive biopsy cores (p < 0.001, serum PSA (p = 0.001 and biopsy Gleason score (p < 0.001 with extraprostatic tumor extension. A similar pathologic outcome was seen among tumors with Gleason score 7, and Gleason score 8 to 10. In multivariate analysis, the 3 preoperative variables showed independent significance to predict tumor extension. This allowed the development of nomogram-1 (using Gleason scores in 3 categories - 2 to 6, 7 and 8 to 10 and nomogram-2 (using Gleason scores in 2 categories - 2 to 6 and 7 to 10 to predict disease extension based on these 3 parameters. In the validation analysis, 87% and 91.1% of the time the nomograms-1 and 2, correctly predicted the probability of a pathological stage to within 10% respectively. CONCLUSION: Incorporating percent of positive biopsy cores to a nomogram that includes preoperative serum PSA and biopsy Gleason score, can accurately predict the presence of extraprostatic disease extension in patients with clinical localized prostate cancer.
Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

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Mayr, Nina A., E-mail: Nina.Mayr@osumc.edu [Department of Radiation Oncology, Ohio State University, Columbus, OH (United States); Huang Zhibin [Department of Radiation Oncology and Department of Physics, East Carolina University, Greenville, NC (United States); Wang, Jian Z. [Department of Radiation Oncology, Ohio State University, Columbus, OH (United States); Lo, Simon S. [Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH (United States); Fan, Joline M. [Department of Molecular Biology, Stanford University, Stanford, CA (United States); Grecula, John C. [Department of Radiation Oncology, Ohio State University, Columbus, OH (United States); Sammet, Steffen [Department of Radiology, University of Chicago, Chicago, IL (United States); Department of Radiology, Ohio State University, Columbus, OH (United States); Sammet, Christina L. [Department of Radiology, University of Chicago, Chicago, IL (United States); Jia Guang; Zhang Jun; Knopp, Michael V.; Yuh, William T.C. [Department of Radiology, Ohio State University, Columbus, OH (United States)

2012-07-01

Purpose: Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. Methods and Materials: DCE-MRI was performed in 102 stage IB{sub 2}-IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity (<2.1 compared with precontrast image, determined by previous receiver operator characteristic analysis). FRVs were correlated with treatment outcome (follow-up: 0.2-9.4, mean 6.8 years) and compared with ATVs (Mann-Whitney, Kaplan-Meier, and multivariate analyses). Results: Before and during therapy at 2-2.5 and 4-5 weeks of RT, FRVs >20, >13, and >5 cm{sup 3}, respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 Multiplication-Sign 10{sup -8}, 2.0 Multiplication-Sign 10{sup -8}) and disease-specific survival (p = 1.9 Multiplication-Sign 10{sup -4}, 2.1 Multiplication-Sign 10{sup -6}, 2.5 Multiplication-Sign 10{sup -7}, respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. Discussion: Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2
Sarcopenia and sarcopenic obesity: do they predict inferior oncologic outcomes after gastrointestinal cancer surgery?

Directory of Open Access Journals (Sweden)

Kimberly L. Mei

2016-10-01

Full Text Available Abstract Sarcopenia, or loss of skeletal muscle mass and quality, has been studied as part of aging and adverse health outcomes in elderly patients but has only recently been evaluated as a separate condition in cancer patients and important indicator of adverse outcomes. Currently, its definition and method of assessment are still being debated. Sarcopenia within an increasingly obese population has led to a subgroup with sarcopenic obesity, at even higher risk of adverse outcomes. Yet, sarcopenia often goes undiagnosed in these patients, hidden beneath higher body mass index. Identifying sarcopenic and sarcopenic obese subpopulations would allow for more effective treatment plans and potential avoidance of suboptimal outcomes, as well as the chance to intervene and combat these modifiable risk factors. This review will examine available literature on the definition and methods of evaluating sarcopenia and sarcopenic obesity, summarize the effectiveness of sarcopenia and sarcopenic obesity as predictors of outcomes after gastrointestinal cancer surgery, including colorectal cancer resection, liver resection, and pancreatic resection, and outline strategies to minimize the impact of sarcopenia. It is clear that untreated sarcopenia and sarcopenic obesity can be associated with suboptimal post-operative outcomes, especially infections and disease-free or overall survival.
Predicting an Optimal Outcome after Radical Prostatectomy: The “Trifecta” Nomogram

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Eastham, James A.; Scardino, Peter T.; Kattan, Michael W.

2014-01-01

Purpose The optimal outcome after radical prostatectomy (RP) for clinically localized prostate cancer is freedom from biochemical recurrence (BCR) along with recovery of continence and erectile function, a so-called trifecta. We evaluated our series of open radical prostatectomy patients to determine the likelihood of this outcome and to develop a nomogram predicting the trifecta. Material and Methods We reviewed records of patients undergoing open RP for clinical stage T1c–T3a prostate cancer at our center during 2000–2006. Men were excluded if they received preoperative hormonal therapy, chemotherapy, or radiation therapy; if their pre-treatment PSA was >50 ng/ml; or if they were impotent or incontinent before RP; 1577 men were included in the study. Freedom from BCR was defined as post-RP PSA <0.2 ng/ml. Continence was defined as not having to wear any protective pads. Potency was defined as erections adequate for intercourse on the majority of attempts, with or without a phosphodiesterase-5 inhibitor. Results Mean patient age was 58 years and mean pretreatment PSA was 6.4 ng/ml. A trifecta outcome (cancer-free status with recovery of continence and potency) was achieved in 62% of patients. In a nomogram developed to predict the likelihood of the trifecta, baseline PSA was the major predictive factor. The area under the receiver operating characteristic curve for the nomogram was 0.773, and calibration appeared excellent. Conclusions A trifecta (optimal) outcome can be achieved in the majority of men undergoing RP. The nomogram will permit patients to estimate preoperatively their likelihood of an optimal outcome after RP. PMID:18423693
SU-E-J-95: Predicting Treatment Outcomes for Prostate Cancer: Irradiation Responses of Prostate Cancer Stem Cells

International Nuclear Information System (INIS)

Wang, K

2014-01-01

Purpose: Most prostate cancers are slow-growing diseases but normally require much higher doses (80Gy) with conventional fractionation radiotherapy, comparing to other more aggressive cancers. This study is to disclose the radiobiological basis of this discrepancy by proposing the concept of prostate cancer stem cells (CSCs) and examining their specific irradiation responses. Methods: There are overwhelming evidences that CSC may keep their stemness, e.g. the competency of cell differentiation, in hypoxic microenvironments and hence become radiation resistive, though the probability is tiny for aggressiveness cancers. Tumor hypoxia used to be considered as an independent reason for poor treatment outcomes, and recent evidences showed that even prostate cancers were also hypoxic though they are very slow-growing. In addition, to achieve comparable outcomes to other much more aggressive cancers, much higher doses (rather than lower doses) are always needed for prostate cancers, regardless of its non-aggressiveness. All these abnormal facts can only be possibly interpreted by the irradiation responses characteristics of prostate CSCs. Results: Both normal cancer cells (NCCs) and CSCs exiting in tumors, in which NCCs are mainly for symptoms whereas killing all CSCs achieves disease-free. Since prostate cancers are slow-growing, the hypoxia in prostate cancers cannot possibly from NCCs, thus it is caused by hypoxic CSCs. However, single hypoxic cell cannot be imaged due to limitation of imaging techniques, unless a large group of hypoxic cells exist together, thus most of CSCs in prostate cancers are virtually hypoxic, i.e. not in working mode because CSCs in proliferating mode have to be normoxic, and this explains why prostate cancers are unaggressive. Conclusion: The fractional dose in conventional radiotherapy (∼2Gy) could only kill NCCs and CSCs in proliferating modes, whereas most CSCs survived fractional treatments since they were hypoxic, thus to eliminate all
SU-D-BRA-04: Fractal Dimension Analysis of Edge-Detected Rectal Cancer CTs for Outcome Prediction

International Nuclear Information System (INIS)

Zhong, H; Wang, J; Hu, W; Shen, L; Wan, J; Zhou, Z; Zhang, Z

2015-01-01

Purpose: To extract the fractal dimension features from edge-detected rectal cancer CTs, and to examine the predictability of fractal dimensions to outcomes of primary rectal cancer patients. Methods: Ninety-seven rectal cancer patients treated with neo-adjuvant chemoradiation were enrolled in this study. CT images were obtained before chemoradiotherapy. The primary lesions of the rectal cancer were delineated by experienced radiation oncologists. These images were extracted and filtered by six different Laplacian of Gaussian (LoG) filters with different filter values (0.5–3.0: from fine to coarse) to achieve primary lesions in different anatomical scales. Edges of the original images were found at zero-crossings of the filtered images. Three different fractal dimensions (box-counting dimension, Minkowski dimension, mass dimension) were calculated upon the image slice with the largest cross-section of the primary lesion. The significance of these fractal dimensions in survival, recurrence and metastasis were examined by Student’s t-test. Results: For a follow-up time of two years, 18 of 97 patients had experienced recurrence, 24 had metastasis, and 18 were dead. Minkowski dimensions under large filter values (2.0, 2.5, 3.0) were significantly larger (p=0.014, 0.006, 0.015) in patients with recurrence than those without. For metastasis, only box-counting dimensions under a single filter value (2.5) showed differences (p=0.016) between patients with and without. For overall survival, box-counting dimensions (filter values = 0.5, 1.0, 1.5), Minkowski dimensions (filter values = 0.5, 1.5, 2.0, 2,5) and mass dimensions (filter values = 1.5, 2.0) were all significant (p<0.05). Conclusion: It is feasible to extract shape information by edge detection and fractal dimensions analysis in neo-adjuvant rectal cancer patients. This information can be used to prognosis prediction
Prognostic nutritional index predicts postoperative complications and long-term outcomes of gastric cancer.

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Jiang, Nan; Deng, Jing-Yu; Ding, Xue-Wei; Ke, Bin; Liu, Ning; Zhang, Ru-Peng; Liang, Han

2014-08-14

To investigate the impact of prognostic nutritional index (PNI) on the postoperative complications and long-term outcomes in gastric cancer patients undergoing total gastrectomy. The data for 386 patients with gastric cancer were extracted and analyzed between January 2003 and December 2008 in our center. The patients were divided into two groups according to the cutoff value of the PNI: those with a PNI ≥ 46 and those with a PNI gastric cancer patients.
Tumor size evaluated by pelvic examination compared with 3-D MR quantitative analysis in the prediction of outcome for cervical cancer

International Nuclear Information System (INIS)

Mayr, Nina A.; Jie Zheng; Yuh, William T.C.; B-Chen, Wen; Ehrhardt, James C.; Sorosky, Joel I.; Pelsang, Retta E.; Hussey, David H.

1996-01-01

Purpose: Tumor size estimated by pelvic examination (PE) is an important prognostic factor in cervical cancer treated with radiation therapy (RT). Recent histologic correlation studies also showed that magnetic resonance imaging (MR) provides high accuracy in the measurement of the actual tumor volume. The purpose of this study was to: (a) compare the accuracy of PE and MR in predicting outcome, and (b) correlate tumor measurements by PE vs. MR. Materials and Methods: Tumor measurements were performed prospectively in 172 MR studies in 43 patients with advanced cervical cancer. MR and PE were performed at the same time intervals: exam 1 (start of RT), exam 2 (after 20-24 Gy/2-2.5 wks), exam 3 (after 40-50 Gy/4-5 wks), and exam 4 (1-2 months after RT). PE determined tumor diameters in anteroposterior (ap), lateral (lat), and craniocaudal (cc) direction, and clinical tumor size was computed as maximum diameter, average diameter, and volume (ap x lat x cc x π/6). MR-derived tumor size was computed by summation of the tumor areas in each slice and multiplication by the slice thickness. Tumor regression during RT was calculated for each method as percentage of initial volume. The measurements were correlated with local recurrence and disease-free survival. Median follow-up was 18 months (range: 3-50 months). Results: Prediction of local control. Overall, tumor regression rate (rapid vs. slow; Table 1) was more precise than the initial tumor size (Table 2) in the prediction of outcome. MR provided a significantly more accurate and earlier prediction of local control (exam 2 and 3 vs. exam 4; Table 1) and disease-free survival than PE. Based on the initial tumor size (Table 2), MR was also better than PE in predicting local control and disease-free survival, particularly in large (≥ 100 cm 3 ) tumors. Size correlation. Tumor size (maximum diameter, average diameter, volume) by PE and MR did not correlate well (r 2 = .51, .61, .58, respectively). When using MR
Association of pretreatment neutrophil-lymphocyte ratio and outcome in emergency colorectal cancer care.

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Palin, R P; Devine, A T; Hicks, G; Burke, D

2018-04-01

Introduction The association between the neutrophil-lymphocyte ratio (NLR) and outcome in elective colorectal cancer surgery is well established; the relationship between NLR and the emergency colorectal cancer patient is, as yet, unexplored. This paper evaluates the predictive quality of the NLR for outcome in the emergency colorectal cancer patient. Materials and Methods A total of 187 consecutive patients who underwent emergency surgery for colorectal cancer were included in the study. NLR was calculated from the haematological tests done on admission. Receiver operating characteristic analyses were used to determine the most suitable cut-off for NLR. Outcomes were assessed by mortality at 30 and 90 days using stepwise Cox proportional hazards regression. Results An NLR cut-off of 5 was found to have the highest sensitivity and specificity. At 30 days, age and time from admission to surgery were associated with increased mortality; a high NLR was associated with an increased risk of mortality in univariate but not multivariate analysis. At 90 days, age, NLR, time from admission to surgery and nodal status were all significantly associated with increased mortality on multivariate analysis. Conclusions Pre-operative NLR is a cheap, easily performed and useful clinical tool to aid prediction of outcome in the emergency colorectal cancer patient.
Uncertainties in model-based outcome predictions for treatment planning

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Deasy, Joseph O.; Chao, K.S. Clifford; Markman, Jerry

2001-01-01

Purpose: Model-based treatment-plan-specific outcome predictions (such as normal tissue complication probability [NTCP] or the relative reduction in salivary function) are typically presented without reference to underlying uncertainties. We provide a method to assess the reliability of treatment-plan-specific dose-volume outcome model predictions. Methods and Materials: A practical method is proposed for evaluating model prediction based on the original input data together with bootstrap-based estimates of parameter uncertainties. The general framework is applicable to continuous variable predictions (e.g., prediction of long-term salivary function) and dichotomous variable predictions (e.g., tumor control probability [TCP] or NTCP). Using bootstrap resampling, a histogram of the likelihood of alternative parameter values is generated. For a given patient and treatment plan we generate a histogram of alternative model results by computing the model predicted outcome for each parameter set in the bootstrap list. Residual uncertainty ('noise') is accounted for by adding a random component to the computed outcome values. The residual noise distribution is estimated from the original fit between model predictions and patient data. Results: The method is demonstrated using a continuous-endpoint model to predict long-term salivary function for head-and-neck cancer patients. Histograms represent the probabilities for the level of posttreatment salivary function based on the input clinical data, the salivary function model, and the three-dimensional dose distribution. For some patients there is significant uncertainty in the prediction of xerostomia, whereas for other patients the predictions are expected to be more reliable. In contrast, TCP and NTCP endpoints are dichotomous, and parameter uncertainties should be folded directly into the estimated probabilities, thereby improving the accuracy of the estimates. Using bootstrap parameter estimates, competing treatment
Technical Performance as a Predictor of Clinical Outcomes in Laparoscopic Gastric Cancer Surgery.

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Fecso, Andras B; Bhatti, Junaid A; Stotland, Peter K; Quereshy, Fayez A; Grantcharov, Teodor P

2018-03-23

The purpose of this study was to evaluate the relationship between technical performance and patient outcomes in laparoscopic gastric cancer surgery. Laparoscopic gastrectomy for cancer is an advanced procedure with high rate of postoperative morbidity and mortality. Many variables including patient, disease, and perioperative management factors have been shown to impact postoperative outcomes; however, the role of surgical performance is insufficiently investigated. A retrospective review was performed for all patients who had undergone laparoscopic gastrectomy for cancer at 3 teaching institutions between 2009 and 2015. Patients with available, unedited video-recording of their procedure were included in the study. Video files were rated for technical performance, using Objective Structured Assessments of Technical Skills (OSATS) and Generic Error Rating Tool instruments. The main outcome variable was major short-term complications. The effect of technical performance on patient outcomes was assessed using logistic regression analysis with backward selection strategy. Sixty-one patients with available video recordings were included in the study. The overall complication rate was 29.5%. The mean Charlson comorbidity index, type of procedure, and the global OSATS score were included in the final predictive model. Lower performance score (OSATS ≤29) remained an independent predictor for major short-term outcomes (odds ratio 6.49), while adjusting for comorbidities and type of procedure. Intraoperative technical performance predicts major short-term outcomes in laparoscopic gastrectomy for cancer. Ongoing assessment and enhancement of surgical skills using modern, evidence-based strategies might improve short-term patient outcomes. Future work should focus on developing and studying the effectiveness of such interventions in laparoscopic gastric cancer surgery.
Predictive utility of cyclo-oxygenase-2 expression by colon and rectal cancer.

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Lobo Prabhu, Kristel C; Vu, Lan; Chan, Simon K; Phang, Terry; Gown, Allen; Jones, Steven J; Wiseman, Sam M

2014-05-01

Cyclo-oxygenase-2 (COX-2), an inducible enzyme expressed in areas of inflammation, is a target of interest for colorectal cancer therapy. Currently, the predictive significance of COX-2 in colorectal cancer remains unclear. Tissue microarrays were constructed using 118 colon cancer and 85 rectal cancer specimens; 44 synchronous metastatic colon cancer and 22 rectal cancer lymph nodes were also evaluated. COX-2 expression was assessed by immunohistochemistry. Univariate analysis was used to determine the predictive significance of clinicopathologic variables. Overall survival, disease-specific survival, and disease-free survival were the main outcomes examined. COX-2 was found to be expressed in 93% of colon cancers and 87% of rectal cancers. Decreased COX-2 expression was related to decreased disease-specific survival (P = .016) and decreased disease-free survival (P = .019) in the rectal cancer cohort but not in the colon cancer cohort. COX-2 expression has predictive utility for management of rectal but not colon cancer. Copyright © 2014 Elsevier Inc. All rights reserved.

Hypoxic Prostate/Muscle PO2 Ratio Predicts for Outcome in Patients With Localized Prostate Cancer: Long-Term Results

International Nuclear Information System (INIS)

Turaka, Aruna; Buyyounouski, Mark K.; Hanlon, Alexandra L.; Horwitz, Eric M.; Greenberg, Richard E.; Movsas, Benjamin

2012-01-01

Purpose: To correlate tumor oxygenation status with long-term biochemical outcome after prostate brachytherapy. Methods and Materials: Custom-made Eppendorf PO 2 microelectrodes were used to obtain PO 2 measurements from the prostate (P), focused on positive biopsy locations, and normal muscle tissue (M), as a control. A total of 11,516 measurements were obtained in 57 men with localized prostate cancer immediately before prostate brachytherapy was given. The Eppendorf histograms provided the median PO 2 , mean PO 2 , and % 2 ratio on BF. Results: With a median follow-up time of 8 years, 12 men had ASTRO BF and 8 had Phoenix BF. On multivariate analysis, P/M PO 2 ratio 2 ratio 2 ratio) significantly predicts for poor long-term biochemical outcome, suggesting that novel hypoxic strategies should be investigated.
Migration Phenotype of Brain-Cancer Cells Predicts Patient Outcomes

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Chris L. Smith

2016-06-01

Full Text Available Glioblastoma multiforme is a heterogeneous and infiltrative cancer with dismal prognosis. Studying the migratory behavior of tumor-derived cell populations can be informative, but it places a high premium on the precision of in vitro methods and the relevance of in vivo conditions. In particular, the analysis of 2D cell migration may not reflect invasion into 3D extracellular matrices in vivo. Here, we describe a method that allows time-resolved studies of primary cell migration with single-cell resolution on a fibrillar surface that closely mimics in vivo 3D migration. We used this platform to screen 14 patient-derived glioblastoma samples. We observed that the migratory phenotype of a subset of cells in response to platelet-derived growth factor was highly predictive of tumor location and recurrence in the clinic. Therefore, migratory phenotypic classifiers analyzed at the single-cell level in a patient-specific way can provide high diagnostic and prognostic value for invasive cancers.
Convolutional neural networks for prostate cancer recurrence prediction

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Kumar, Neeraj; Verma, Ruchika; Arora, Ashish; Kumar, Abhay; Gupta, Sanchit; Sethi, Amit; Gann, Peter H.

2017-03-01

Accurate prediction of the treatment outcome is important for cancer treatment planning. We present an approach to predict prostate cancer (PCa) recurrence after radical prostatectomy using tissue images. We used a cohort whose case vs. control (recurrent vs. non-recurrent) status had been determined using post-treatment follow up. Further, to aid the development of novel biomarkers of PCa recurrence, cases and controls were paired based on matching of other predictive clinical variables such as Gleason grade, stage, age, and race. For this cohort, tissue resection microarray with up to four cores per patient was available. The proposed approach is based on deep learning, and its novelty lies in the use of two separate convolutional neural networks (CNNs) - one to detect individual nuclei even in the crowded areas, and the other to classify them. To detect nuclear centers in an image, the first CNN predicts distance transform of the underlying (but unknown) multi-nuclear map from the input HE image. The second CNN classifies the patches centered at nuclear centers into those belonging to cases or controls. Voting across patches extracted from image(s) of a patient yields the probability of recurrence for the patient. The proposed approach gave 0.81 AUC for a sample of 30 recurrent cases and 30 non-recurrent controls, after being trained on an independent set of 80 case-controls pairs. If validated further, such an approach might help in choosing between a combination of treatment options such as active surveillance, radical prostatectomy, radiation, and hormone therapy. It can also generalize to the prediction of treatment outcomes in other cancers.
The predictive value of 2-year posttreatment biopsy after prostate cancer radiotherapy for eventual biochemical outcome

International Nuclear Information System (INIS)

Vance, Waseet; Tucker, Susan L.; Crevoisier, Renaud de; Kuban, Deborah A.; Cheung, M. Rex

2007-01-01

Purpose: To determine the value of a 2-year post-radiotherapy (RT) prostate biopsy for predicting eventual biochemical failure in patients who were treated for localized prostate cancer. Methods and Materials: This study comprised 164 patients who underwent a planned 2-year post-RT prostate biopsy. The independent prognostic value of the biopsy results for forecasting eventual biochemical outcome and overall survival was tested with other factors (the Gleason score, 1992 American Joint Committee on Cancer tumor stage, pretreatment prostate-specific antigen level, risk group, and RT dose) in a multivariate analysis. The current nadir + 2 (CN + 2) definition of biochemical failure was used. Patients with rising prostate-specific antigen (PSA) or suspicious digital rectal examination before the biopsy were excluded. Results: The biopsy results were normal in 78 patients, scant atypical and malignant cells in 30, carcinoma with treatment effect in 43, and carcinoma without treatment effect in 13. Using the CN + 2 definition, we found a significant association between biopsy results and eventual biochemical failure. We also found that the biopsy status provides predictive information independent of the PSA status at the time of biopsy. Conclusion: A 2-year post-RT prostate biopsy may be useful for forecasting CN + 2 biochemical failure. Posttreatment prostate biopsy may be useful for identifying patients for aggressive salvage therapy
Predicted vitamin D status and colon cancer recurrence and mortality in CALGB 89803 (Alliance).

Science.gov (United States)

Fuchs, M A; Yuan, C; Sato, K; Niedzwiecki, D; Ye, X; Saltz, L B; Mayer, R J; Mowat, R B; Whittom, R; Hantel, A; Benson, A; Atienza, D; Messino, M; Kindler, H; Venook, A; Innocenti, F; Warren, R S; Bertagnolli, M M; Ogino, S; Giovannucci, E L; Horvath, E; Meyerhardt, J A; Ng, K

2017-06-01

Observational studies suggest that higher levels of 25-hydroxyvitamin D3 (25(OH)D) are associated with a reduced risk of colorectal cancer and improved survival of colorectal cancer patients. However, the influence of vitamin D status on cancer recurrence and survival of patients with stage III colon cancer is unknown. We prospectively examined the influence of post-diagnosis predicted plasma 25(OH)D on outcome among 1016 patients with stage III colon cancer who were enrolled in a National Cancer Institute-sponsored adjuvant therapy trial (CALGB 89803). Predicted 25(OH)D scores were computed using validated regression models. We examined the influence of predicted 25(OH)D scores on cancer recurrence and mortality (disease-free survival; DFS) using Cox proportional hazards. Patients in the highest quintile of predicted 25(OH)D score had an adjusted hazard ratio (HR) for colon cancer recurrence or mortality (DFS) of 0.62 (95% confidence interval [CI], 0.44-0.86), compared with those in the lowest quintile (Ptrend = 0.005). Higher predicted 25(OH)D score was also associated with a significant improvement in recurrence-free survival and overall survival (Ptrend = 0.01 and 0.0004, respectively). The benefit associated with higher predicted 25(OH)D score appeared consistent across predictors of cancer outcome and strata of molecular tumor characteristics, including microsatellite instability and KRAS, BRAF, PIK3CA, and TP53 mutation status. Higher predicted 25(OH)D levels after a diagnosis of stage III colon cancer may be associated with decreased recurrence and improved survival. Clinical trials assessing the benefit of vitamin D supplementation in the adjuvant setting are warranted. NCT00003835. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Predictive and therapeutic markers in ovarian cancer

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Gray, Joe W.; Guan, Yinghui; Kuo, Wen-Lin; Fridlyand, Jane; Mills, Gordon B.

2013-03-26

Cancer markers may be developed to detect diseases characterized by increased expression of apoptosis-suppressing genes, such as aggressive cancers. Genes in the human chromosomal regions, 8q24, 11q13, 20q11-q13, were found to be amplified indicating in vivo drug resistance in diseases such as ovarian cancer. Diagnosis and assessment of amplification levels certain genes shown to be amplified, including PVT1, can be useful in prediction of poor outcome of patient's response and drug resistance in ovarian cancer patients with low survival rates. Certain genes were found to be high priority therapeutic targets by the identification of recurrent aberrations involving genome sequence, copy number and/or gene expression are associated with reduced survival duration in certain diseases and cancers, specifically ovarian cancer. Therapeutics to inhibit amplification and inhibitors of one of these genes, PVT1, target drug resistance in ovarian cancer patients with low survival rates is described.
Caveolin-1 expression level in cancer associated fibroblasts predicts outcome in gastric cancer.

Directory of Open Access Journals (Sweden)

Xianda Zhao

Full Text Available AIMS: Altered expression of epithelial or stromal caveolin-1 (Cav-1 is observed in various types of human cancers. However, the clinical significance of Cav-1 expression in gastric cancer (GC remains largely unknown. The present study aims to explore the clinicopathological significance and prognostic value of both tumor cells and cancer associated fibroblasts (CAFs Cav-1 in GC. METHODS AND RESULTS: Quantum dots immunofluorescence histochemistry was performed to examine the expression of Cav-1 in 20 cases of gastritis without intestinal metaplasia (IM, 20 cases of gastritis with IM and 286 cases of GC. Positive rates of epithelial Cav-1 in gastritis without IM, gastritis with IM and GC showed a decreasing trend (P = 0.012. Low expression of Cav-1 in CAFs but not in tumor cells was an independent predictor of poor prognosis in GC patients (P = 0.034 and 0.005 respectively in disease free survival and overall survival. Cav-1 level in tumor cells and CAFs showed no significant correlation with classic clinicopathological features. CONCLUSIONS: Loss of epithelial Cav-1 may promote malignant progression and low CAFs Cav-1 level herald worse outcome of GC patient, suggesting CAFs Cav-1 may be a candidate therapeutic target and a useful prognostic marker of GC.
A utility/cost analysis of breast cancer risk prediction algorithms

Science.gov (United States)

Abbey, Craig K.; Wu, Yirong; Burnside, Elizabeth S.; Wunderlich, Adam; Samuelson, Frank W.; Boone, John M.

2016-03-01

Breast cancer risk prediction algorithms are used to identify subpopulations that are at increased risk for developing breast cancer. They can be based on many different sources of data such as demographics, relatives with cancer, gene expression, and various phenotypic features such as breast density. Women who are identified as high risk may undergo a more extensive (and expensive) screening process that includes MRI or ultrasound imaging in addition to the standard full-field digital mammography (FFDM) exam. Given that there are many ways that risk prediction may be accomplished, it is of interest to evaluate them in terms of expected cost, which includes the costs of diagnostic outcomes. In this work we perform an expected-cost analysis of risk prediction algorithms that is based on a published model that includes the costs associated with diagnostic outcomes (true-positive, false-positive, etc.). We assume the existence of a standard screening method and an enhanced screening method with higher scan cost, higher sensitivity, and lower specificity. We then assess expected cost of using a risk prediction algorithm to determine who gets the enhanced screening method under the strong assumption that risk and diagnostic performance are independent. We find that if risk prediction leads to a high enough positive predictive value, it will be cost-effective regardless of the size of the subpopulation. Furthermore, in terms of the hit-rate and false-alarm rate of the of the risk prediction algorithm, iso-cost contours are lines with slope determined by properties of the available diagnostic systems for screening.
Cytoplasmic Drosha Is Aberrant in Precancerous Lesions of Gastric Carcinoma and Its Loss Predicts Worse Outcome for Gastric Cancer Patients.

Science.gov (United States)

Zhang, Hailong; Hou, Yixuan; Xu, Liyun; Zeng, Zongyue; Wen, Siyang; Du, Yan-E; Sun, Kexin; Yin, Jiali; Lang, Lei; Tang, Xiaoli; Liu, Manran

2016-04-01

The nuclear localization of Drosha is critical for its function as a microRNA maturation regulator. Dephosphorylation of Drosha at serine 300 and serine 302 disrupts its nuclear localization, and aberrant distribution of Drosha has been detected in some tumors. The purpose of the present study was to assess cytoplasmic/nuclear Drosha expression in gastric cancer carcinogenesis and progression. Drosha expression and its subcellular location was investigated by immunohistochemical staining of a set of tissue microarrays composed of normal adjacent tissues (374), chronic gastritis (137), precancerous lesions (94), and gastric adenocarcinoma (829) samples, and in gastric cancer cell lines with varying differentiation by immunofluorescence and western blot assay. Gradual loss of cytoplasmic Drosha was accompanied by tumor progression in both gastric cancer tissues and cell lines, and was inversely associated with tumor volume (P = 0.002), tumor grade (P gastric cancer. High levels of cytoplasmic Drosha predicted longer survival (LR = 7.088, P = 0.008) in gastric cancer patients. Our data provide novel insights into gastric cancer that cytoplasmic Drosha potentially plays a role in preventing carcinogenesis and tumor progression, and may be an independent predictor of patient outcome.
Pretreatment tables predicting pathologic stage of locally advanced prostate cancer.

Science.gov (United States)

Joniau, Steven; Spahn, Martin; Briganti, Alberto; Gandaglia, Giorgio; Tombal, Bertrand; Tosco, Lorenzo; Marchioro, Giansilvio; Hsu, Chao-Yu; Walz, Jochen; Kneitz, Burkhard; Bader, Pia; Frohneberg, Detlef; Tizzani, Alessandro; Graefen, Markus; van Cangh, Paul; Karnes, R Jeffrey; Montorsi, Francesco; van Poppel, Hein; Gontero, Paolo

2015-02-01

Pretreatment tables for the prediction of pathologic stage have been published and validated for localized prostate cancer (PCa). No such tables are available for locally advanced (cT3a) PCa. To construct tables predicting pathologic outcome after radical prostatectomy (RP) for patients with cT3a PCa with the aim to help guide treatment decisions in clinical practice. This was a multicenter retrospective cohort study including 759 consecutive patients with cT3a PCa treated with RP between 1987 and 2010. Retropubic RP and pelvic lymphadenectomy. Patients were divided into pretreatment prostate-specific antigen (PSA) and biopsy Gleason score (GS) subgroups. These parameters were used to construct tables predicting pathologic outcome and the presence of positive lymph nodes (LNs) after RP for cT3a PCa using ordinal logistic regression. In the model predicting pathologic outcome, the main effects of biopsy GS and pretreatment PSA were significant. A higher GS and/or higher PSA level was associated with a more unfavorable pathologic outcome. The validation procedure, using a repeated split-sample method, showed good predictive ability. Regression analysis also showed an increasing probability of positive LNs with increasing PSA levels and/or higher GS. Limitations of the study are the retrospective design and the long study period. These novel tables predict pathologic stage after RP for patients with cT3a PCa based on pretreatment PSA level and biopsy GS. They can be used to guide decision making in men with locally advanced PCa. Our study might provide physicians with a useful tool to predict pathologic stage in locally advanced prostate cancer that might help select patients who may need multimodal treatment. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.
An etiologic prediction model incorporating biomarkers to predict the bladder cancer risk associated with occupational exposure to aromatic amines: a pilot study.

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Mastrangelo, Giuseppe; Carta, Angela; Arici, Cecilia; Pavanello, Sofia; Porru, Stefano

2017-01-01

No etiological prediction model incorporating biomarkers is available to predict bladder cancer risk associated with occupational exposure to aromatic amines. Cases were 199 bladder cancer patients. Clinical, laboratory and genetic data were predictors in logistic regression models (full and short) in which the dependent variable was 1 for 15 patients with aromatic amines related bladder cancer and 0 otherwise. The receiver operating characteristics approach was adopted; the area under the curve was used to evaluate discriminatory ability of models. Area under the curve was 0.93 for the full model (including age, smoking and coffee habits, DNA adducts, 12 genotypes) and 0.86 for the short model (including smoking, DNA adducts, 3 genotypes). Using the "best cut-off" of predicted probability of a positive outcome, percentage of cases correctly classified was 92% (full model) against 75% (short model). Cancers classified as "positive outcome" are those to be referred for evaluation by an occupational physician for etiological diagnosis; these patients were 28 (full model) or 60 (short model). Using 3 genotypes instead of 12 can double the number of patients with suspect of aromatic amine related cancer, thus increasing costs of etiologic appraisal. Integrating clinical, laboratory and genetic factors, we developed the first etiologic prediction model for aromatic amine related bladder cancer. Discriminatory ability was excellent, particularly for the full model, allowing individualized predictions. Validation of our model in external populations is essential for practical use in the clinical setting.
De novo sequencing of circulating miRNAs identifies novel markers predicting clinical outcome of locally advanced breast cancer

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Wu Xiwei

2012-03-01

Full Text Available Abstract Background MicroRNAs (miRNAs have been recently detected in the circulation of cancer patients, where they are associated with clinical parameters. Discovery profiling of circulating small RNAs has not been reported in breast cancer (BC, and was carried out in this study to identify blood-based small RNA markers of BC clinical outcome. Methods The pre-treatment sera of 42 stage II-III locally advanced and inflammatory BC patients who received neoadjuvant chemotherapy (NCT followed by surgical tumor resection were analyzed for marker identification by deep sequencing all circulating small RNAs. An independent validation cohort of 26 stage II-III BC patients was used to assess the power of identified miRNA markers. Results More than 800 miRNA species were detected in the circulation, and observed patterns showed association with histopathological profiles of BC. Groups of circulating miRNAs differentially associated with ER/PR/HER2 status and inflammatory BC were identified. The relative levels of selected miRNAs measured by PCR showed consistency with their abundance determined by deep sequencing. Two circulating miRNAs, miR-375 and miR-122, exhibited strong correlations with clinical outcomes, including NCT response and relapse with metastatic disease. In the validation cohort, higher levels of circulating miR-122 specifically predicted metastatic recurrence in stage II-III BC patients. Conclusions Our study indicates that certain miRNAs can serve as potential blood-based biomarkers for NCT response, and that miR-122 prevalence in the circulation predicts BC metastasis in early-stage patients. These results may allow optimized chemotherapy treatments and preventive anti-metastasis interventions in future clinical applications.
Predicting Scheduling and Attending for an Oral Cancer Examination

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Shepperd, James A.; Emanuel, Amber S.; Howell, Jennifer L.; Logan, Henrietta L.

2015-01-01

Background Oral and pharyngeal cancer is highly treatable if diagnosed early, yet late diagnosis is commonplace apparently because of delays in undergoing an oral cancer examination. Purpose We explored predictors of scheduling and attending an oral cancer examination among a sample of Black and White men who were at high risk for oral cancer because they smoked. Methods During an in-person interview, participants (N = 315) from rural Florida learned about oral and pharyngeal cancer, completed survey measures, and were offered a free examination in the next week. Later, participants received a follow-up phone call to explore why they did or did not attend their examination. Results Consistent with the notion that scheduling and attending an oral cancer exam represent distinct decisions, we found that the two outcomes had different predictors. Defensive avoidance and exam efficacy predicted scheduling an examination; exam efficacy and having coping resources, time, and transportation predicted attending the examination. Open-ended responses revealed that the dominant reasons participants offered for missing a scheduled examination was conflicting obligations, forgetting, and confusion or misunderstanding about the examination. Conclusions The results suggest interventions to increase scheduling and attending an oral cancer examination. PMID:26152644
Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

Science.gov (United States)

Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

2014-09-09

Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.
Rectal cancer surgery: volume-outcome analysis.

LENUS (Irish Health Repository)

Nugent, Emmeline

2010-12-01

There is strong evidence supporting the importance of the volume-outcome relationship with respect to lung and pancreatic cancers. This relationship for rectal cancer surgery however remains unclear. We review the currently available literature to assess the evidence base for volume outcome in relation to rectal cancer surgery.
Nomograms for Prediction of Outcome With or Without Adjuvant Radiation Therapy for Patients With Endometrial Cancer: A Pooled Analysis of PORTEC-1 and PORTEC-2 Trials

Energy Technology Data Exchange (ETDEWEB)

Creutzberg, Carien L., E-mail: c.l.creutzberg@lumc.nl [Department of Clinical Oncology, Leiden University Medical Center, Leiden (Netherlands); Stiphout, Ruud G.P.M. van [Department of Radiation Oncology, MAASTRO, GROW, University Medical Centre Maastricht, Maastricht (Netherlands); Nout, Remi A. [Department of Clinical Oncology, Leiden University Medical Center, Leiden (Netherlands); Lutgens, Ludy C.H.W. [Department of Radiation Oncology, MAASTRO, GROW, University Medical Centre Maastricht, Maastricht (Netherlands); Jürgenliemk-Schulz, Ina M. [Department of Radiation Oncology, University Medical Center Utrecht, Utrecht (Netherlands); Jobsen, Jan J. [Department of Radiotherapy, Medisch Spectrum Twente, Enschede (Netherlands); Smit, Vincent T.H.B.M. [Department of Pathology, Leiden University Medical Center, Leiden (Netherlands); Lambin, Philippe [Department of Radiation Oncology, MAASTRO, GROW, University Medical Centre Maastricht, Maastricht (Netherlands)

2015-03-01

Background: Postoperative radiation therapy for stage I endometrial cancer improves locoregional control but is without survival benefit. To facilitate treatment decision support for individual patients, accurate statistical models to predict locoregional relapse (LRR), distant relapse (DR), overall survival (OS), and disease-free survival (DFS) are required. Methods and Materials: Clinical trial data from the randomized Post Operative Radiation Therapy for Endometrial Cancer (PORTEC-1; N=714 patients) and PORTEC-2 (N=427 patients) trials and registered group (grade 3 and deep invasion, n=99) were pooled for analysis (N=1240). For most patients (86%) pathology review data were available; otherwise original pathology data were used. Trial variables which were clinically relevant and eligible according to data constraints were age, stage, given treatment (pelvic external beam radiation therapy (EBRT), vaginal brachytherapy (VBT), or no adjuvant treatment, FIGO histological grade, depth of invasion, and lymph-vascular invasion (LVSI). Multivariate analyses were based on Cox proportional hazards regression model. Predictors were selected based on a backward elimination scheme. Model results were expressed by the c-index (0.5-1.0; random to perfect prediction). Two validation sets (n=244 and 291 patients) were used. Results: Accuracy of the developed models was good, with training accuracies between 0.71 and 0.78. The nomograms validated well for DR (0.73), DFS (0.69), and OS (0.70), but validation was only fair for LRR (0.59). Ranking of variables as to their predictive power showed that age, tumor grade, and LVSI were highly predictive for all outcomes, and given treatment for LRR and DFS. The nomograms were able to significantly distinguish low- from high-probability patients for these outcomes. Conclusions: The nomograms are internally validated and able to accurately predict long-term outcome for endometrial cancer patients with observation, pelvic EBRT, or VBT
lncRNA Gene Signatures for Prediction of Breast Cancer Intrinsic Subtypes and Prognosis

Directory of Open Access Journals (Sweden)

Silu Zhang

2018-01-01

Full Text Available Background: Breast cancer is intrinsically heterogeneous and is commonly classified into four main subtypes associated with distinct biological features and clinical outcomes. However, currently available data resources and methods are limited in identifying molecular subtyping on protein-coding genes, and little is known about the roles of long non-coding RNAs (lncRNAs, which occupies 98% of the whole genome. lncRNAs may also play important roles in subgrouping cancer patients and are associated with clinical phenotypes. Methods: The purpose of this project was to identify lncRNA gene signatures that are associated with breast cancer subtypes and clinical outcomes. We identified lncRNA gene signatures from The Cancer Genome Atlas (TCGA RNAseq data that are associated with breast cancer subtypes by an optimized 1-Norm SVM feature selection algorithm. We evaluated the prognostic performance of these gene signatures with a semi-supervised principal component (superPC method. Results: Although lncRNAs can independently predict breast cancer subtypes with satisfactory accuracy, a combined gene signature including both coding and non-coding genes will give the best clinically relevant prediction performance. We highlighted eight potential biomarkers (three from coding genes and five from non-coding genes that are significantly associated with survival outcomes. Conclusion: Our proposed methods are a novel means of identifying subtype-specific coding and non-coding potential biomarkers that are both clinically relevant and biologically significant.
Note of the methodological flaws in the paper entitled "GSTT1 and GSTM1 polymorphisms predict treatment outcome for breast cancer: a systematic review and meta-analysis".

Science.gov (United States)

Qiu, Mali; Wu, Xu; Qu, Xiaobing

2016-09-01

With great interest, we read the paper "GSTT1 and GSTM1 polymorphisms predict treatment outcome for breast cancer: a systematic review and meta-analysis" (by Hu XY et al.), which has reached important conclusions that GSTM1 null and GSTT1/GSTM1 double null polymorphisms might be significantly associated with an increased tumor response in breast cancer. The result is encouraging. Nevertheless, several methodological flaws in this meta-analysis are worth noticing.
Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer

International Nuclear Information System (INIS)

Karlsson, Elin; Delle, Ulla; Danielsson, Anna; Olsson, Björn; Abel, Frida; Karlsson, Per; Helou, Khalil

2008-01-01

It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved. The research on these tumours was approved by the Medical Faculty Research
Machine learning applications in cancer prognosis and prediction.

Science.gov (United States)

Kourou, Konstantina; Exarchos, Themis P; Exarchos, Konstantinos P; Karamouzis, Michalis V; Fotiadis, Dimitrios I

2015-01-01

Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in cancer research, as it can facilitate the subsequent clinical management of patients. The importance of classifying cancer patients into high or low risk groups has led many research teams, from the biomedical and the bioinformatics field, to study the application of machine learning (ML) methods. Therefore, these techniques have been utilized as an aim to model the progression and treatment of cancerous conditions. In addition, the ability of ML tools to detect key features from complex datasets reveals their importance. A variety of these techniques, including Artificial Neural Networks (ANNs), Bayesian Networks (BNs), Support Vector Machines (SVMs) and Decision Trees (DTs) have been widely applied in cancer research for the development of predictive models, resulting in effective and accurate decision making. Even though it is evident that the use of ML methods can improve our understanding of cancer progression, an appropriate level of validation is needed in order for these methods to be considered in the everyday clinical practice. In this work, we present a review of recent ML approaches employed in the modeling of cancer progression. The predictive models discussed here are based on various supervised ML techniques as well as on different input features and data samples. Given the growing trend on the application of ML methods in cancer research, we present here the most recent publications that employ these techniques as an aim to model cancer risk or patient outcomes.

Hashimoto's thyroiditis predicts outcome in intrathyroidal papillary thyroid cancer.

Science.gov (United States)

Marotta, Vincenzo; Sciammarella, Concetta; Chiofalo, Maria Grazia; Gambardella, Claudio; Bellevicine, Claudio; Grasso, Marica; Conzo, Giovanni; Docimo, Giovanni; Botti, Gerardo; Losito, Simona; Troncone, Giancarlo; De Palma, Maurizio; Giacomelli, Laura; Pezzullo, Luciano; Colao, Annamaria; Faggiano, Antongiulio

2017-09-01

Hashimoto's thyroiditis (HT) seems to have favourable prognostic impact on papillary thyroid cancer (PTC), but data were obtained analysing all disease stages. Given that HT-related microenvironment involves solely the thyroid, we aimed to assess the relationship between HT, as detected through pathological assessment, and outcome in intrathyroidal PTC. This was a multicentre, retrospective, observational study including 301 PTC with no evidence of extrathyroidal disease. Primary study endpoint was the rate of clinical remission. Auxiliary endpoint was recurrence-free survival (RFS). HT was detected in 42.5% of the cohort and was associated to female gender, smaller tumour size, lower rate of aggressive PTC variants and less frequent post-surgery radio-iodine administration. HT showed relationship with significantly higher rate of clinical remission ( P < 0.001, OR 4, 95% CI 1.78-8.94). PTCs with concomitant HT had significantly longer RFS, as compared with non-HT tumours ( P = 0.004). After adjustment for other parameters affecting disease outcome at univariate analysis (age at diagnosis, histology, tumour size and multifocality), prognostic effect of HT remained significant ( P = 0.006, OR 3.28, 95% CI 1.39-7.72). To verify whether HT could optimise the identification of PTCs with unfavourable outcome, we assessed the accuracy of 'non-HT status' as negative prognostic marker, demonstrating poor capability of identifying patients not maintaining clinical remission until final follow-up (probability of no clinical remission in PTCs without HT: 21.05%, 95% CI 15.20-27.93). In conclusion, our data show that HT represents an independent prognostic parameter in intrathyroidal PTC, but cannot improve prognostic specificity. © 2017 Society for Endocrinology.
Oral symptoms and functional outcome related to oral and oropharyngeal cancer.

Science.gov (United States)

Kamstra, Jolanda I; Jager-Wittenaar, Harriet; Dijkstra, Pieter U; Huisman, Paulien M; van Oort, Rob P; van der Laan, Bernard F A M; Roodenburg, Jan L N

2011-09-01

This study aimed to assess: (1) oral symptoms of patients treated for oral or oropharyngeal cancer; (2) how patients rank the burden of oral symptoms; (3) the impact of the tumor, the treatment, and oral symptoms on functional outcome. Eighty-nine patients treated for oral or oropharyngeal cancer were asked about their oral symptoms related to mouth opening, dental status, oral sensory function, tongue mobility, salivary function, and pain. They were asked to rank these oral symptoms according to the degree of burden experienced. The Mandibular Function Impairment Questionnaire (MFIQ) was used to assess functional outcome. In a multivariate linear regression analyses, variables related to MFIQ scores (p≤0.10) were entered as predictors with MFIQ score as the outcome. Lack of saliva (52%), restricted mouth opening (48%), and restricted tongue mobility (46%) were the most frequently reported oral symptoms. Lack of saliva was most frequently (32%) ranked as the most burdensome oral symptom. For radiated patients, an inability to wear a dental prosthesis, a T3 or T4 stage, and a higher age were predictive of MFIQ scores. For non-radiated patients, a restricted mouth opening, an inability to wear a dental prosthesis, restricted tongue mobility, and surgery of the mandible were predictive of MFIQ scores. Lack of saliva was not only the most frequently reported oral symptom after treatment for oral or oropharyngeal cancer, but also the most burdensome. Functional outcome is strongly influenced by an inability to wear a dental prosthesis in both radiated and non-radiated patients.
Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study

OpenAIRE

Chu Annie TW; Bonanno George A; Ho Judy WC; Ho Samuel MY; Chan Emily MS

2010-01-01

Abstract Background - Genetic testing for hereditary colorectal cancer (HCRC) had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. Methods - A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer R...
Validation of the 2015 prostate cancer grade groups for predicting long-term oncologic outcomes in a shared equal-access health system.

Science.gov (United States)

Schulman, Ariel A; Howard, Lauren E; Tay, Kae Jack; Tsivian, Efrat; Sze, Christina; Amling, Christopher L; Aronson, William J; Cooperberg, Matthew R; Kane, Christopher J; Terris, Martha K; Freedland, Stephen J; Polascik, Thomas J

2017-11-01

A 5-tier prognostic grade group (GG) system was enacted to simplify the risk stratification of patients with prostate cancer in which Gleason scores of ≤6, 3 + 4, 4 + 3, 8, and 9 or 10 are considered GG 1 through 5, respectively. The authors investigated the utility of biopsy GG for predicting long-term oncologic outcomes after radical prostatectomy in an equal-access health system. Men who underwent prostatectomy at 1 of 6 Veterans Affairs hospitals in the Shared Equal Access Regional Cancer Hospital database between 2005 and 2015 were reviewed. The prognostic ability of biopsy GG was examined using Cox models. Interactions between GG and race also were tested. In total, 2509 men were identified who had data available on biopsy Gleason scores, covariates, and follow-up. The cohort included men with GG 1 (909 patients; 36.2%), GG 2 (813 patients; 32.4%), GG 3 (398 patients; 15.9%), GG 4 (279 patients; 11.1%), and GG 5 (110 patients; 4.4%) prostate cancer. The cohort included 1002 African American men (41%). The median follow-up was 60 months (interquartile range, 33-90 months). Higher GG was associated with higher clinical stage, older age, more recent surgery, and surgical center (P prostate cancer, metastases, and prostate cancer-specific mortality (all P Cancer 2017;123:4122-4129. © 2017 American Cancer Society. © 2017 American Cancer Society.
Gene expression signatures predict outcome in non-muscle invasive bladder carcinoma - a multi-center validation study

DEFF Research Database (Denmark)

Andersen, Lars Dyrskjøt; Zieger, Karsten; Real, Francisco X.

2007-01-01

and carcinoma in situ (CIS) and for predicting disease recurrence and progression. EXPERIMENTAL DESIGN: We analyzed tumors from 404 patients diagnosed with bladder cancer in hospitals in Denmark, Sweden, England, Spain, and France using custom microarrays. Molecular classifications were compared with pathologic....... CONCLUSION: This multicenter validation study confirms in an independent series the clinical utility of molecular classifiers to predict the outcome of patients initially diagnosed with non-muscle-invasive bladder cancer. This information may be useful to better guide patient treatment....
Predicting outcome of status epilepticus.

Science.gov (United States)

Leitinger, M; Kalss, G; Rohracher, A; Pilz, G; Novak, H; Höfler, J; Deak, I; Kuchukhidze, G; Dobesberger, J; Wakonig, A; Trinka, E

2015-08-01

Status epilepticus (SE) is a frequent neurological emergency complicated by high mortality and often poor functional outcome in survivors. The aim of this study was to review available clinical scores to predict outcome. Literature review. PubMed Search terms were "score", "outcome", and "status epilepticus" (April 9th 2015). Publications with abstracts available in English, no other language restrictions, or any restrictions concerning investigated patients were included. Two scores were identified: "Status Epilepticus Severity Score--STESS" and "Epidemiology based Mortality score in SE--EMSE". A comprehensive comparison of test parameters concerning performance, options, and limitations was performed. Epidemiology based Mortality score in SE allows detailed individualization of risk factors and is significantly superior to STESS in a retrospective explorative study. In particular, EMSE is very good at detection of good and bad outcome, whereas STESS detecting bad outcome is limited by a ceiling effect and uncertainty of correct cutoff value. Epidemiology based Mortality score in SE can be adapted to different regions in the world and to advances in medicine, as new data emerge. In addition, we designed a reporting standard for status epilepticus to enhance acquisition and communication of outcome relevant data. A data acquisition sheet used from patient admission in emergency room, from the EEG lab to intensive care unit, is provided for optimized data collection. Status Epilepticus Severity Score is easy to perform and predicts bad outcome, but has a low predictive value for good outcomes. Epidemiology based Mortality score in SE is superior to STESS in predicting good or bad outcome but needs marginally more time to perform. Epidemiology based Mortality score in SE may prove very useful for risk stratification in interventional studies and is recommended for individual outcome prediction. Prospective validation in different cohorts is needed for EMSE, whereas
A comparison of machine learning techniques for survival prediction in breast cancer.

Science.gov (United States)

Vanneschi, Leonardo; Farinaccio, Antonella; Mauri, Giancarlo; Antoniotti, Mauro; Provero, Paolo; Giacobini, Mario

2011-05-11

The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data.
A comparison of machine learning techniques for survival prediction in breast cancer

Directory of Open Access Journals (Sweden)

Vanneschi Leonardo

2011-05-01

Full Text Available Abstract Background The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. Results We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Conclusions Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data.
Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

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Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

2016-02-01

The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.
Machine learning models in breast cancer survival prediction.

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Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

2016-01-01

Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of
Diffusion-weighted MRI characteristics of the cerebral metastasis to brain boundary predicts patient outcomes

International Nuclear Information System (INIS)

Zakaria, Rasheed; Das, Kumar; Radon, Mark; Bhojak, Maneesh; Rudland, Philip R; Sluming, Vanessa; Jenkinson, Michael D

2014-01-01

Diffusion-weighted MRI (DWI) has been used in neurosurgical practice mainly to distinguish cerebral metastases from abscess and glioma. There is evidence from other solid organ cancers and metastases that DWI may be used as a biomarker of prognosis and treatment response. We therefore investigated DWI characteristics of cerebral metastases and their peritumoral region recorded pre-operatively and related these to patient outcomes. Retrospective analysis of 76 cases operated upon at a single institution with DWI performed pre-operatively at 1.5T. Maps of apparent diffusion coefficient (ADC) were generated using standard protocols. Readings were taken from the tumor, peritumoral region and across the brain-tumor interface. Patient outcomes were overall survival and time to local recurrence. A minimum ADC greater than 919.4 × 10 -6 mm 2 /s within a metastasis predicted longer overall survival regardless of adjuvant therapies. This was not simply due to differences between the types of primary cancer because the effect was observed even in a subgroup of 36 patients with the same primary, non-small cell lung cancer. The change in diffusion across the tumor border and into peritumoral brain was measured by the “ADC transition coefficient” or ATC and this was more strongly predictive than ADC readings alone. Metastases with a sharp change in diffusion across their border (ATC >0.279) showed shorter overall survival compared to those with a more diffuse edge. The ATC was the only imaging measurement which independently predicted overall survival in multivariate analysis (hazard ratio 0.54, 95% CI 0.3 – 0.97, p = 0.04). DWI demonstrates changes in the tumor, across the tumor edge and in the peritumoral region which may not be visible on conventional MRI and this may be useful in predicting patient outcomes for operated cerebral metastases
Colon cancer with unresectable synchronous metastases: the AAAP scoring system for predicting the outcome after primary tumour resection.

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Li, Z M; Peng, Y F; Du, C Z; Gu, J

2016-03-01

The aim of this study was to develop a prognostic scoring system to predict the outcome of patients with unresectable metastatic colon cancer who received primary colon tumour resection. Patients with confirmed metastatic colon cancer treated at the Peking University Cancer Hospital between 2003 and 2012 were reviewed retrospectively. The correlation of clinicopathological factors with overall survival was analysed using the Kaplan-Meier method and the log-rank test. Independent prognostic factors were identified using a Cox proportional hazards regression model and were then combined to form a prognostic scoring system. A total of 110 eligible patients were included in the study. The median survival time was 10.4 months and the 2-year overall survival (OS) rate was 21.8%. Age over 70 years, an alkaline phosphatase (ALP) level over 160 IU/l, ascites, a platelet/lymphocyte ratio (PLR) above 162 and no postoperative therapy were independently associated with a shorter OS in multivariate analysis. Age, ALP, ascites and PLR were subsequently combined to form the so-called AAAP scoring system. Patients were classified into high, medium and low risk groups according to the score obtained. There were significant differences in OS between each group (P colonic cancer who underwent primary tumour resection. The AAAP scoring system may be a useful tool for surgical decision making. Colorectal Disease © 2015 The Association of Coloproctology of Great Britain and Ireland.
Progastrin: a potential predictive marker of liver metastasis in colorectal cancer.

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Westwood, David A; Patel, Oneel; Christophi, Christopher; Shulkes, Arthur; Baldwin, Graham S

2017-07-01

Staging of colorectal cancer often fails to discriminate outcomes of patients with morphologically similar tumours that exhibit different clinical behaviours. Data from several studies suggest that the gastrin family of growth factors potentiates colorectal cancer tumourigenesis. The aim of this study was to investigate whether progastrin expression may predict clinical outcome in colorectal cancer. Patients with colorectal adenocarcinoma of identical depth of invasion who had not received neoadjuvant therapy were included. The patients either had stage IIa disease with greater than 3-year disease-free survival without adjuvant therapy or stage IV disease with liver metastases on staging CT. Progastrin expression in tumour sections was scored with reference to the intensity and area of immunohistochemical staining. Progastrin expression by stage IV tumours was significantly greater than stage IIa tumours with mean progastrin immunopositivity scores of 2.1 ± 0.2 versus 0.5 ± 0.2, respectively (P colorectal cancer and supports its clinical relevance and potential use as a biomarker.
Outcomes in Lung Cancer: 9-Year Experience From a Tertiary Cancer Center in India

OpenAIRE

Aditya Navile Murali; Venkatraman Radhakrishnan; Trivadi S. Ganesan; Rejiv Rajendranath; Prasanth Ganesan; Ganesarajah Selvaluxmy; Rajaraman Swaminathan; Shirley Sundersingh; Arvind Krishnamurthy; Tenali Gnana Sagar

2017-01-01

Purpose: Lung cancer is the most common cause of cancer mortality in the world. There are limited studies on survival outcomes of lung cancer in developing countries such as India. This study analyzed the outcomes of patients with lung cancer who underwent treatment at Cancer Institute (WIA), Chennai, India, between 2006 and 2015 to determine survival outcomes and identify prognostic factors. Patients and Methods: In all, 678 patients with lung cancer underwent treatment. Median age was 58 ye...
Predictive modeling of outcomes following definitive chemoradiotherapy for oropharyngeal cancer based on FDG-PET image characteristics

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Folkert, Michael R.; Setton, Jeremy; Apte, Aditya P.; Grkovski, Milan; Young, Robert J.; Schöder, Heiko; Thorstad, Wade L.; Lee, Nancy Y.; Deasy, Joseph O.; Oh, Jung Hun

2017-07-01

In this study, we investigate the use of imaging feature-based outcomes research (‘radiomics’) combined with machine learning techniques to develop robust predictive models for the risk of all-cause mortality (ACM), local failure (LF), and distant metastasis (DM) following definitive chemoradiation therapy (CRT). One hundred seventy four patients with stage III-IV oropharyngeal cancer (OC) treated at our institution with CRT with retrievable pre- and post-treatment 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) scans were identified. From pre-treatment PET scans, 24 representative imaging features of FDG-avid disease regions were extracted. Using machine learning-based feature selection methods, multiparameter logistic regression models were built incorporating clinical factors and imaging features. All model building methods were tested by cross validation to avoid overfitting, and final outcome models were validated on an independent dataset from a collaborating institution. Multiparameter models were statistically significant on 5 fold cross validation with the area under the receiver operating characteristic curve (AUC) = 0.65 (p = 0.004), 0.73 (p = 0.026), and 0.66 (p = 0.015) for ACM, LF, and DM, respectively. The model for LF retained significance on the independent validation cohort with AUC = 0.68 (p = 0.029) whereas the models for ACM and DM did not reach statistical significance, but resulted in comparable predictive power to the 5 fold cross validation with AUC = 0.60 (p = 0.092) and 0.65 (p = 0.062), respectively. In the largest study of its kind to date, predictive features including increasing metabolic tumor volume, increasing image heterogeneity, and increasing tumor surface irregularity significantly correlated to mortality, LF, and DM on 5 fold cross validation in a relatively uniform single-institution cohort. The LF model also retained
Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

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Enshaei, A; Robson, C N; Edmondson, R J

2015-11-01

The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, conventional algorithms become too complex for routine clinical use. This study therefore investigated the potential for an artificial intelligence model to provide this information and compared it with conventional statistical approaches. The authors created a database comprising 668 cases of epithelial ovarian cancer during a 10-year period and collected data routinely available in a clinical environment. They also collected survival data for all the patients, then constructed an artificial intelligence model capable of comparing a variety of algorithms and classifiers alongside conventional statistical approaches such as logistic regression. The model was used to predict overall survival and demonstrated that an artificial neural network (ANN) algorithm was capable of predicting survival with high accuracy (93 %) and an area under the curve (AUC) of 0.74 and that this outperformed logistic regression. The model also was used to predict the outcome of surgery and again showed that ANN could predict outcome (complete/optimal cytoreduction vs. suboptimal cytoreduction) with 77 % accuracy and an AUC of 0.73. These data are encouraging and demonstrate that artificial intelligence systems may have a role in providing prognostic and predictive data for patients. The performance of these systems likely will improve with increasing data set size, and this needs further investigation.
The prognostic value of stromal FK506-binding protein 1 and androgen receptor in prostate cancer outcome.

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Leach, Damien A; Trotta, Andrew P; Need, Eleanor F; Risbridger, Gail P; Taylor, Renea A; Buchanan, Grant

2017-02-01

Improving our ability to predict cancer progression and response to conservative or radical intent therapy is critical if we are to prevent under or over treatment of individual patients. Whereas the majority of solid tumors now have a range of molecular and/or immunological markers to help define prognosis and treatment options, prostate cancer still relies mainly on histological grading and clinical parameters. We have recently reported that androgen receptor (AR) expression in stroma inversely associates with prostate cancer-specific survival, and that stromal AR reduces metastasis. For this paper, we tested the hypothesis that the AR-regulated gene FKBP51 could be used as a marker of AR activity to better predict outcome. Using immunohistochemistry on a cohort of 64 patient-matched benign and malignant prostate tissues, we assessed patient outcome by FKBP51 and AR levels. Immunoblot and RT-qPCR were used to demonstrate androgen regulation of FKBP51 in primary and primary human prostatic fibroblasts and fibroblast cell-lines. As predicted by FKBP51 level, high AR activity in cancer stroma was associated with longer median survival (1,306 days) compared with high AR alone (699 days), whereas those with low AR and/or low FKBP51 did poorly (384 and 338 days, respectively). Survival could not be predicted on the basis cancer epithelial AR levels or activity, and was not associated with immunoreactivity in patient matched benign tissues. FKBP51 improves the ability of stromal AR to predict prostate cancer-specific mortality. By adding additional immunological assessment, similar to what is already in place in a number of other cancers, we could better serve patients with prostate cancer in prognosis and informed treatment choices. Prostate 77:185-195, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Esophageal cancer prediction based on qualitative features using adaptive fuzzy reasoning method

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Raed I. Hamed

2015-04-01

Full Text Available Esophageal cancer is one of the most common cancers world-wide and also the most common cause of cancer death. In this paper, we present an adaptive fuzzy reasoning algorithm for rule-based systems using fuzzy Petri nets (FPNs, where the fuzzy production rules are represented by FPN. We developed an adaptive fuzzy Petri net (AFPN reasoning algorithm as a prognostic system to predict the outcome for esophageal cancer based on the serum concentrations of C-reactive protein and albumin as a set of input variables. The system can perform fuzzy reasoning automatically to evaluate the degree of truth of the proposition representing the risk degree value with a weight value to be optimally tuned based on the observed data. In addition, the implementation process for esophageal cancer prediction is fuzzily deducted by the AFPN algorithm. Performance of the composite model is evaluated through a set of experiments. Simulations and experimental results demonstrate the effectiveness and performance of the proposed algorithms. A comparison of the predictive performance of AFPN models with other methods and the analysis of the curve showed the same results with an intuitive behavior of AFPN models.
Prediction of Pathological Complete Response Using Endoscopic Findings and Outcomes of Patients Who Underwent Watchful Waiting After Chemoradiotherapy for Rectal Cancer.

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Kawai, Kazushige; Ishihara, Soichiro; Nozawa, Hiroaki; Hata, Keisuke; Kiyomatsu, Tomomichi; Morikawa, Teppei; Fukayama, Masashi; Watanabe, Toshiaki

2017-04-01

Nonoperative management for patients with rectal cancer who have achieved a clinical complete response after chemoradiotherapy is becoming increasingly important in recent years. However, the definition of and modality used for patients with clinical complete response differ greatly between institutions, and the role of endoscopic assessment as a nonoperative approach has not been fully investigated. This study aimed to investigate the ability of endoscopic assessments to predict pathological regression of rectal cancer after chemoradiotherapy and the applicability of these assessments for the watchful waiting approach. This was a retrospective comparative study. This study was conducted at a single referral hospital. A total of 198 patients with rectal cancer underwent preoperative endoscopic assessments after chemoradiotherapy. Of them, 186 patients underwent radical surgery with lymph node dissection. The histopathological findings of resected tissues were compared with the preoperative endoscopic findings. Twelve patients refused radical surgery and chose watchful waiting; their outcomes were compared with the outcomes of patients who underwent radical surgery. The endoscopic criteria correlated well with tumor regression grading. The sensitivity and specificity for a pathological complete response were 65.0% to 87.1% and 39.1% to 78.3%. However, endoscopic assessment could not fully discriminate pathological complete responses, and the outcomes of patients who underwent watchful waiting were considerably poorer than the patients who underwent radical surgery. Eventually, 41.7% of the patients who underwent watchful waiting experienced uncontrollable local failure, and many of these occurrences were observed more than 3 years after chemoradiotherapy. The number of the patients treated with the watchful waiting strategy was limited, and the selection was not randomized. Although endoscopic assessment after chemoradiotherapy correlated with pathological response
Personal resilience resources predict post-stem cell transplant cancer survivors' psychological outcomes through reductions in depressive symptoms and meaning-making.

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Campo, Rebecca A; Wu, Lisa M; Austin, Jane; Valdimarsdottir, Heiddis; Rini, Christine

2017-01-01

This longitudinal study examined whether post-transplant cancer survivors (N = 254, 9 months to 3 years after stem cell transplant treatment) with greater personal resilience resources demonstrated better psychological outcomes and whether this could be attributed to reductions in depressive symptoms and/or four meaning-making processes (searching for and finding reasons for one's illness; searching for and finding benefit from illness). Hierarchical linear regression analyses examined associations of survivors' baseline personal resilience resources (composite variable of self-esteem, mastery, and optimism), which occurred an average of 1.7 years after transplant, and 4-month changes in psychological outcomes highly relevant to recovering from this difficult and potentially traumatic treatment: post-traumatic stress disorder (PTSD) symptoms and purpose in life. Boot-strapped analyses tested mediation. Greater personal resilience resources predicted decreases in PTSD stress symptoms (b = -0.07, p = 0.005), mediated by reductions in depressive symptoms (b = -0.01, 95% CI: -0.027, -0.003) and in searching for a reason for one's illness (b = -0.01, 95% CI: -0.034, -0.0003). In addition, greater resilience resources predicted increases in purpose in life (b = 0.10, p meaning-making (searching for a reason for one's illness) was also important for reducing PTSD symptoms.

Usefulness of Clinical Prediction Rules, D-dimer, and Arterial Blood Gas Analysis to Predict Pulmonary Embolism in Cancer Patients

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Shazia Awan

2017-03-01

Full Text Available Objectives: Pulmonary embolism (PE is seven times more common in cancer patients than non-cancer patients. Since the existing clinical prediction rules (CPRs were validated predominantly in a non-cancer population, we decided to look at the utility of arterial blood gas (ABG analysis and D-dimer in predicting PE in cancer patients. Methods: Electronic medical records were reviewed between December 2005 and November 2010. A total of 177 computed tomography pulmonary angiograms (CTPAs were performed. We selected 104 individuals based on completeness of laboratory and clinical data. Patients were divided into two groups, CTPA positive (patients with PE and CTPA negative (PE excluded. Wells score, Geneva score, and modified Geneva score were calculated for each patient. Primary outcomes of interest were the sensitivities, specificities, positive, and negative predictive values for all three CPRs. Results: Of the total of 104 individuals who had CTPAs, 33 (31.7% were positive for PE and 71 (68.3% were negative. There was no difference in basic demographics between the two groups. Laboratory parameters were compared and partial pressure of oxygen was significantly lower in patients with PE (68.1 mmHg vs. 71 mmHg, p = 0.030. Clinical prediction rules showed good sensitivities (88−100% and negative predictive values (93−100%. An alveolar-arterial (A-a gradient > 20 had 100% sensitivity and negative predictive values. Conclusions: CPRs and a low A-a gradient were useful in excluding PE in cancer patients. There is a need for prospective trials to validate these results.
Prediction of prostate cancer in unscreened men: external validation of a risk calculator.

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van Vugt, Heidi A; Roobol, Monique J; Kranse, Ries; Määttänen, Liisa; Finne, Patrik; Hugosson, Jonas; Bangma, Chris H; Schröder, Fritz H; Steyerberg, Ewout W

2011-04-01

Prediction models need external validation to assess their value beyond the setting where the model was derived from. To assess the external validity of the European Randomized study of Screening for Prostate Cancer (ERSPC) risk calculator (www.prostatecancer-riskcalculator.com) for the probability of having a positive prostate biopsy (P(posb)). The ERSPC risk calculator was based on data of the initial screening round of the ERSPC section Rotterdam and validated in 1825 and 531 men biopsied at the initial screening round in the Finnish and Swedish sections of the ERSPC respectively. P(posb) was calculated using serum prostate specific antigen (PSA), outcome of digital rectal examination (DRE), transrectal ultrasound and ultrasound assessed prostate volume. The external validity was assessed for the presence of cancer at biopsy by calibration (agreement between observed and predicted outcomes), discrimination (separation of those with and without cancer), and decision curves (for clinical usefulness). Prostate cancer was detected in 469 men (26%) of the Finnish cohort and in 124 men (23%) of the Swedish cohort. Systematic miscalibration was present in both cohorts (mean predicted probability 34% versus 26% observed, and 29% versus 23% observed, both pscreened men, but overestimated the risk of a positive biopsy. Further research is necessary to assess the performance and applicability of the ERSPC risk calculator when a clinical setting is considered rather than a screening setting. Copyright © 2010 Elsevier Ltd. All rights reserved.
Predicting Recurrence and Progression of Noninvasive Papillary Bladder Cancer at Initial Presentation Based on Quantitative Gene Expression Profiles

DEFF Research Database (Denmark)

Birkhahn, M.; Mitra, A.P.; Williams, Johan

2010-01-01

% specificity. Since this is a small retrospective study using medium-throughput profiling, larger confirmatory studies are needed. Conclusions: Gene expression profiling across relevant cancer pathways appears to be a promising approach for Ta bladder tumor outcome prediction at initial diagnosis......Background: Currently, tumor grade is the best predictor of outcome at first presentation of noninvasive papillary (Ta) bladder cancer. However, reliable predictors of Ta tumor recurrence and progression for individual patients, which could optimize treatment and follow-up schedules based...... on specific tumor biology, are yet to be identified. Objective: To identify genes predictive for recurrence and progression in Ta bladder cancer at first presentation using a quantitative, pathway-specific approach. Design, setting, and participants: Retrospective study of patients with Ta G2/3 bladder tumors...
Benefits and harms of prostate cancer screening – predictions of the ONCOTYROL prostate cancer outcome and policy model

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Nikolai Mühlberger

2017-06-01

Full Text Available Abstract Background A recent recalibration of the ONCOTYROL Prostate Cancer Outcome and Policy (PCOP Model, assuming that latent prostate cancer (PCa detectable at autopsy might be detectable by screening as well, resulted in considerable worsening of the benefit-harm balance of screening. In this study, we used the recalibrated model to assess the effects of familial risk, quality of life (QoL preferences, age, and active surveillance. Methods Men with average and elevated familial PCa risk were simulated in separate models, differing in familial risk parameters. Familial risk was assumed to affect PCa onset and progression simultaneously in the base-case, and separately in scenario analyses. Evaluated screening strategies included one-time screening at different ages, and screening at different intervals and age ranges. Optimal screening strategies were identified depending on age and individual QoL preferences. Strategies were additionally evaluated with active surveillance by biennial re-biopsy delaying treatment of localized cancer until grade progression to Gleason score ≥ 7. Results Screening men with average PCa risk reduced quality-adjusted life expectancy (QALE even under favorable assumptions. Men with elevated familial risk, depending on age and disutilities, gained QALE. While for men with familial risk aged 55 and 60 years annual screening to age 69 was the optimal strategy over most disutility ranges, no screening was the preferred option for 65 year-old men with average and above disutilities. Active surveillance greatly reduced overtreatment, but QALE gains by averted adverse events were opposed by losses due to delayed treatment and additional biopsies. The effect of active surveillance on the benefit-harm balance of screening differed between populations, as net losses and gains in QALE predicted for screening without active surveillance in men with average and familial PCa risk, respectively, were both reduced
Prognostic nomograms for predicting survival and distant metastases in locally advanced rectal cancers.

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Junjie Peng

Full Text Available To develop prognostic nomograms for predicting outcomes in patients with locally advanced rectal cancers who do not receive preoperative treatment.A total of 883 patients with stage II-III rectal cancers were retrospectively collected from a single institution. Survival analyses were performed to assess each variable for overall survival (OS, local recurrence (LR and distant metastases (DM. Cox models were performed to develop a predictive model for each endpoint. The performance of model prediction was validated by cross validation and on an independent group of patients.The 5-year LR, DM and OS rates were 22.3%, 32.7% and 63.8%, respectively. Two prognostic nomograms were successfully developed to predict 5-year OS and DM-free survival rates, with c-index of 0.70 (95% CI = [0.66, 0.73] and 0.68 (95% CI = [0.64, 0.72] on the original dataset, and 0.76 (95% CI = [0.67, 0.86] and 0.73 (95% CI = [0.63, 0.83] on the validation dataset, respectively. Factors in our models included age, gender, carcinoembryonic antigen value, tumor location, T stage, N stage, metastatic lymph nodes ratio, adjuvant chemotherapy and chemoradiotherapy. Predicted by our nomogram, substantial variability in terms of 5-year OS and DM-free survival was observed within each TNM stage category.The prognostic nomograms integrated demographic and clinicopathological factors to account for tumor and patient heterogeneity, and thereby provided a more individualized outcome prognostication. Our individualized prediction nomograms could help patients with preoperatively under-staged rectal cancer about their postoperative treatment strategies and follow-up protocols.
Predictive Potential of Preoperative Nutritional Status in Long-Term Outcome Projections for Patients with Gastric Cancer.

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Sakurai, Katsunobu; Ohira, Masaichi; Tamura, Tatsuro; Toyokawa, Takahiro; Amano, Ryosuke; Kubo, Naoshi; Tanaka, Hiroaki; Muguruma, Kazuya; Yashiro, Masakazu; Maeda, Kiyoshi; Hirakawa, Kosei

2016-02-01

Preoperative nutritional status not only correlates with the incidence of postoperative complications but also may be indicative of long-term outcomes for patients with cancer. The impact of preoperative nutritional status on outcomes for patients undergoing gastrectomy for gastric cancer (GC) was investigated. The study reviewed 594 patients treated for GC by gastrectomy at the authors' hospital between January, 2004 and December, 2010. Onodera's prognostic nutritional index (PNI) was invoked, using an optimal cut point to group patients as having high (PNI > 45; n = 449) or low (PNI ≤ 45; n = 145) nutritional status. Clinicopathologic features, perioperative results, and long-term outcomes, including cause of death, were compared. Multivariate analysis of 5-year overall survival (OS) and disease-specific survival (DSS) indicated that low PNI was independently associated with unfavorable outcomes for patients with GC. In subgroup analysis, the 5-year OS and DSS rates for patients with GC at stages 1 and 2 were significantly worse in the low PNI group than in the high PNI group. Although wound and extrasurgical field infections also tended to be more frequent in the low PNI group, postoperative intraabdominal infections did not differ significantly by group. Preoperative PNI may have merit as a gauge of prognosis for patients with GC at stages 1 and 2, but PNI and postoperative morbidity showed no correlation in this setting.
Prostate Cancer Probability Prediction By Machine Learning Technique.

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Jović, Srđan; Miljković, Milica; Ivanović, Miljan; Šaranović, Milena; Arsić, Milena

2017-11-26

The main goal of the study was to explore possibility of prostate cancer prediction by machine learning techniques. In order to improve the survival probability of the prostate cancer patients it is essential to make suitable prediction models of the prostate cancer. If one make relevant prediction of the prostate cancer it is easy to create suitable treatment based on the prediction results. Machine learning techniques are the most common techniques for the creation of the predictive models. Therefore in this study several machine techniques were applied and compared. The obtained results were analyzed and discussed. It was concluded that the machine learning techniques could be used for the relevant prediction of prostate cancer.
Action-outcome learning and prediction shape the window of simultaneity of audiovisual outcomes.

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Desantis, Andrea; Haggard, Patrick

2016-08-01

To form a coherent representation of the objects around us, the brain must group the different sensory features composing these objects. Here, we investigated whether actions contribute in this grouping process. In particular, we assessed whether action-outcome learning and prediction contribute to audiovisual temporal binding. Participants were presented with two audiovisual pairs: one pair was triggered by a left action, and the other by a right action. In a later test phase, the audio and visual components of these pairs were presented at different onset times. Participants judged whether they were simultaneous or not. To assess the role of action-outcome prediction on audiovisual simultaneity, each action triggered either the same audiovisual pair as in the learning phase ('predicted' pair), or the pair that had previously been associated with the other action ('unpredicted' pair). We found the time window within which auditory and visual events appeared simultaneous increased for predicted compared to unpredicted pairs. However, no change in audiovisual simultaneity was observed when audiovisual pairs followed visual cues, rather than voluntary actions. This suggests that only action-outcome learning promotes temporal grouping of audio and visual effects. In a second experiment we observed that changes in audiovisual simultaneity do not only depend on our ability to predict what outcomes our actions generate, but also on learning the delay between the action and the multisensory outcome. When participants learned that the delay between action and audiovisual pair was variable, the window of audiovisual simultaneity for predicted pairs increased, relative to a fixed action-outcome pair delay. This suggests that participants learn action-based predictions of audiovisual outcome, and adapt their temporal perception of outcome events based on such predictions. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Gene Polymorphism-related Individual and Interracial Differences in the Outcomes of Androgen Deprivation Therapy for Prostate Cancer.

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Fujimoto, Naohiro; Shiota, Masaki; Tomisaki, Ikko; Minato, Akinori

2017-06-01

Among patients with prostate cancer, the prognosis after androgen deprivation therapy differs significantly among individuals and among races; however, the reasons underlying these differences are poorly understood. Several single nucleotide polymorphisms in genes associated with prostate cancer progression or castration resistance might serve as the host factor that influences prognosis and, thus, accounts for these individual and racial gaps in treatment outcomes. Accordingly, single nucleotide polymorphisms associated with treatment outcomes could be used as predictive and/or prognostic biomarkers for patient stratification and to identify personalized treatment and follow-up protocols. The present review has summarized the genetic polymorphisms that have been reported to associate with androgen deprivation therapy outcomes among patients with prostate cancer and compared the allele frequencies among different ethnic groups. Copyright © 2017 Elsevier Inc. All rights reserved.
Microarray-based cancer prediction using soft computing approach.

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Wang, Xiaosheng; Gotoh, Osamu

2009-05-26

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.
Tandem repeat variation near the HIC1 (hypermethylated in cancer 1) promoter predicts outcome of oxaliplatin-based chemotherapy in patients with metastatic colorectal cancer.

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Okazaki, Satoshi; Schirripa, Marta; Loupakis, Fotios; Cao, Shu; Zhang, Wu; Yang, Dongyun; Ning, Yan; Berger, Martin D; Miyamoto, Yuji; Suenaga, Mitsukuni; Iqubal, Syma; Barzi, Afsaneh; Cremolini, Chiara; Falcone, Alfredo; Battaglin, Francesca; Salvatore, Lisa; Borelli, Beatrice; Helentjaris, Timothy G; Lenz, Heinz-Josef

2017-11-15

The hypermethylated in cancer 1/sirtuin 1 (HIC1/SIRT1) axis plays an important role in regulating the nucleotide excision repair pathway, which is the main oxaliplatin-induced damage-repair system. On the basis of prior evidence that the variable number of tandem repeat (VNTR) sequence located near the promoter lesion of HIC1 is associated with HIC1 gene expression, the authors tested the hypothesis that this VNTR is associated with clinical outcome in patients with metastatic colorectal cancer who receive oxaliplatin-based chemotherapy. Four independent cohorts were tested. Patients who received oxaliplatin-based chemotherapy served as the training cohort (n = 218), and those who received treatment without oxaliplatin served as the control cohort (n = 215). Two cohorts of patients who received oxaliplatin-based chemotherapy were used for validation studies (n = 176 and n = 73). The VNTR sequence near HIC1 was analyzed by polymerase chain reaction analysis and gel electrophoresis and was tested for associations with the response rate, progression-free survival, and overall survival. In the training cohort, patients who harbored at least 5 tandem repeats (TRs) in both alleles had a significantly shorter PFS compared with those who had fewer than 4 TRs in at least 1 allele (9.5 vs 11.6 months; hazard ratio, 1.93; P = .012), and these findings remained statistically significant after multivariate analysis (hazard ratio, 2.00; 95% confidence interval, 1.13-3.54; P = .018). This preliminary association was confirmed in the validation cohort, and patients who had at least 5 TRs in both alleles had a worse PFS compared with the other cohort (7.9 vs 9.8 months; hazard ratio, 1.85; P = .044). The current findings suggest that the VNTR sequence near HIC1 could be a predictive marker for oxaliplatin-based chemotherapy in patients with metastatic colorectal cancer. Cancer 2017;123:4506-14. © 2017 American Cancer Society. © 2017 American Cancer Society.
The Identification of a Threshold of Long Work Hours for Predicting Elevated Risks of Adverse Health Outcomes.

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Conway, Sadie H; Pompeii, Lisa A; Gimeno Ruiz de Porras, David; Follis, Jack L; Roberts, Robert E

2017-07-15

Working long hours has been associated with adverse health outcomes. However, a definition of long work hours relative to adverse health risk has not been established. Repeated measures of work hours among approximately 2,000 participants from the Panel Study of Income Dynamics (1986-2011), conducted in the United States, were retrospectively analyzed to derive statistically optimized cutpoints of long work hours that best predicted three health outcomes. Work-hours cutpoints were assessed for model fit, calibration, and discrimination separately for the outcomes of poor self-reported general health, incident cardiovascular disease, and incident cancer. For each outcome, the work-hours threshold that best predicted increased risk was 52 hours per week or more for a minimum of 10 years. Workers exposed at this level had a higher risk of poor self-reported general health (relative risk (RR) = 1.28; 95% confidence interval (CI): 1.06, 1.53), cardiovascular disease (RR = 1.42; 95% CI: 1.24, 1.63), and cancer (RR = 1.62; 95% CI: 1.22, 2.17) compared with those working 35-51 hours per week for the same duration. This study provides the first health risk-based definition of long work hours. Further examination of the predictive power of this cutpoint on other health outcomes and in other study populations is needed. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
A Polymorphism within the Vitamin D Transporter Gene Predicts Outcome in Metastatic Colorectal Cancer Patients Treated with FOLFIRI/Bevacizumab or FOLFIRI/Cetuximab.

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Berger, Martin D; Stintzing, Sebastian; Heinemann, Volker; Cao, Shu; Yang, Dongyun; Sunakawa, Yu; Matsusaka, Satoshi; Ning, Yan; Okazaki, Satoshi; Miyamoto, Yuji; Suenaga, Mitsukuni; Schirripa, Marta; Hanna, Diana L; Soni, Shivani; Puccini, Alberto; Zhang, Wu; Cremolini, Chiara; Falcone, Alfredo; Loupakis, Fotios; Lenz, Heinz-Josef

2018-02-15

Purpose: Vitamin D exerts its inhibitory influence on colon cancer growth by inhibiting Wnt signaling and angiogenesis. We hypothesized that SNPs in genes involved in vitamin D transport, metabolism, and signaling are associated with outcome in metastatic colorectal cancer (mCRC) patients treated with first-line FOLFIRI and bevacizumab. Experimental Design: 522 mCRC patients enrolled in the FIRE-3 (discovery cohort) and TRIBE (validation set) trials treated with FOLFIRI/bevacizumab were included in this study. 278 patients receiving FOLFIRI and cetuximab (FIRE-3) served as a control cohort. Six SNPs in 6 genes ( GC, CYP24A1, CYP27B1, VDR, DKK1, CST5 ) were analyzed. Results: In the discovery cohort, AA carriers of the GC rs4588 SNP encoding for the vitamin D-binding protein, and treated with FOLFIRI/bevacizumab had a shorter overall survival (OS) than those harboring any C allele (15.9 vs. 25.1 months) in both univariable ( P = 0.001) and multivariable analyses ( P = 0.047). This association was confirmed in the validation cohort in multivariable analysis (OS 18.1 vs. 26.2 months, HR, 1.83; P = 0.037). Interestingly, AA carriers in the control set exhibited a longer OS (48.0 vs. 25.2 months, HR, 0.50; P = 0.021). This association was further confirmed in a second validation cohort comprising refractory mCRC patients treated with cetuximab ± irinotecan (PFS 8.7 vs. 3.7 months) in univariable ( P = 0.033) and multivariable analyses ( P = 0.046). Conclusions: GC rs4588 SNP might serve as a predictive marker in mCRC patients treated with FOLFIRI/bevacizumab or FOLFIRI/cetuximab. Whereas AA carriers derive a survival benefit with FOLFIRI/cetuximab, treatment with FOLFIRI/bevacizumab is associated with a worse outcome. Clin Cancer Res; 24(4); 784-93. ©2017 AACR . ©2017 American Association for Cancer Research.
Altered expression of HER-2 and the mismatch repair genes MLH1 and MSH2 predicts the outcome of T1 high-grade bladder cancer.

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Sanguedolce, Francesca; Cormio, Antonella; Massenio, Paolo; Pedicillo, Maria C; Cagiano, Simona; Fortunato, Francesca; Calò, Beppe; Di Fino, Giuseppe; Carrieri, Giuseppe; Bufo, Pantaleo; Cormio, Luigi

2018-04-01

The identification of factors predicting the outcome of stage T1 high-grade bladder cancer (BC) is a major clinical issue. We performed immunohistochemistry to assess the role of human epidermal growth factor receptor-2 (HER-2) and microsatellite instability (MSI) factors MutL homologue 1 (MLH1) and MutS homologue 2 (MSH2) in predicting recurrence and progression of T1 high-grade BCs having undergone transurethral resection of bladder tumor (TURBT) alone or TURBT + intravesical instillations of bacillus Calmette-Guerin (BCG). HER-2 overexpression was a significant predictor of disease-free survival (DFS) in the overall as well as in the two patients' population; as for progression-free survival (PFS), it was significant in the overall but not in the two patients' population. MLH1 was an independent predictor of PFS only in patients treated with BCG and MSH2 failed to predict DFS and PFS in all populations. Most importantly, the higher the number of altered markers the lowers the DFS and PFS. In multivariate Cox proportional-hazards regression analysis, the number of altered molecular markers and BCG treatment were significant predictors (p = 0.0004 and 0.0283, respectively) of DFS, whereas the number of altered molecular markers was the only significant predictor (p = 0.0054) of PFS. Altered expression of the proto-oncogene HER-2 and the two molecular markers of genetic instability MLH1 and MSH2 predicted T1 high-grade BC outcome with the higher the number of altered markers the lower the DFS and PFS. These findings provide grounds for further testing them in predicting the outcome of this challenging disease.
Predictive and Prognostic Value of sPRR in Patients with Primary Epithelial Ovarian Cancer

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Katrin Kreienbring

2016-01-01

Full Text Available Aim. The purpose of the present study was to analyze the predictive and prognostic role of soluble (prorenin receptor (sPRR as a biomarker for clinicopathological outcome in patients with primary epithelial ovarian cancer (EOC. As part of the renin-angiotensin system (RAS whose activity is known to increase in ovarian cancer patients, the relation of sPRR and ovarian cancer should be further investigated. Patients and Methods. In this study 197 patients with primary EOC in our institution from 2000 to 2011 were included. sPRR was determined by enzyme-linked immunosorbent assay (ELISA in preoperative taken blood sera. Associations with clinicopathological outcome were analyzed and serum levels of sPRR in patients have been compared to those in healthy specimen. Kaplan-Meier and logistic/Cox regression assessed the impact of the markers on progression-free survival (PFS and overall survival (OS. Results. There have been no correlations proved of sPRR levels with neither clinicopathological factors nor prognostic data. Also the distribution of sPRR in patients and controls was normal. Conclusion. sPRR seems to have no predictive, prognostic, or diagnostic value in EOC. As several factors of the RAS which might indicate cancer events have been shown, sPRR seems not to be affected.
Chemotherapy-related leukopenia as a biomarker predicting survival outcomes in locally advanced cervical cancer.

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Bogani, Giorgio; Sabatucci, Ilaria; Maltese, Giuseppa; Lecce, Francesca; Signorelli, Mauro; Martinelli, Fabio; Chiappa, Valentina; Indini, Alice; Leone Roberti Maggiore, Umberto; Borghi, Chiara; Fucà, Giovanni; Ditto, Antonino; Raspagliesi, Francesco; Lorusso, Domenica

2017-01-01

To investigate the impact of hematologic toxicity and leukopenia in locally advanced cervical cancer patients undergoing neoadjuvant chemotherapy (NACT). Data of consecutive patients undergoing platinum-based NACT followed by surgery were retrospectively searched in order to evaluate the impact of chemotherapy-related toxicity on survival outcomes. Toxicity was graded per the Common Terminology Criteria for Adverse Events (CTCAEv.4.03). Survival outcomes were evaluated using Kaplan-Meir and Cox hazard models. Overall, 126 patients were included. Among those, 94 (74.6%) patients experienced grade2+ hematologic toxicity; while, grade2+ non-hematologic toxicity occurred in 11 (8.7%) patients. After a median follow-up of 37.1 (inter-quartile range, 12-57.5) months, 21 (16.6%) patients experienced recurrence. Via multivariate analysis, no factor was independently associated with disease-free survival; while a trend toward worse prognosis was observed for patients experiencing grade2+ leukopenia at cycle-3 (HR:3.13 (95%CI: 0.94, 10.3); p=0.06). Similarly, grade2+ leukopenia (HR:9.98 (95%CI: 1.14, 86.6); p=0.03), lymph-node positivity (HR:14.6 (95%CI:1.0, 214.4); p=0.05) and vaginal involvement (HR:5.81 (95%CI:1.43, 23.6); p=0.01) impacted on overall survival, at multivariate analysis. Magnitude of leukopenia correlated with survival (p<0.001). Although, our data have to be confirmed by prospective investigations, the present study shows an association between the occurrence of leukopenia and survival outcomes. NACT-related immunosuppression might reduce the response against the tumor, thus promoting cancer progression. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study.

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Miao, Hui; Hartman, Mikael; Bhoo-Pathy, Nirmala; Lee, Soo-Chin; Taib, Nur Aishah; Tan, Ern-Yu; Chan, Patrick; Moons, Karel G M; Wong, Hoong-Seam; Goh, Jeremy; Rahim, Siti Mastura; Yip, Cheng-Har; Verkooijen, Helena M

2014-01-01

In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.
Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study.

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Hui Miao

Full Text Available BACKGROUND: In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. MATERIALS AND METHODS: We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic. RESULTS: We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53 to 0.63 (95% CI, 0.60-0.66. CONCLUSION: The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.
Elevated C1orf63 expression is correlated with CDK10 and predicts better outcome for advanced breast cancers: a retrospective study

International Nuclear Information System (INIS)

Hong, Chao-Qun; Zhang, Fan; You, Yan-Jie; Qiu, Wei-Li; Giuliano, Armando E.; Cui, Xiao-Jiang; Zhang, Guo-Jun; Cui, Yu-Kun

2015-01-01

independent prognostic factor predicting better clinical outcome (HR: 0.41; 95 % CI: 0.17 ~ 0.97; P = 0.042). Additionally, we found that CDK10 mRNA expression was positively correlated with C1orf63, which was consistent with the relationship of protein expression between C1orf63 and CDK10 (r s = 0.391; P < 0.001). Compared to adjacent non-cancerous tissues, C1orf63 expression was elevated in tumor tissues. However, C1orf63 predicts better prognosis for breast cancers with advanced TNM stage, and the underlying mechanism is unknown. In addition, C1orf63 is correlated with the cell cycle related gene, CDK10
Early Prediction of Disease Progression in Small Cell Lung Cancer: Toward Model-Based Personalized Medicine in Oncology.

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Buil-Bruna, Núria; Sahota, Tarjinder; López-Picazo, José-María; Moreno-Jiménez, Marta; Martín-Algarra, Salvador; Ribba, Benjamin; Trocóniz, Iñaki F

2015-06-15

Predictive biomarkers can play a key role in individualized disease monitoring. Unfortunately, the use of biomarkers in clinical settings has thus far been limited. We have previously shown that mechanism-based pharmacokinetic/pharmacodynamic modeling enables integration of nonvalidated biomarker data to provide predictive model-based biomarkers for response classification. The biomarker model we developed incorporates an underlying latent variable (disease) representing (unobserved) tumor size dynamics, which is assumed to drive biomarker production and to be influenced by exposure to treatment. Here, we show that by integrating CT scan data, the population model can be expanded to include patient outcome. Moreover, we show that in conjunction with routine medical monitoring data, the population model can support accurate individual predictions of outcome. Our combined model predicts that a change in disease of 29.2% (relative standard error 20%) between two consecutive CT scans (i.e., 6-8 weeks) gives a probability of disease progression of 50%. We apply this framework to an external dataset containing biomarker data from 22 small cell lung cancer patients (four patients progressing during follow-up). Using only data up until the end of treatment (a total of 137 lactate dehydrogenase and 77 neuron-specific enolase observations), the statistical framework prospectively identified 75% of the individuals as having a predictable outcome in follow-up visits. This included two of the four patients who eventually progressed. In all identified individuals, the model-predicted outcomes matched the observed outcomes. This framework allows at risk patients to be identified early and therapeutic intervention/monitoring to be adjusted individually, which may improve overall patient survival. ©2015 American Association for Cancer Research.

Use of Molecular Imaging to Predict Clinical Outcome in Patients With Rectal Cancer After Preoperative Chemotherapy and Radiation

International Nuclear Information System (INIS)

Konski, Andre; Li Tianyu; Sigurdson, Elin; Cohen, Steven J.; Small, William; Spies, Stewart; Yu, Jian Q.; Wahl, Andrew; Stryker, Steven; Meropol, Neal J.

2009-01-01

Purpose: To correlate changes in 2-deoxy-2-[18F]fluoro-D-glucose (18-FDG) positron emission tomography (PET) (18-FDG-PET) uptake with response and disease-free survival with combined modality neoadjuvant therapy in patients with locally advanced rectal cancer. Methods and Materials: Charts were reviewed for consecutive patients with ultrasound-staged T3x to T4Nx or TxN1 rectal adenocarcinoma who underwent preoperative chemoradiation therapy at Fox Chase Cancer Center (FCCC) or Robert H. Lurie Comprehensive Cancer Center of Northwestern University with 18-FDG-PET scanning before and after combined-modality neoadjuvant chemoradiation therapy . The maximum standardized uptake value (SUV) was measured from the tumor before and 3 to 4 weeks after completion of chemoradiation therapy preoperatively. Logistic regression was used to analyze the association of pretreatment SUV, posttreatment SUV, and % SUV decrease on pathologic complete response (pCR), and a Cox model was fitted to analyze disease-free survival. Results: A total of 53 patients (FCCC, n = 41, RLCCC, n = 12) underwent pre- and postchemoradiation PET scanning between September 2000 and June 2006. The pCR rate was 31%. Univariate analysis revealed that % SUV decrease showed a marginally trend in predicting pCR (p = 0.08). In the multivariable analysis, posttreatment SUV was shown a predictor of pCR (p = 0.07), but the test results did not reach statistical significance. None of the investigated variables were predictive of disease-free survival. Conclusions: A trend was observed for % SUV decrease and posttreatment SUV predicting pCR in patients with rectal cancer treated with preoperative chemoradiation therapy. Further prospective study with a larger sample size is warranted to better characterize the role of 18-FDG-PET for response prediction in patients with rectal cancer.
Early Prediction of Outcome in Advanced Head-and-Neck Cancer Based on Tumor Blood Volume Alterations During Therapy: A Prospective Study

International Nuclear Information System (INIS)

Cao Yue; Popovtzer, Aron; Li, Diana; Chepeha, Douglas B.; Moyer, Jeffrey S.; Prince, Mark E.; Worden, Francis; Teknos, Theodoros; Bradford, Carol; Mukherji, Suresh K.; Eisbruch, Avraham

2008-01-01

Purpose: To assess whether alterations in tumor blood volume (BV) and blood flow (BF) during the early course of chemo-radiotherapy (chemo-RT) for head-and-neck cancer (HNC) predict treatment outcome. Methods and Materials: Fourteen patients receiving concomitant chemo-RT for nonresectable, locally advanced HNC underwent dynamic contrast-enhanced (DCE) MRI scans before therapy and 2 weeks after initiation of chemo-RT. The BV and BF were quantified from DCE MRI. Preradiotherapy BV and BF, as well as their changes during RT, were evaluated separately in the primary gross tumor volume (GTV) and nodal GTV for association with outcomes. Results: At a median follow-up of 10 months (range, 5-27 months), 9 patients had local-regional controlled disease. One patient had regional failure, 3 had local failures, and 1 had local-regional failure. Reduction in tumor volume after 2 weeks of chemo-RT did not predict for local control. In contrast, the BV in the primary GTV after 2 weeks of chemo-RT was increased significantly in the local control patients compared with the local failure patients (p < 0.03). Conclusions: Our data suggest that an increase in available primary tumor blood for oxygen extraction during the early course of RT is associated with local control, thus yielding a predictor with potential to modify treatment. These findings require validation in larger studies
Colorectal cancer intrinsic subtypes predict chemotherapy benefit, deficient mismatch repair and epithelial-to-mesenchymal transition

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Roepman, P.; Schlicker, A.; Tabernero, J.; Majewski, I.; Tian, S.; Moreno, V.; Snel, M.H.; Chresta, C.M.; Rosenberg, R.; Nitsche, U.; Macarulla, T.; Capella, G.; Salazar, R.; Orphanides, G.; Wessels, L.F.A.; Bernards, R.; Simon, I.M.

2013-01-01

In most colorectal cancer (CRC) patients, outcome cannot be predicted because tumors with similar clinicopathological features can have differences in disease progression and treatment response. Therefore, a better understanding of the CRC biology is required to identify those patients who will
Implementing a Childhood Cancer Outcomes Surveillance System Within a Population-Based Cancer Registry

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Oscar Ramirez

2018-03-01

Full Text Available Purpose: Approximately 80% of cases of childhood cancer occur in low- and middle-income countries and are associated with high mortality rates. Assessing outcomes is essential for designing effective strategies to improve outcomes equally worldwide. We implemented a real-time surveillance system, VIGICANCER, embedded in a population-based cancer registry (PBCR to assess childhood cancer outcomes. Methods: VIGICANCER was established in 2009 as an integral part of Cali’s PBCR to collect real-time data on outcomes of patients (age < 19 years with a new diagnosis of cancer treated in pediatric oncology units in Cali, Colombia. Baseline and follow-up data (death, relapse, treatment abandonment, second neoplasms were collected from medical records, hospital discharge logs, pathology reports, death certificates, and the National Public Health Insurance database. A quality assurance process was implemented for the system. Results: From 2009 to 2013, data from 1,242 patients were included in VIGICANCER: 32% of patients were younger than 5 years, 55% were male, and 15% were Afro-descendants. International Classification of Childhood Cancer group I diagnoses predominated in all age groups except children younger than 1 year old, in whom CNS tumors predominated. Five-year overall survival for all cancers was 51.7% (95% CI, 47.9% to 55.4% for children (< 15 years, and 39.4% (95% CI, 29.8% to 50.5% for adolescents (15 to 18.9 years. Five-year overall survival for acute lymphoblastic leukemia was 55.6% (95% CI, 48.5% to 62.2%. Conclusion: Our study demonstrates the feasibility of implementing a real-time childhood cancer outcomes surveillance system embedded in a PBCR that can guide interventions to improve clinical outcomes in low- and middle-income countries.
Low Preoperative Prognostic Nutritional Index Predicts Poor Survival Post-gastrectomy in Elderly Patients with Gastric Cancer.

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Sakurai, Katsunobu; Tamura, Tatsuro; Toyokawa, Takahiro; Amano, Ryosuke; Kubo, Naoshi; Tanaka, Hiroaki; Muguruma, Kazuya; Yashiro, Masakazu; Maeda, Kiyoshi; Ohira, Masaichi; Hirakawa, Kosei

2016-10-01

Preoperative nutritional status may predict short- and long-term outcomes of patients with cancer. The aim of this study was to clarify the impact of preoperative nutritional status on outcomes of elderly patients who have undergone gastrectomy for gastric cancer (GC). A review examining 147 patients treated for GC by gastrectomy at our institution between January 2004 and December 2011 was conducted. Onodera's prognostic nutritional index (PNI) was invoked, using an optimal cutpoint to stratify patients by high (PNI > 43.8; n = 84) or low (PNI ≤ 43.8; n = 63) nutritional status. Clinicopathologic features and short- and long-term outcomes, including the cause of death, were compared. In multivariate analysis, low PNI was identified as an independent correlate of poor 5-year overall survival (OS). In subgroup analysis, 5-year OS rates for patients with stage 1 GC were significantly worse in the low PNI (vs. high PNI) patient subset, which also posed a significantly higher risk of death from other disease; however, 5-year cancer-specific survival and PNI were unrelated. Deaths from recurrence in both groups were statistically similar, and morbidity rates did not differ significantly by group. PNI is useful in predicting long-term outcomes of elderly patients surgically treated for GC, helping to identify those at high risk of death from other disease. In an effort to improve patient outcomes, nutritional status and oncologic staging merit attention.
Learned predictiveness and outcome predictability effects are not simply two sides of the same coin.

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Thorwart, Anna; Livesey, Evan J; Wilhelm, Francisco; Liu, Wei; Lachnit, Harald

2017-10-01

The Learned Predictiveness effect refers to the observation that learning about the relationship between a cue and an outcome is influenced by the predictive relevance of the cue for other outcomes. Similarly, the Outcome Predictability effect refers to a recent observation that the previous predictability of an outcome affects learning about this outcome in new situations, too. We hypothesize that both effects may be two manifestations of the same phenomenon and stimuli that have been involved in highly predictive relationships may be learned about faster when they are involved in new relationships regardless of their functional role in predictive learning as cues and outcomes. Four experiments manipulated both the relationships and the function of the stimuli. While we were able to replicate the standard effects, they did not survive a transfer to situations where the functional role of the stimuli changed, that is the outcome of the first phase becomes a cue in the second learning phase or the cue of the first phase becomes the outcome of the second phase. Furthermore, unlike learned predictiveness, there was little indication that the distribution of overt attention in the second phase was influenced by previous predictability. The results suggest that these 2 very similar effects are not manifestations of a more general phenomenon but rather independent from each other. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
DNA Mismatch Repair Deficiency in Rectal Cancer: Benchmarking Its Impact on Prognosis, Neoadjuvant Response Prediction, and Clinical Cancer Genetics.

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de Rosa, Nicole; Rodriguez-Bigas, Miguel A; Chang, George J; Veerapong, Jula; Borras, Ester; Krishnan, Sunil; Bednarski, Brian; Messick, Craig A; Skibber, John M; Feig, Barry W; Lynch, Patrick M; Vilar, Eduardo; You, Y Nancy

2016-09-01

DNA mismatch repair deficiency (dMMR) hallmarks consensus molecular subtype 1 of colorectal cancer. It is being routinely tested, but little is known about dMMR rectal cancers. The efficacy of novel treatment strategies cannot be established without benchmarking the outcomes of dMMR rectal cancer with current therapy. We aimed to delineate the impact of dMMR on prognosis, the predicted response to fluoropyrimidine-based neoadjuvant therapy, and implications of germline alterations in the MMR genes in rectal cancer. Between 1992 and 2012, 62 patients with dMMR rectal cancers underwent multimodality therapy. Oncologic treatment and outcomes as well as clinical genetics work-up were examined. Overall and rectal cancer-specific survival were calculated by the Kaplan-Meier method. The median age at diagnosis was 41 years. MMR deficiency was most commonly due to alterations in MSH2 (53%) or MSH6 (23%). After a median follow-up of 6.8 years, the 5-year rectal cancer-specific survival was 100% for stage I and II, 85.1% for stage III, and 60.0% for stage IV disease. Fluoropyrimidine-based neoadjuvant chemoradiation was associated with a complete pathologic response rate of 27.6%. The extent of surgical resection was influenced by synchronous colonic disease at presentation, tumor height, clinical stage, and pelvic radiation. An informed decision for a limited resection focusing on proctectomy did not compromise overall survival. Five of the 11 (45.5%) deaths during follow-up were due to extracolorectal malignancies. dMMR rectal cancer had excellent prognosis and pathologic response with current multimodality therapy including an individualized surgical treatment plan. Identification of a dMMR rectal cancer should trigger germline testing, followed by lifelong surveillance for both colorectal and extracolorectal malignancies. We herein provide genotype-specific outcome benchmarks for comparison with novel interventions. © 2016 by American Society of Clinical Oncology.
Early Adolescent Affect Predicts Later Life Outcomes.

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Kansky, Jessica; Allen, Joseph P; Diener, Ed

2016-07-01

Subjective well-being as a predictor for later behavior and health has highlighted its relationship to health, work performance, and social relationships. However, the majority of such studies neglect the developmental nature of well-being in contributing to important changes across the transition to adulthood. To examine the potential role of subjective well-being as a long-term predictor of critical life outcomes, we examined indicators of positive and negative affect at age 14 as predictors of relationship, adjustment, self-worth, and career outcomes a decade later at ages 23 to 25, controlling for family income and gender. We utilised multi-informant methods including reports from the target participant, close friends, and romantic partners in a demographically diverse community sample of 184 participants. Early adolescent positive affect predicted fewer relationship problems (less self-reported and partner-reported conflict, and greater friendship attachment as rated by close peers) and healthy adjustment to adulthood (lower levels of depression, anxiety, and loneliness). It also predicted positive work functioning (higher levels of career satisfaction and job competence) and increased self-worth. Negative affect did not significantly predict any of these important life outcomes. In addition to predicting desirable mean levels of later outcomes, early positive affect predicted beneficial changes across time in many outcomes. The findings extend early research on the beneficial outcomes of subjective well-being by having an earlier assessment of well-being, including informant reports in measuring a large variety of outcome variables, and by extending the findings to a lower socioeconomic group of a diverse and younger sample. The results highlight the importance of considering positive affect as an important component of subjective well-being distinct from negative affect. © 2016 The International Association of Applied Psychology.
Identifying the Gene Signatures from Gene-Pathway Bipartite Network Guarantees the Robust Model Performance on Predicting the Cancer Prognosis

Directory of Open Access Journals (Sweden)

Li He

2014-01-01

Full Text Available For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.
Breast Cancer: Treatment, Outcomes, and Cost-Effectiveness

National Research Council Canada - National Science Library

McClellan, Mark

2000-01-01

...) use Medicare data, linked SEER cancer registry data, and claims data from large firms to analyze trends in diagnosis rates and staging, treatment, expenditures, and outcomes for Americans with breast cancer; and (3...
MicroRNA classifier and nomogram for metastasis prediction in colon cancer.

Science.gov (United States)

Goossens-Beumer, Inès J; Derr, Remco S; Buermans, Henk P J; Goeman, Jelle J; Böhringer, Stefan; Morreau, Hans; Nitsche, Ulrich; Janssen, Klaus-Peter; van de Velde, Cornelis J H; Kuppen, Peter J K

2015-01-01

Colon cancer prognosis and treatment are currently based on a classification system still showing large heterogeneity in clinical outcome, especially in TNM stages II and III. Prognostic biomarkers for metastasis risk are warranted as development of distant recurrent disease mainly accounts for the high lethality rates of colon cancer. miRNAs have been proposed as potential biomarkers for cancer. Furthermore, a verified standard for normalization of the amount of input material in PCR-based relative quantification of miRNA expression is lacking. A selection of frozen tumor specimens from two independent patient cohorts with TNM stage II-III microsatellite stable primary adenocarcinomas was used for laser capture microdissection. Next-generation sequencing was performed on small RNAs isolated from colorectal tumors from the Dutch cohort (N = 50). Differential expression analysis, comparing in metastasized and nonmetastasized tumors, identified prognostic miRNAs. Validation was performed on colon tumors from the German cohort (N = 43) using quantitative PCR (qPCR). miR25-3p and miR339-5p were identified and validated as independent prognostic markers and used to construct a multivariate nomogram for metastasis risk prediction. The nomogram showed good probability prediction in validation. In addition, we recommend combination of miR16-5p and miR26a-5p as standard for normalization in qPCR of colon cancer tissue-derived miRNA expression. In this international study, we identified and validated a miRNA classifier in primary cancers, and propose a nomogram capable of predicting metastasis risk in microsatellite stable TNM stage II-III colon cancer. In conjunction with TNM staging, by means of a nomogram, this miRNA classifier may allow for personalized treatment decisions based on individual tumor characteristics. ©2014 American Association for Cancer Research.
The Neutrophil-Platelet Score (NPS Predicts Survival in Primary Operable Colorectal Cancer and a Variety of Common Cancers.

Directory of Open Access Journals (Sweden)

David G Watt

Full Text Available Recent in-vitro studies have suggested that a critical checkpoint early in the inflammatory process involves the interaction between neutrophils and platelets. This confirms the importance of the innate immune system in the elaboration of the systemic inflammatory response. The aim of the present study was to examine whether a combination of the neutrophil and platelet counts were predictive of survival in patients with cancer.Patients with histologically proven colorectal cancer who underwent potentially curative resection at a single centre between March 1999 and May 2013 (n = 796 and patients with cancer from the Glasgow Inflammation Outcome Study, who had a blood sample taken between January 2000 and December 2007 (n = 9649 were included in the analysis.In the colorectal cancer cohort, there were 173 cancer and 135 non-cancer deaths. In patients undergoing elective surgery, cancer-specific survival (CSS at 5 years ranged from 97% in patients with TNM I disease and NPS = 0 to 57% in patients with TNM III disease and NPS = 2 (p = 0.019 and in patients undergoing elective surgery for node-negative colon cancer from 98% (TNM I, NPS = 0 to 65% (TNM II, NPS = 2 (p = 0.004. In those with a variety of common cancers there were 5218 cancer and 929 non-cancer deaths. On multivariate analysis, adjusting for age and sex and stratified by tumour site, incremental increase in the NPS was significantly associated with poorer CSS (p<0.001.The neutrophil-platelet score predicted survival in a variety of common cancers and highlights the importance of the innate immune system in patients with cancer.
Preoperative Nomogram Predicting the 10-Year Probability of Prostate Cancer Recurrence After Radical Prostatectomy

Science.gov (United States)

Stephenson, Andrew J.; Scardino, Peter T.; Eastham, James A.; Bianco, Fernando J.; Dotan, Zohar A.; Fearn, Paul A.; Kattan, Michael W.

2008-01-01

An existing preoperative nomogram predicts the probability of prostate cancer recurrence, defined by prostate-specific antigen (PSA), at 5 years after radical prostatectomy based on clinical stage, serum PSA, and biopsy Gleason grade. In an updated and enhanced nomogram, we have extended the predictions to 10 years, added the prognostic information of systematic biopsy results, and enabled the predictions to be adjusted for the year of surgery. Cox regression analysis was used to model the clinical information for 1978 patients treated by two high-volume surgeons from our institution. The nomogram was externally validated on an independent cohort of 1545 patients with a concordance index of 0.79 and was well calibrated with respect to observed outcome. The inclusion of the number of positive and negative biopsy cores enhanced the predictive accuracy of the model. Thus, a new preoperative nomogram provides robust predictions of prostate cancer recurrence up to 10 years after radical prostatectomy. PMID:16705126
Depression and under-treatment of depression: potential risks and outcomes in black lung cancer patients

Science.gov (United States)

Traeger, Lara; Cannon, Sheila; Pirl, William F.; Park, Elyse R.

2015-01-01

In the U.S., black men are at higher risk than white men for lung cancer mortality whereas rates are comparable between black and white women. This paper draws from empirical work in lung cancer, mental health and health disparities to highlight that race and depression may overlap in predicting lower treatment access and utilization and poorer quality of life among patients. Racial barriers to depression identification and treatment in the general population may compound these risks. Prospective data are needed to examine whether depression plays a role in racial disparities in lung cancer outcomes. PMID:23514250
Improving breast cancer outcome prediction by combining multiple data sources

NARCIS (Netherlands)

Van Vliet, M.H.

2010-01-01

Cancer has recently become the number one cause of death in The Netherlands. Breast cancer is the most prevalent form of cancer among females, with a lifetime risk of 12.8% (i.e. the 1 in 8 rule). As a result, more and more research is devoted to getting a better insight into cancer, and to further
Primary tumor location predicts poor clinical outcome with cetuximab in RAS wild-type metastatic colorectal cancer.

Science.gov (United States)

Kim, Dalyong; Kim, Sun Young; Lee, Ji Sung; Hong, Yong Sang; Kim, Jeong Eun; Kim, Kyu-Pyo; Kim, Jihun; Jang, Se Jin; Yoon, Young-Kwang; Kim, Tae Won

2017-11-23

In metastatic colorectal cancer, the location of the primary tumor has been suggested to have biological significance. In this study, we investigated whether primary tumor location affects cetuximab efficacy in patients with RAS wild-type metastatic colorectal cancer. Genotyping by the SequenomMassARRAY technology platform (OncoMap) targeting KRAS, NRAS, PIK3CA, and BRAF was performed in tumors from 307 patients who had been given cetuximab as salvage treatment. Tumors with mutated RAS (KRAS or NRAS; n = 127) and those with multiple primary location (n = 10) were excluded. Right colon cancer was defined as a tumor located in the proximal part to splenic flexure. A total of 170 patients were included in the study (right versus left, 23 and 147, respectively). Patients with right colon cancer showed more mutated BRAF (39.1% vs. 5.4%), mutated PIK3CA (13% vs. 1.4%), poorly differentiated tumor (17.4% vs. 3.4%), and peritoneal involvement (26.1% vs. 8.8%) than those with left colon and rectal cancer. Right colon cancer showed poorer progression-free survival (2.0 vs.5.0 months, P = 0.002) and overall survival (4.1 months and 13.0 months, P < 0.001) than the left colon and rectal cancer. By multivariable analysis, BRAF mutation, right colon primary, poorly differentiated histology, and peritoneal involvement were associated with risk of death. In RAS wild-type colon cancer treated with cetuximab as salvage treatment, right colon primary was associated with poorer survival outcomes than left colon and rectal cancer.
A Review of Current Machine Learning Methods Used for Cancer Recurrence Modeling and Prediction

Energy Technology Data Exchange (ETDEWEB)

Hemphill, Geralyn M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-09-27

Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type has become a necessity in cancer research. A major challenge in cancer management is the classification of patients into appropriate risk groups for better treatment and follow-up. Such risk assessment is critically important in order to optimize the patient’s health and the use of medical resources, as well as to avoid cancer recurrence. This paper focuses on the application of machine learning methods for predicting the likelihood of a recurrence of cancer. It is not meant to be an extensive review of the literature on the subject of machine learning techniques for cancer recurrence modeling. Other recent papers have performed such a review, and I will rely heavily on the results and outcomes from these papers. The electronic databases that were used for this review include PubMed, Google, and Google Scholar. Query terms used include “cancer recurrence modeling”, “cancer recurrence and machine learning”, “cancer recurrence modeling and machine learning”, and “machine learning for cancer recurrence and prediction”. The most recent and most applicable papers to the topic of this review have been included in the references. It also includes a list of modeling and classification methods to predict cancer recurrence.
Macaques can predict social outcomes from facial expressions.

Science.gov (United States)

Waller, Bridget M; Whitehouse, Jamie; Micheletta, Jérôme

2016-09-01

There is widespread acceptance that facial expressions are useful in social interactions, but empirical demonstration of their adaptive function has remained elusive. Here, we investigated whether macaques can use the facial expressions of others to predict the future outcomes of social interaction. Crested macaques (Macaca nigra) were shown an approach between two unknown individuals on a touchscreen and were required to choose between one of two potential social outcomes. The facial expressions of the actors were manipulated in the last frame of the video. One subject reached the experimental stage and accurately predicted different social outcomes depending on which facial expressions the actors displayed. The bared-teeth display (homologue of the human smile) was most strongly associated with predicted friendly outcomes. Contrary to our predictions, screams and threat faces were not associated more with conflict outcomes. Overall, therefore, the presence of any facial expression (compared to neutral) caused the subject to choose friendly outcomes more than negative outcomes. Facial expression in general, therefore, indicated a reduced likelihood of social conflict. The findings dispute traditional theories that view expressions only as indicators of present emotion and instead suggest that expressions form part of complex social interactions where individuals think beyond the present.
A seven-gene CpG-island methylation panel predicts breast cancer progression

International Nuclear Information System (INIS)

Li, Yan; Melnikov, Anatoliy A.; Levenson, Victor; Guerra, Emanuela; Simeone, Pasquale; Alberti, Saverio; Deng, Youping

2015-01-01

DNA methylation regulates gene expression, through the inhibition/activation of gene transcription of methylated/unmethylated genes. Hence, DNA methylation profiling can capture pivotal features of gene expression in cancer tissues from patients at the time of diagnosis. In this work, we analyzed a breast cancer case series, to identify DNA methylation determinants of metastatic versus non-metastatic tumors. CpG-island methylation was evaluated on a 56-gene cancer-specific biomarker microarray in metastatic versus non-metastatic breast cancers in a multi-institutional case series of 123 breast cancer patients. Global statistical modeling and unsupervised hierarchical clustering were applied to identify a multi-gene binary classifier with high sensitivity and specificity. Network analysis was utilized to quantify the connectivity of the identified genes. Seven genes (BRCA1, DAPK1, MSH2, CDKN2A, PGR, PRKCDBP, RANKL) were found informative for prognosis of metastatic diffusion and were used to calculate classifier accuracy versus the entire data-set. Individual-gene performances showed sensitivities of 63–79 %, 53–84 % specificities, positive predictive values of 59–83 % and negative predictive values of 63–80 %. When modelled together, these seven genes reached a sensitivity of 93 %, 100 % specificity, a positive predictive value of 100 % and a negative predictive value of 93 %, with high statistical power. Unsupervised hierarchical clustering independently confirmed these findings, in close agreement with the accuracy measurements. Network analyses indicated tight interrelationship between the identified genes, suggesting this to be a functionally-coordinated module, linked to breast cancer progression. Our findings identify CpG-island methylation profiles with deep impact on clinical outcome, paving the way for use as novel prognostic assays in clinical settings. The online version of this article (doi:10.1186/s12885-015-1412-9) contains supplementary
Factors and outcomes of decision making for cancer clinical trial participation.

Science.gov (United States)

Biedrzycki, Barbara A

2011-09-01

To describe factors and outcomes related to the decision-making process regarding participation in a cancer clinical trial. Cross-sectional, descriptive. Urban, academic, National Cancer Institute-designated comprehensive cancer center in the mid-Atlantic United States. 197 patients with advanced gastrointestinal cancer. Mailed survey using one investigator-developed instrument, eight instruments used in published research, and a medical record review. disease context, sociodemographics, hope, quality of life, trust in healthcare system, trust in health professional, preference for research decision control, understanding risks, and information. decision to accept or decline research participation and satisfaction with this decision. All of the factors within the Research Decision Making Model together predicted cancer clinical trial participation and satisfaction with this decision. The most frequently preferred decision-making style for research participation was shared (collaborative) (83%). Multiple factors affect decision making for cancer clinical trial participation and satisfaction with this decision. Shared decision making previously was an unrecognized factor and requires further investigation. Enhancing the process of research decision making may facilitate an increase in cancer clinical trial enrollment rates. Oncology nurses have unique opportunities as educators and researchers to support shared decision making by those who prefer this method for deciding whether to accept or decline cancer clinical trial participation.

Using Five Machine Learning for Breast Cancer Biopsy Predictions Based on Mammographic Diagnosis

OpenAIRE

Oyewola, David; Hakimi, Danladi; Adeboye, Kayode; Shehu, Musa Danjuma

2017-01-01

Breast cancer is one of thecauses of female death in the world. Mammography is commonly used for distinguishing malignant tumors from benign ones. In this research, a mammographic diagnostic method is presented for breast cancer biopsy outcome predictions using fivemachine learning which includes: Logistic Regression(LR), Linear DiscriminantAnalysis(LDA), Quadratic Discriminant Analysis(QDA), Random Forest(RF) andSupport Vector Machine(SVM) classification. The testing result...
Hypoxic Prostate/Muscle PO{sub 2} Ratio Predicts for Outcome in Patients With Localized Prostate Cancer: Long-Term Results

Energy Technology Data Exchange (ETDEWEB)

Turaka, Aruna [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA (United States); Buyyounouski, Mark K., E-mail: mark.buyyounouski@fccc.edu [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA (United States); Hanlon, Alexandra L. [School of Nursing, University of Pennsylvania, Philadelphia, PA (United States); Horwitz, Eric M. [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA (United States); Greenberg, Richard E. [Department of Surgery, Fox Chase Cancer Center, Philadelphia, PA (United States); Movsas, Benjamin [Department of Radiation Oncology, Henry Ford Hospital, Detroit, MI (United States)

2012-03-01

Purpose: To correlate tumor oxygenation status with long-term biochemical outcome after prostate brachytherapy. Methods and Materials: Custom-made Eppendorf PO{sub 2} microelectrodes were used to obtain PO{sub 2} measurements from the prostate (P), focused on positive biopsy locations, and normal muscle tissue (M), as a control. A total of 11,516 measurements were obtained in 57 men with localized prostate cancer immediately before prostate brachytherapy was given. The Eppendorf histograms provided the median PO{sub 2}, mean PO{sub 2}, and % <5 mm Hg or <10 mm Hg. Biochemical failure (BF) was defined using both the former American Society of Therapeutic Radiation Oncology (ASTRO) (three consecutive raises) and the current Phoenix (prostate-specific antigen nadir + 2 ng/mL) definitions. A Cox proportional hazards regression model evaluated the influence of hypoxia using the P/M mean PO{sub 2} ratio on BF. Results: With a median follow-up time of 8 years, 12 men had ASTRO BF and 8 had Phoenix BF. On multivariate analysis, P/M PO{sub 2} ratio <0.10 emerged as the only significant predictor of ASTRO BF (p = 0.043). Hormonal therapy (p = 0.015) and P/M PO{sub 2} ratio <0.10 (p = 0.046) emerged as the only independent predictors of the Phoenix BF. Kaplan-Meier freedom from BF for P/M ratio <0.10 vs. {>=}0.10 at 8 years for ASTRO BF was 46% vs. 78% (p = 0.03) and for the Phoenix BF was 66% vs. 83% (p = 0.02). Conclusions: Hypoxia in prostate cancer (low mean P/M PO{sub 2} ratio) significantly predicts for poor long-term biochemical outcome, suggesting that novel hypoxic strategies should be investigated.
EMMPRIN is associated with S100A4 and predicts patient outcome in colorectal cancer

Science.gov (United States)

Boye, K; Nesland, J M; Sandstad, B; Haugland Haugen, M; Mælandsmo, G M; Flatmark, K

2012-01-01

Background: Proteolytic enzymes and their regulators have important biological roles in colorectal cancer by stimulating invasion and metastasis, which makes these factors attractive as potential prognostic biomarkers. Methods: The expression of extracellular matrix metalloproteinase inducer (EMMPRIN) was characterised using immunohistochemistry in primary tumours from a cohort of 277 prospectively recruited colorectal cancer patients, and associations with expression of S100A4, clinicopathological parameters and patient outcome were investigated. Results: One hundred and ninety-eight samples (72%) displayed positive membrane staining of the tumour cells, whereas 10 cases (4%) were borderline positive. EMMPRIN expression was associated with shorter metastasis-free, disease-specific and overall survival in both univariate and multivariate analyses. The prognostic impact was largely confined to TNM stage III, and EMMPRIN-negative stage III patients had an excellent prognosis. Furthermore, EMMPRIN was significantly associated with expression of S100A4, and the combined expression of these biomarkers conferred an even poorer prognosis. However, there was no evidence of direct regulation between the two proteins in the colorectal cancer cell lines HCT116 and SW620 in siRNA knockdown experiments. Conclusion: EMMPRIN is a promising prognostic biomarker in colorectal cancer, and our findings suggest that it could be used in the selection of stage III patients for adjuvant therapy. PMID:22782346
Development of an International Prostate Cancer Outcomes Registry.

Science.gov (United States)

Evans, Sue M; Nag, Nupur; Roder, David; Brooks, Andrew; Millar, Jeremy L; Moretti, Kim L; Pryor, David; Skala, Marketa; McNeil, John J

2016-04-01

To establish a Prostate Cancer Outcomes Registry-Australia and New Zealand (PCOR-ANZ) for monitoring outcomes of prostate cancer treatment and care, in a cost-effective manner. Stakeholders were recruited based on their interest, importance in achieving the monitoring and reporting of clinical practice and patient outcomes, and in amalgamation of existing registries. Each participating jurisdiction is responsible for local governance, site recruitment, data collection, and data transfer into the PCOR-ANZ. To establish each local registry, hospitals and clinicians within a jurisdiction were approached to voluntarily contribute to the registry following relevant ethical approval. Patient contact occurs following notification of prostate cancer through a hospital or pathology report, or from a cancer registry. Patient registration is based on an opt-out model. The PCOR-ANZ is a secure web-based registry adhering to ISO 27001 standards. Based on a standardised minimum data set, information on demographics, diagnosis, treatment, outcomes, and patient reported quality of life, are collected. Eight of nine jurisdictions have agreed to contribute to the PCOR-ANZ. Each jurisdiction has commenced implementation of necessary infrastructure to support rapid rollout. PCOR-ANZ has defined a minimum data set for collection, to enable analysis of key quality indicators that will aid in assessing clinical practice and patient focused outcomes. PCOR-ANZ will provide a useful resource of risk-adjusted evidence-based data to clinicians, hospitals, and decision makers on prostate cancer clinical practice. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.
Correlation of microarray-based breast cancer molecular subtypes and clinical outcomes: implications for treatment optimization

Directory of Open Access Journals (Sweden)

Hsu Hui-Chi

2011-04-01

Full Text Available Abstract Background Optimizing treatment through microarray-based molecular subtyping is a promising method to address the problem of heterogeneity in breast cancer; however, current application is restricted to prediction of distant recurrence risk. This study investigated whether breast cancer molecular subtyping according to its global intrinsic biology could be used for treatment customization. Methods Gene expression profiling was conducted on fresh frozen breast cancer tissue collected from 327 patients in conjunction with thoroughly documented clinical data. A method of molecular subtyping based on 783 probe-sets was established and validated. Statistical analysis was performed to correlate molecular subtypes with survival outcome and adjuvant chemotherapy regimens. Heterogeneity of molecular subtypes within groups sharing the same distant recurrence risk predicted by genes of the Oncotype and MammaPrint predictors was studied. Results We identified six molecular subtypes of breast cancer demonstrating distinctive molecular and clinical characteristics. These six subtypes showed similarities and significant differences from the Perou-Sørlie intrinsic types. Subtype I breast cancer was in concordance with chemosensitive basal-like intrinsic type. Adjuvant chemotherapy of lower intensity with CMF yielded survival outcome similar to those of CAF in this subtype. Subtype IV breast cancer was positive for ER with a full-range expression of HER2, responding poorly to CMF; however, this subtype showed excellent survival when treated with CAF. Reduced expression of a gene associated with methotrexate sensitivity in subtype IV was the likely reason for poor response to methotrexate. All subtype V breast cancer was positive for ER and had excellent long-term survival with hormonal therapy alone following surgery and/or radiation therapy. Adjuvant chemotherapy did not provide any survival benefit in early stages of subtype V patients. Subtype V was
Correlation of microarray-based breast cancer molecular subtypes and clinical outcomes: implications for treatment optimization

International Nuclear Information System (INIS)

Kao, Kuo-Jang; Chang, Kai-Ming; Hsu, Hui-Chi; Huang, Andrew T

2011-01-01

Optimizing treatment through microarray-based molecular subtyping is a promising method to address the problem of heterogeneity in breast cancer; however, current application is restricted to prediction of distant recurrence risk. This study investigated whether breast cancer molecular subtyping according to its global intrinsic biology could be used for treatment customization. Gene expression profiling was conducted on fresh frozen breast cancer tissue collected from 327 patients in conjunction with thoroughly documented clinical data. A method of molecular subtyping based on 783 probe-sets was established and validated. Statistical analysis was performed to correlate molecular subtypes with survival outcome and adjuvant chemotherapy regimens. Heterogeneity of molecular subtypes within groups sharing the same distant recurrence risk predicted by genes of the Oncotype and MammaPrint predictors was studied. We identified six molecular subtypes of breast cancer demonstrating distinctive molecular and clinical characteristics. These six subtypes showed similarities and significant differences from the Perou-Sørlie intrinsic types. Subtype I breast cancer was in concordance with chemosensitive basal-like intrinsic type. Adjuvant chemotherapy of lower intensity with CMF yielded survival outcome similar to those of CAF in this subtype. Subtype IV breast cancer was positive for ER with a full-range expression of HER2, responding poorly to CMF; however, this subtype showed excellent survival when treated with CAF. Reduced expression of a gene associated with methotrexate sensitivity in subtype IV was the likely reason for poor response to methotrexate. All subtype V breast cancer was positive for ER and had excellent long-term survival with hormonal therapy alone following surgery and/or radiation therapy. Adjuvant chemotherapy did not provide any survival benefit in early stages of subtype V patients. Subtype V was consistent with a unique subset of luminal A intrinsic
Outcomes in Lung Cancer: 9-Year Experience From a Tertiary Cancer Center in India

Directory of Open Access Journals (Sweden)

Aditya Navile Murali

2017-10-01

Full Text Available Purpose: Lung cancer is the most common cause of cancer mortality in the world. There are limited studies on survival outcomes of lung cancer in developing countries such as India. This study analyzed the outcomes of patients with lung cancer who underwent treatment at Cancer Institute (WIA, Chennai, India, between 2006 and 2015 to determine survival outcomes and identify prognostic factors. Patients and Methods: In all, 678 patients with lung cancer underwent treatment. Median age was 58 years, and 91% of patients had non–small-cell lung cancer (NSCLC. Testing for epidermal growth factor receptor mutation was performed in 132 of 347 patients and 61 (46% were positive. Results: Median progression-free survival was 6.9 months and overall survival (OS was 7.6 months for patients with NSCLC. Median progression-free survival was 6 months and OS was 7.2 months for patients with small-cell lung cancer. On multivariable analysis, the factors found to be significantly associated with inferior OS in NSCLC included nonadenocarcinoma histology, performance status more than 2, and stage. In small-cell lung cancer, younger age and earlier stage at presentation showed significantly better survival. Conclusion: Our study highlights the challenges faced in treating lung cancer in India. Although median survival in advanced-stage lung cancer is still poor, strategies such as personalized medicine and use of second-line and maintenance chemotherapy may significantly improve the survival in patients with advanced-stage lung cancer in developing countries.
Outcomes in Lung Cancer: 9-Year Experience From a Tertiary Cancer Center in India

Science.gov (United States)

Murali, Aditya Navile; Ganesan, Trivadi S.; Rajendranath, Rejiv; Ganesan, Prasanth; Selvaluxmy, Ganesarajah; Swaminathan, Rajaraman; Sundersingh, Shirley; Krishnamurthy, Arvind; Sagar, Tenali Gnana

2017-01-01

Purpose Lung cancer is the most common cause of cancer mortality in the world. There are limited studies on survival outcomes of lung cancer in developing countries such as India. This study analyzed the outcomes of patients with lung cancer who underwent treatment at Cancer Institute (WIA), Chennai, India, between 2006 and 2015 to determine survival outcomes and identify prognostic factors. Patients and Methods In all, 678 patients with lung cancer underwent treatment. Median age was 58 years, and 91% of patients had non–small-cell lung cancer (NSCLC). Testing for epidermal growth factor receptor mutation was performed in 132 of 347 patients and 61 (46%) were positive. Results Median progression-free survival was 6.9 months and overall survival (OS) was 7.6 months for patients with NSCLC. Median progression-free survival was 6 months and OS was 7.2 months for patients with small-cell lung cancer. On multivariable analysis, the factors found to be significantly associated with inferior OS in NSCLC included nonadenocarcinoma histology, performance status more than 2, and stage. In small-cell lung cancer, younger age and earlier stage at presentation showed significantly better survival. Conclusion Our study highlights the challenges faced in treating lung cancer in India. Although median survival in advanced-stage lung cancer is still poor, strategies such as personalized medicine and use of second-line and maintenance chemotherapy may significantly improve the survival in patients with advanced-stage lung cancer in developing countries. PMID:29094084
Survival among Never-Smokers with Lung Cancer in the Cancer Care Outcomes Research and Surveillance Study.

Science.gov (United States)

Clément-Duchêne, Christelle; Stock, Shannon; Xu, Xiangyan; Chang, Ellen T; Gomez, Scarlett Lin; West, Dee W; Wakelee, Heather A; Gould, Michael K

2016-01-01

Differences in patient characteristics and outcomes have been observed among current, former, and never-smokers with lung cancer, but most prior studies included few never-smokers and were not prospective. We used data from a large, prospective study of lung cancer care and outcomes in the United States to compare characteristics of never-smokers and smokers with lung cancer and to examine survival among the never-smokers. Smoking status at diagnosis was determined by self-report and survival was determined from medical records and cancer registries, with follow-up through June 2010 or later. Cox regression was used to examine the association between smoking and survival, and to identify predictors of survival among never-smokers. Among 3,410 patients with lung cancer diagnosed between September 1, 2003 and October 14, 2005 who completed a baseline patient survey, there were 274 never-smokers (8%), 1,612 former smokers (47%), 1,496 current smokers or smokers who quit recently (44%), and 28 with missing information about smoking status (Never-smokers appeared more likely than former and current/recent smokers to be female and of Asian or Hispanic race/ethnicity, and to have adenocarcinoma histology, fewer comorbidities, private insurance, and higher income and education. Compared with never-smokers, the adjusted hazard of death from any cause was 29% higher among former smokers (hazard ratio, 1.29; 95% confidence interval, 1.08-1.55), and 39% higher among current/recent smokers (hazard ratio, 1.39; 95% confidence interval, 1.16-1.67). Factors predicting worse overall survival among never-smokers included Hispanic ethnicity, severe comorbidity, undifferentiated histology, and regional or distant stage. Never-smoking Hispanics appeared more likely to have regional or advanced disease at diagnosis and less likely to undergo surgical resection, although these differences were not statistically significant. Never-smokers with lung cancer are more likely than ever
The PER (Preoperative Esophagectomy Risk) Score: A Simple Risk Score to Predict Short-Term and Long-Term Outcome in Patients with Surgically Treated Esophageal Cancer.

Science.gov (United States)

Reeh, Matthias; Metze, Johannes; Uzunoglu, Faik G; Nentwich, Michael; Ghadban, Tarik; Wellner, Ullrich; Bockhorn, Maximilian; Kluge, Stefan; Izbicki, Jakob R; Vashist, Yogesh K

2016-02-01

Esophageal resection in patients with esophageal cancer (EC) is still associated with high mortality and morbidity rates. We aimed to develop a simple preoperative risk score for the prediction of short-term and long-term outcomes for patients with EC treated by esophageal resection. In total, 498 patients suffering from esophageal carcinoma, who underwent esophageal resection, were included in this retrospective cohort study. Three preoperative esophagectomy risk (PER) groups were defined based on preoperative functional evaluation of different organ systems by validated tools (revised cardiac risk index, model for end-stage liver disease score, and pulmonary function test). Clinicopathological parameters, morbidity, and mortality as well as disease-free survival (DFS) and overall survival (OS) were correlated to the PER score. The PER score significantly predicted the short-term outcome of patients with EC who underwent esophageal resection. PER 2 and PER 3 patients had at least double the risk of morbidity and mortality compared to PER 1 patients. Furthermore, a higher PER score was associated with shorter DFS (P PER score was identified as an independent predictor of tumor recurrence (hazard ratio [HR] 2.1; P PER score allows preoperative objective allocation of patients with EC into different risk categories for morbidity, mortality, and long-term outcomes. Thus, multicenter studies are needed for independent validation of the PER score.
Predicting death from surgery for lung cancer

DEFF Research Database (Denmark)

O'Dowd, Emma L; Lüchtenborg, Margreet; Baldwin, David R

2016-01-01

OBJECTIVES: Current British guidelines advocate the use of risk prediction scores such as Thoracoscore to estimate mortality prior to radical surgery for non-small cell lung cancer (NSCLC). A recent publication used the National Lung Cancer Audit (NLCA) to produce a score to predict 90day mortali...
Diffusion Weighted MRI as a predictive tool for effect of radiotherapy in locally advanced cervical cancer

DEFF Research Database (Denmark)

Haack, Søren; Tanderup, Kari; Fokdal, Lars

Diffusion weighted MRI has shown great potential in diagnostic cancer imaging and may also have value for monitoring tumor response during radiotherapy. Patients with advanced cervical cancer are treated with external beam radiotherapy followed by brachytherapy. This study evaluates the value of DW......-MRI for predicting outcome of patients with advanced cervical cancer at time of brachytherapy. Volume of hyper-intensity on highly diffusion sensitive images and resulting ADC value for treatment responders and non-responders is compared. The change of ADC and volume of hyper-intensity over time of BT is also...
Expression level of novel tumor suppressor gene FATS is associated with the outcome of node positive breast cancer

Institute of Scientific and Technical Information of China (English)

ZHANG Jun; GU Lin; ZHAO Lu-jun; ZHANG Xi-feng; QIU Li; LI Zheng

2011-01-01

Background Recently, we reported the identification of a previously uncharacterized and evolutionarily conserved gene, fragile-site associated tumor suppressor (FATS), at a frequently deleted region in irradiation (IR)-induced tumors.However, the role of FATS in breast cancer development and its clinical significance has not been defined. The aim of this study was to determine the role of FA7S in breast cancer development and to evaluate its clinical significance in breast cancer.Methods The expression level of FATS mRNA was determined in 106 breast carcinomas and 23 paired normal breast tissues using quantitative real time reverse transcription-polymerase chain reaction (RT-PCR). The relationship between FATS expression and clinicopathological parameters were also analyzed.Results The mRNA level of FATS was down-regulated in breast cancer compared with paired normal tissues. Low expression of FATS was correlated with high nuclear grade. There was a tendency to a favorable outcome for patients with high expression of FATS (P=0.346). However, low expression of FATS was associated with poor outcome of breast cancer patients with node positive (P=0.011). Furthermore, the mRNA level of FATS showed an independent value in predicting the outcome of breast cancer patients with positive lymph nodes.Conclusion FATS is involved in the carcinogenesis and development of breast cancer and could be a potential biomarker and prognostic factor for breast cancer therapy.
Detecting Lung and Colorectal Cancer Recurrence Using Structured Clinical/Administrative Data to Enable Outcomes Research and Population Health Management.

Science.gov (United States)

Hassett, Michael J; Uno, Hajime; Cronin, Angel M; Carroll, Nikki M; Hornbrook, Mark C; Ritzwoller, Debra

2017-12-01

Recurrent cancer is common, costly, and lethal, yet we know little about it in community-based populations. Electronic health records and tumor registries contain vast amounts of data regarding community-based patients, but usually lack recurrence status. Existing algorithms that use structured data to detect recurrence have limitations. We developed algorithms to detect the presence and timing of recurrence after definitive therapy for stages I-III lung and colorectal cancer using 2 data sources that contain a widely available type of structured data (claims or electronic health record encounters) linked to gold-standard recurrence status: Medicare claims linked to the Cancer Care Outcomes Research and Surveillance study, and the Cancer Research Network Virtual Data Warehouse linked to registry data. Twelve potential indicators of recurrence were used to develop separate models for each cancer in each data source. Detection models maximized area under the ROC curve (AUC); timing models minimized average absolute error. Algorithms were compared by cancer type/data source, and contrasted with an existing binary detection rule. Detection model AUCs (>0.92) exceeded existing prediction rules. Timing models yielded absolute prediction errors that were small relative to follow-up time (differences by cancer type and dataset challenged efforts to create 1 common algorithm for all scenarios. Valid and reliable detection of recurrence using big data is feasible. These tools will enable extensive, novel research on quality, effectiveness, and outcomes for lung and colorectal cancer patients and those who develop recurrence.
Thyroid cancer outcomes in Filipino patients.

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Kus, Lukas H; Shah, Manish; Eski, Spiro; Walfish, Paul G; Freeman, Jeremy L

2010-02-01

To compare the outcomes of patients having thyroid cancer among Filipinos vs non-Filipinos. Retrospective medical record review. High-volume tertiary referral center in Toronto, Ontario, Canada. A total of 499 patients with thyroid cancer (36 Filipino and 463 non-Filipino) treated at Mount Sinai Hospital from January 1, 1984, to August 31, 2003, with a minimum 5-year follow-up period and a minimum 1.0-cm tumor size. Patients were identified from a thyroid cancer database. Data on patient, tumor, and treatment factors were collected along with outcomes. The presence of thyroid cancer recurrence, the rate of death from disease, and the time to recurrence. The 2 groups were similar for sex, age, history of head and neck radiation exposure, family history of thyroid cancer, follow-up time, tumor size, tumor pathologic findings, presence of tumor multifocality, stage of primary disease, type of thyroid surgery, use of postoperative radioactive iodine therapy, and use of external beam radiation therapy. Filipino patients experienced a thyroid cancer recurrence rate of 25% compared with 9.5% for non-Filipino patients (odds ratio, 3.20; 95% confidence interval, 1.23-7.49; P = .004). On multivariate analysis, the increased risk of thyroid cancer recurrence persisted for Filipino patients (odds ratio, 6.99; 95% confidence interval, 2.31-21.07; P Filipino patients and non-Filipino patients regarding the rate of death from disease (5.6% vs 1.9%) and the time to recurrence (52.6 vs 53.1 months). Filipino patients have a significantly higher risk of thyroid cancer recurrence compared with non-Filipino patients. However, no significant difference was noted in the time to recurrence or the rate of death from disease. These findings justify a more aggressive initial management and follow-up regimen for Filipino patients with thyroid cancer.
Understanding the relationship between the Centers for Medicare and Medicaid Services' Hospital Compare star rating, surgical case volume, and short-term outcomes after major cancer surgery.

Science.gov (United States)

Kaye, Deborah R; Norton, Edward C; Ellimoottil, Chad; Ye, Zaojun; Dupree, James M; Herrel, Lindsey A; Miller, David C

2017-11-01

Both the Centers for Medicare and Medicaid Services' (CMS) Hospital Compare star rating and surgical case volume have been publicized as metrics that can help patients to identify high-quality hospitals for complex care such as cancer surgery. The current study evaluates the relationship between the CMS' star rating, surgical volume, and short-term outcomes after major cancer surgery. National Medicare data were used to evaluate the relationship between hospital star ratings and cancer surgery volume quintiles. Then, multilevel logistic regression models were fit to examine the association between cancer surgery outcomes and both star rankings and surgical volumes. Lastly, a graphical approach was used to compare how well star ratings and surgical volume predicted cancer surgery outcomes. This study identified 365,752 patients undergoing major cancer surgery for 1 of 9 cancer types at 2,550 hospitals. Star rating was not associated with surgical volume (P cancer surgery outcomes (mortality, complication rate, readmissions, and prolonged length of stay). The adjusted predicted probabilities for 5- and 1-star hospitals were 2.3% and 4.5% for mortality, 39% and 48% for complications, 10% and 15% for readmissions, and 8% and 16% for a prolonged length of stay, respectively. The adjusted predicted probabilities for hospitals with the highest and lowest quintile cancer surgery volumes were 2.7% and 5.8% for mortality, 41% and 55% for complications, 12.2% and 11.6% for readmissions, and 9.4% and 13% for a prolonged length of stay, respectively. Furthermore, surgical volume and the star rating were similarly associated with mortality and complications, whereas the star rating was more highly associated with readmissions and prolonged length of stay. In the absence of other information, these findings suggest that the star rating may be useful to patients when they are selecting a hospital for major cancer surgery. However, more research is needed before these ratings can
Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data

OpenAIRE

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor, Maureen

2014-01-01

We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer risks for a healthy individual are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial i...
Small median tumor diameter at cure threshold (lung cancers in male smokers predicts both chest X-ray and CT screening outcomes in a novel simulation framework.

Science.gov (United States)

Goldwasser, Deborah L; Kimmel, Marek

2013-01-01

The effectiveness of population-wide lung cancer screening strategies depends on the underlying natural course of lung cancer. We evaluate the expected stage distribution in the Mayo CT screening study under an existing simulation model of non-small cell lung cancer (NSCLC) progression calibrated to the Mayo lung project (MLP). Within a likelihood framework, we evaluate whether the probability of 5-year NSCLC survival conditional on tumor diameter at detection depends significantly on screening detection modality, namely chest X-ray and computed tomography. We describe a novel simulation framework in which tumor progression depends on cellular proliferation and mutation within a stem cell compartment of the tumor. We fit this model to randomized trial data from the MLP and produce estimates of the median radiologic size at the cure threshold. We examine the goodness of model fit with respect to radiologic tumor size and 5-year NSCLC survival among incident cancers in both the MLP and Mayo CT studies. An existing model of NSCLC progression under-predicts the number of advanced-stage incident NSCLCs among males in the Mayo CT study (p-value = 0.004). The probability of 5-year NSCLC survival conditional on tumor diameter depends significantly on detection modality (p-value = 0.0312). In our new model, selected solution sets having a median tumor diameter of 16.2-22.1 mm at cure threshold among aggressive NSCLCs predict both MLP and Mayo CT outcomes. We conclude that the median lung tumor diameter at cure threshold among aggressive NSCLCs in male smokers may be small (<20 mm). Copyright © 2012 UICC.
Breast cancer risks and risk prediction models.

Science.gov (United States)

Engel, Christoph; Fischer, Christine

2015-02-01

BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.
Principles for guiding the ONKALO prediction-outcome studies

International Nuclear Information System (INIS)

Andersson, J.; Hudson, J.A.; Anttila, P.; Koskinen, L.; Pitkaenen, P.; Hautojaervi, A.; Wikstroem, L.

2005-09-01

This document provides the necessary foundation for establishing the strategy for the Prediction-Outcome studies currently being conducted by the ONKALO Modelling Task Force (OMTF) during the construction of the ONKALO ramp. These studies relate to the geology, rock mechanics, hydrogeology and hydrogeochemistry. The purpose of the Prediction-Outcome campaign currently underway in the ONKALO ramp tunnel is to optimize Posiva's ability to predict rock conditions ahead of the excavation face. The aim of the work is: to enhance confidence in ability to predict rock conditions in general - and especially for the repository volumes; (later) testing and verification of repository design rules as it would not be possible to make too many additional boreholes in repository volume; and to support the ongoing construction work and make possible the application of the CEIC method. The document also presents current plans for at what stages of the ONKALO construction predictions and outcome assessments will be made as well as current plans for what properties and impacts will be predicted. These plans will evidently be subject to revision during the course of the work. (orig.)

Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

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Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

2016-07-01

The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Depressive symptoms predict head and neck cancer survival: Examining plausible behavioral and biological pathways.

Science.gov (United States)

Zimmaro, Lauren A; Sephton, Sandra E; Siwik, Chelsea J; Phillips, Kala M; Rebholz, Whitney N; Kraemer, Helena C; Giese-Davis, Janine; Wilson, Liz; Bumpous, Jeffrey M; Cash, Elizabeth D

2018-03-01

Head and neck cancers are associated with high rates of depression, which may increase the risk for poorer immediate and long-term outcomes. Here it was hypothesized that greater depressive symptoms would predict earlier mortality, and behavioral (treatment interruption) and biological (treatment response) mediators were examined. Patients (n = 134) reported depressive symptomatology at treatment planning. Clinical data were reviewed at the 2-year follow-up. Greater depressive symptoms were associated with significantly shorter survival (hazard ratio, 0.868; 95% confidence interval [CI], 0.819-0.921; P ratio, 0.865; 95% CI, 0.774-0.966; P = .010), and poorer treatment response (odds ratio, 0.879; 95% CI, 0.803-0.963; P = .005). The poorer treatment response partially explained the depression-survival relation. Other known prognostic indicators did not challenge these results. Depressive symptoms at the time of treatment planning predict overall 2-year mortality. Effects are partly influenced by the treatment response. Depression screening and intervention may be beneficial. Future studies should examine parallel biological pathways linking depression to cancer survival, including endocrine disruption and inflammation. Cancer 2018;124:1053-60. © 2018 American Cancer Society. © 2018 American Cancer Society.
Synuclein gamma predicts poor clinical outcome in colon cancer with normal levels of carcinoembryonic antigen

Directory of Open Access Journals (Sweden)

Xing Xiaofang

2010-07-01

Full Text Available Abstract Background Synuclein gamma (SNCG, initially identified as a breast cancer specific gene, is aberrantly expressed in many different malignant tumors but rarely expressed in matched nonneoplastic adjacent tissues. In this study, we investigated the prognostic potential of SNCG in colon cancer particularly in the patients with normal carcinoembryonic antigen (CEA levels. Methods SNCG levels were assessed immunohistochemically in cancer tissues from 229 colon adenocarcinoma patients with a mean follow-up of 44 months. Correlations between SNCG levels and clinicopathologic features, preoperative serum CEA level, and clinical outcome were analyzed statistically using SPSS. Results SNCG levels in colon adenocarcinoma were closely associated with intravascular embolus and tumor recurrence but independent of preoperative serum CEA levels. SNCG expression was an independent prognostic factor of a shorter disease-free survival (DFS and overall survival (OS (P P = 0.001, P = 0.001, 0.002 for 97 patients with normal preoperative serum CEA level. Conclusions Our results suggest for the first time that SNCG is a new independent predicator for poor prognosis in patients with colon adenocarcinoma, including those with normal CEA levels. Combination of CEA with SNCG improves prognostic evaluation for patients with colon adenocarcinoma.
Colorectal Cancer: Late Presentation and Outcome of Treatment ...

African Journals Online (AJOL)

Background: Colorectal cancer remains a major health problem especially in developed countries where it ranks as the third most common cause of cancer in both men and women. Though incidence of colorectal cancer is low in Nigeria and other developing countries, outcome of treatment remains poor due largely to late ...
Identification of a claudin-4 and E-cadherin score to predict prognosis in breast cancer.

Science.gov (United States)

Szasz, Attila M; Nemeth, Zsuzsanna; Gyorffy, Balazs; Micsinai, Mariann; Krenacs, Tibor; Baranyai, Zsolt; Harsanyi, Laszlo; Kiss, Andras; Schaff, Zsuzsa; Tokes, Anna-Maria; Kulka, Janina

2011-12-01

The elevated expression of claudins (CLDN) and E-cadherin (CDH-1) was found to correlate with poor prognostic features. Our aim was to perform a comprehensive analysis to assess their potential to predict prognosis in breast cancer. The expression of CLDN-1, -3-5, -7, -8, -10, -15, -18, and E-cadherin at the mRNA level was evaluated in correlation with survival in datasets containing expression measurements of 1809 breast cancer patients. The breast cancer tissues of 197 patients were evaluated with tissue microarray technique and immunohistochemical method for CLDN-1-5, -7, and E-cadherin protein expression. An additional validation set of 387 patients was used to test the accuracy of the resulting prognostic score. Based on the bioinformatic screening of publicly-available datasets, the metagene of CLDN-3, -4, -7, and E-cadherin was shown to have the most powerful predictive power in the survival analyses. An immunohistochemical protein profile consisting of CLDN-2, -4, and E-cadherin was able to predict outcome in the most effective manner in the training set. Combining the overlapping members of the above two methods resulted in the claudin-4 and E-cadherin score (CURIO), which was able to accurately predict relapse-free survival in the validation cohort (P = 0.029). The multivariate analysis, including clinicopathological variables and the CURIO, showed that the latter kept its predictive power (P = 0.040). Furthermore, the CURIO was able to further refine prognosis, separating good versus poor prognosis subgroups in luminal A, luminal B, and triple-negative breast cancer intrinsic subtypes. In breast cancer, the CURIO provides additional prognostic information besides the routinely utilized diagnostic approaches and factors. © 2011 Japanese Cancer Association.
Predictive Biomarkers of Radiation Sensitivity in Rectal Cancer

Science.gov (United States)

Tut, Thein Ga

repair (MMR) proteins, the insufficiency of which is characteristic of CRCs with microsatellite instability (MSI). MSI may enable unlimited replicative potential of malignant cell that leads to radiation injury resistance. Therefore, these proteins were characterized in both CRC cell lines (MMR proteins) and different (core and invasive front) rectal cancer tissues (Plk1, gammaH2AX and MMR proteins) exposed to radiation. Histopathological grading of tumour regression was performed following radiotherapy in rectal cancer as a marker of radiotherapy response and a surrogate indicator of patient prognosis. Though MMR protein expressions correlated with improved in vitro cell survival following radiation, these findings could only be partially replicated in patient tissue samples. This may not be entirely unexpected, given intratumoural heterogeneity in genetic profiles and oxygenation between individual cancer cells, their interaction with stromal environment and a multitude of other factors that cannot be adequately replicated in cell line experiments. In our rectal cancer patient cohort, histopathological regression following radiotherapy did appear to correlate with better clinical outcome, but certainly no replacement for the routine pTNM staging with which it was compared. Overexpression of Plk1 in the primary rectal cancer also correlates with poor tumour regression and reduced overall survival. High level of gammaH2AX correlates with higher tumour stage, perineural invasion and vascular invasion. However, interpretation of the results is limited by the small number of positivity amongst the cohort, with respect to gammaH2AX and MMR proteins. The combined analysis of all the proteins examined in this thesis revealed no interactions, possibly suggesting these biomarkers act individually within the DDR pathway, rather than in a demonstrably interdependent manner. Though our results are mixed, finding biomarkers predictive of radiation response is nonetheless critical
Nomograms Predicting Response to Therapy and Outcomes After Bladder-Preserving Trimodality Therapy for Muscle-Invasive Bladder Cancer

Energy Technology Data Exchange (ETDEWEB)

Coen, John J., E-mail: jcoen@harthosp.org [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Paly, Jonathan J.; Niemierko, Andrzej [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Kaufman, Donald S. [Department of Medical Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Heney, Niall M. [Department of Urology, Massachusetts General Hospital, Boston, Massachusetts (United States); Spiegel, Daphne Y.; Efstathiou, Jason A.; Zietman, Anthony L.; Shipley, William U. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)

2013-06-01

Purpose: Selective bladder preservation by use of trimodality therapy is an established management strategy for muscle-invasive bladder cancer. Individual disease features have been associated with response to therapy, likelihood of bladder preservation, and disease-free survival. We developed prognostic nomograms to predict the complete response rate, disease-specific survival, and likelihood of remaining free of recurrent bladder cancer or cystectomy. Methods and Materials: From 1986 to 2009, 325 patients were managed with selective bladder preservation at Massachusetts General Hospital (MGH) and had complete data adequate for nomogram development. Treatment consisted of a transurethral resection of bladder tumor followed by split-course chemoradiation. Patients with a complete response at midtreatment cystoscopic assessment completed radiation, whereas those with a lesser response underwent a prompt cystectomy. Prognostic nomograms were constructed predicting complete response (CR), disease-specific survival (DSS), and bladder-intact disease-free survival (BI-DFS). BI-DFS was defined as the absence of local invasive or regional recurrence, distant metastasis, bladder cancer-related death, or radical cystectomy. Results: The final nomograms included information on clinical T stage, presence of hydronephrosis, whether a visibly complete transurethral resection of bladder tumor was performed, age, sex, and tumor grade. The predictive accuracy of these nomograms was assessed. For complete response, the area under the receiving operating characteristic curve was 0.69. The Harrell concordance index was 0.61 for both DSS and BI-DFS. Conclusions: Our nomograms allow individualized estimates of complete response, DSS, and BI-DFS. They may assist patients and clinicians making important treatment decisions.
Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer.

Science.gov (United States)

Petersen, Japke F; Stuiver, Martijn M; Timmermans, Adriana J; Chen, Amy; Zhang, Hongzhen; O'Neill, James P; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T; Koch, Wayne; van den Brekel, Michiel W M

2018-05-01

TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442 patients with T3T4N0N+M0 larynx cancer. The model was internally validated using bootstrapping samples and externally validated on patient data from five external centers (n = 770). The main outcome was performance of the model as tested by discrimination, calibration, and the ability to distinguish risk groups based on tertiles from the derivation dataset. The model performance was compared to a model based on T and N classification only. We included age, gender, T and N classification, and subsite as prognostic variables in the standard model. After external validation, the standard model had a significantly better fit than a model based on T and N classification alone (C statistic, 0.59 vs. 0.55, P statistic to 0.68. A risk prediction model for patients with advanced larynx cancer, consisting of readily available clinical variables, gives more accurate estimations of the estimated 5-year survival rate when compared to a model based on T and N classification alone. 2c. Laryngoscope, 128:1140-1145, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.
Outcome of severe infections in afebrile neutropenic cancer patients

Science.gov (United States)

Mahkovic-Hergouth, Ksenija; Novakovic, Barbara Jezersek; Seruga, Bostjan

2016-01-01

Abstract Background In some neutropenic cancer patients fever may be absent despite microbiologically and/or clinically confirmed infection. We hypothesized that afebrile neutropenic cancer patients with severe infections have worse outcome as compared to cancer patients with febrile neutropenia. Patients and methods We retrospectively analyzed all adult cancer patients with chemotherapy-induced neutropenia and severe infection, who were admitted to the Intensive Care Unit at our cancer center between 2000 and 2011. The outcome of interest was 30-day in-hospital mortality rate. Association between the febrile status and in-hospital mortality rate was evaluated by the Fisher’s exact test. Results We identified 69 episodes of severe neutropenic infections in 65 cancer patients. Among these, 9 (13%) episodes were afebrile. Patients with afebrile neutropenic infection presented with hypotension, severe fatigue with inappetence, shaking chills, altered mental state or cough and all of them eventually deteriorated to severe sepsis or septic shock. Overall 30-day in-hospital mortality rate was 55.1%. Patients with afebrile neutropenic infection had a trend for a higher 30-day in-hospital mortality rate as compared to patients with febrile neutropenic infection (78% vs. 52%, p = 0.17). Conclusions Afebrile cancer patients with chemotherapy-induced neutropenia and severe infections might have worse outcome as compared to cancer patients with febrile neutropenia. Patients should be informed that severe neutropenic infection without fever can occasionally occur during cancer treatment with chemotherapy. PMID:27904453
Workload and surgeon's specialty for outcome after colorectal cancer surgery

DEFF Research Database (Denmark)

Archampong, David; Borowski, David; Wille-Jørgensen, Peer

2012-01-01

A large body of research has focused on investigating the effects of healthcare provider volume and specialization on patient outcomes including outcomes of colorectal cancer surgery. However there is conflicting evidence about the role of such healthcare provider characteristics in the management...... of colorectal cancer....
Outcome of Laparoscopic Versus Open Resection for Transverse Colon Cancer.

Science.gov (United States)

Zeng, Wei-Gen; Liu, Meng-Jia; Zhou, Zhi-Xiang; Hou, Hui-Rong; Liang, Jian-Wei; Wang, Zheng; Zhang, Xing-Mao; Hu, Jun-Jie

2015-10-01

Laparoscopic resection for transverse colon cancer remains controversial. The aim of this study is to investigate the short- and long-term outcomes of laparoscopic surgery for transverse colon cancer. A total of 278 patients with transverse colon cancer from a single institution were included. All patients underwent curative surgery, 156 patients underwent laparoscopic resection (LR), and 122 patients underwent open resection (OR). The short- and long-term results were compared between two groups. Baseline demographic and clinical characteristics were comparable between two groups. Conversions were required in eight (5.1 %) patients. LR group was associated with significantly longer median operating time (180 vs. 140 min; P colon cancer is associated with better short-term outcomes and equivalent long-term oncologic outcomes.
The prediction of breast cancer biopsy outcomes using two CAD approaches that both emphasize an intelligible decision process

International Nuclear Information System (INIS)

Elter, M.; Schulz-Wendtland, R.; Wittenberg, T.

2007-01-01

Mammography is the most effective method for breast cancer screening available today. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approximately 70% unnecessary biopsies with benign outcomes. To reduce the high number of unnecessary breast biopsies, several computer-aided diagnosis (CAD) systems have been proposed in the last several years. These systems help physicians in their decision to perform a breast biopsy on a suspicious lesion seen in a mammogram or to perform a short term follow-up examination instead. We present two novel CAD approaches that both emphasize an intelligible decision process to predict breast biopsy outcomes from BI-RADS findings. An intelligible reasoning process is an important requirement for the acceptance of CAD systems by physicians. The first approach induces a global model based on decison-tree learning. The second approach is based on case-based reasoning and applies an entropic similarity measure. We have evaluated the performance of both CAD approaches on two large publicly available mammography reference databases using receiver operating characteristic (ROC) analysis, bootstrap sampling, and the ANOVA statistical significance test. Both approaches outperform the diagnosis decisions of the physicians. Hence, both systems have the potential to reduce the number of unnecessary breast biopsies in clinical practice. A comparison of the performance of the proposed decision tree and CBR approaches with a state of the art approach based on artificial neural networks (ANN) shows that the CBR approach performs slightly better than the ANN approach, which in turn results in slightly better performance than the decision-tree approach. The differences are statistically significant (p value <0.001). On 2100 masses extracted from the DDSM database, the CRB approach for example resulted in an area under the ROC curve of A(z)=0.89±0.01, the decision-tree approach in A(z)=0.87±0
Predictive model for survival in patients with gastric cancer.

Science.gov (United States)

Goshayeshi, Ladan; Hoseini, Benyamin; Yousefli, Zahra; Khooie, Alireza; Etminani, Kobra; Esmaeilzadeh, Abbas; Golabpour, Amin

2017-12-01

Gastric cancer is one of the most prevalent cancers in the world. Characterized by poor prognosis, it is a frequent cause of cancer in Iran. The aim of the study was to design a predictive model of survival time for patients suffering from gastric cancer. This was a historical cohort conducted between 2011 and 2016. Study population were 277 patients suffering from gastric cancer. Data were gathered from the Iranian Cancer Registry and the laboratory of Emam Reza Hospital in Mashhad, Iran. Patients or their relatives underwent interviews where it was needed. Missing values were imputed by data mining techniques. Fifteen factors were analyzed. Survival was addressed as a dependent variable. Then, the predictive model was designed by combining both genetic algorithm and logistic regression. Matlab 2014 software was used to combine them. Of the 277 patients, only survival of 80 patients was available whose data were used for designing the predictive model. Mean ?SD of missing values for each patient was 4.43?.41 combined predictive model achieved 72.57% accuracy. Sex, birth year, age at diagnosis time, age at diagnosis time of patients' family, family history of gastric cancer, and family history of other gastrointestinal cancers were six parameters associated with patient survival. The study revealed that imputing missing values by data mining techniques have a good accuracy. And it also revealed six parameters extracted by genetic algorithm effect on the survival of patients with gastric cancer. Our combined predictive model, with a good accuracy, is appropriate to forecast the survival of patients suffering from Gastric cancer. So, we suggest policy makers and specialists to apply it for prediction of patients' survival.
Prediction Model for Gastric Cancer Incidence in Korean Population.

Directory of Open Access Journals (Sweden)

Bang Wool Eom

Full Text Available Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea.Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell's C-statistics, and the calibration was evaluated using a calibration plot and slope.During a median of 11.4 years of follow-up, 19,465 (1.4% and 5,579 (0.7% newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women.In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance.
Cancer Outcomes in Low-Income Elders

Data.gov (United States)

U.S. Department of Health & Human Services — Cancer Outcomes in Low-Income Elders, Is There An Advantage to Being on Medicaid Because of reduced financial barriers, dual Medicare-Medicaid enrollment of...
Outcome of severe infections in afebrile neutropenic cancer patients

Directory of Open Access Journals (Sweden)

Strojnik Ksenija

2016-12-01

Full Text Available In some neutropenic cancer patients fever may be absent despite microbiologically and/or clinically confirmed infection. We hypothesized that afebrile neutropenic cancer patients with severe infections have worse outcome as compared to cancer patients with febrile neutropenia.
Discrimination measures for survival outcomes: connection between the AUC and the predictiveness curve.

Science.gov (United States)

Viallon, Vivian; Latouche, Aurélien

2011-03-01

Finding out biomarkers and building risk scores to predict the occurrence of survival outcomes is a major concern of clinical epidemiology, and so is the evaluation of prognostic models. In this paper, we are concerned with the estimation of the time-dependent AUC--area under the receiver-operating curve--which naturally extends standard AUC to the setting of survival outcomes and enables to evaluate the discriminative power of prognostic models. We establish a simple and useful relation between the predictiveness curve and the time-dependent AUC--AUC(t). This relation confirms that the predictiveness curve is the key concept for evaluating calibration and discrimination of prognostic models. It also highlights that accurate estimates of the conditional absolute risk function should yield accurate estimates for AUC(t). From this observation, we derive several estimators for AUC(t) relying on distinct estimators of the conditional absolute risk function. An empirical study was conducted to compare our estimators with the existing ones and assess the effect of model misspecification--when estimating the conditional absolute risk function--on the AUC(t) estimation. We further illustrate the methodology on the Mayo PBC and the VA lung cancer data sets. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Prostate-specific antigen for pretreatment prediction and posttreatment evaluation of outcome after definitive irradiation for prostate cancer

Energy Technology Data Exchange (ETDEWEB)

Kuban, Deborah A; El-Mahdi, Anas M; Schellhammer, Paul F

1995-05-15

Purpose: This study was undertaken to assess the predictive value of pretreatment prostate-specific antigen (PSA) and the difference between clinical and PSA disease-free status in patients with long-term follow-up after irradiation for prostatic carcinoma. Comparison of the distribution of prognostic factors between surgical and radiation series was also made. Methods and Materials: From 1975-1989, 652 patients with clinical Stage A2-C prostatic adenocarcinoma were definitively irradiated using external beam therapy. One hundred and fifty patients with banked serum and up to 14 years follow-up have pretreatment PSA levels and 355 patients with up to 17 years follow-up have posttreatment values. Treatment failure was analyzed by tumor stage, grade, and four pretreatment PSA categories. Disease-progression was evaluated by clinical and biochemical (PSA) endpoints. Prognostic factors were compared to two surgical series. Results: A significant difference was seen in clinical and PSA disease-free (PSA {<=} 4.0 ng/ml) status based on tumor grade, stage, and pretreatment PSA category. Although the expected clinical outcome has been well-documented previously, results based on posttreatment PSA levels show 5-year disease-free survivals reduced by 10-16% and 10-year survivals lessened by 15-39% depending upon the particular tumor grade and stage. The earlier stage, lower grade tumors showed the largest difference between clinical and biochemical recurrence rates at the longest interval from treatment. Even more notable were the differences in the clinical and PSA disease-free rates based on the pretreatment PSA level. Comparing the irradiated patients to two surgical series showed that the former had a larger percentage of more advanced stage tumors with more unfavorable PSA levels as compared to prostatectomy patients. Conclusion: With long-term follow-up, the pretreatment PSA level continues to be a powerful predictor of clinical and biochemical outcome in patients
Observed and Predicted Risk of Breast Cancer Death in Randomized Trials on Breast Cancer Screening.

Science.gov (United States)

Autier, Philippe; Boniol, Mathieu; Smans, Michel; Sullivan, Richard; Boyle, Peter

2016-01-01

The role of breast screening in breast cancer mortality declines is debated. Screening impacts cancer mortality through decreasing the number of advanced cancers with poor diagnosis, while cancer treatment works through decreasing the case-fatality rate. Hence, reductions in cancer death rates thanks to screening should directly reflect reductions in advanced cancer rates. We verified whether in breast screening trials, the observed reductions in the risk of breast cancer death could be predicted from reductions of advanced breast cancer rates. The Greater New York Health Insurance Plan trial (HIP) is the only breast screening trial that reported stage-specific cancer fatality for the screening and for the control group separately. The Swedish Two-County trial (TCT)) reported size-specific fatalities for cancer patients in both screening and control groups. We computed predicted numbers of breast cancer deaths, from which we calculated predicted relative risks (RR) and (95% confidence intervals). The Age trial in England performed its own calculations of predicted relative risk. The observed and predicted RR of breast cancer death were 0.72 (0.56-0.94) and 0.98 (0.77-1.24) in the HIP trial, and 0.79 (0.78-1.01) and 0.90 (0.80-1.01) in the Age trial. In the TCT, the observed RR was 0.73 (0.62-0.87), while the predicted RR was 0.89 (0.75-1.05) if overdiagnosis was assumed to be negligible and 0.83 (0.70-0.97) if extra cancers were excluded. In breast screening trials, factors other than screening have contributed to reductions in the risk of breast cancer death most probably by reducing the fatality of advanced cancers in screening groups. These factors were the better management of breast cancer patients and the underreporting of breast cancer as the underlying cause of death. Breast screening trials should publish stage-specific fatalities observed in each group.
Early prostate cancer antigen expression in predicting presence of prostate cancer in men with histologically negative biopsies.

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Hansel, D E; DeMarzo, A M; Platz, E A; Jadallah, S; Hicks, J; Epstein, J I; Partin, A W; Netto, G J

2007-05-01

Early prostate cancer antigen is a nuclear matrix protein that was recently shown to be expressed in prostate adenocarcinoma and adjacent benign tissue. Previous studies have demonstrated early prostate cancer antigen expression in benign prostate tissue up to 5 years before a diagnosis of prostate carcinoma, suggesting that early prostate cancer antigen could be used as a potential predictive marker. We evaluated early prostate cancer antigen expression by immunohistochemistry using a polyclonal antibody (Onconome Inc., Seattle, Washington) on benign biopsies from 98 patients. Biopsies were obtained from 4 groups that included 39 patients with first time negative biopsy (group 1), 24 patients with persistently negative biopsies (group 2), 8 patients with initially negative biopsies who were subsequently diagnosed with prostate carcinoma (group 3) and negative biopsies obtained from 27 cases where other concurrent biopsies contained prostate carcinoma (group 4). Early prostate cancer antigen staining was assessed by 2 of the authors who were blind to the group of the examined sections. Staining intensity (range 0 to 3) and extent (range 1 to 3) scores were assigned. The presence of intensity 3 staining in any of the blocks of a biopsy specimen was considered as positive for early prostate cancer antigen for the primary outcome in the statistical analysis. In addition, as secondary outcomes we evaluated the data using the proportion of blocks with intensity 3 early prostate cancer antigen staining, the mean of the product of staining intensity and staining extent of all blocks within a biopsy, and the mean of the product of intensity 3 staining and extent. Primary outcome analysis revealed the proportion of early prostate cancer antigen positivity to be highest in group 3 (6 of 8, 75%) and lowest in group 2 (7 of 24, 29%, p=0.04 for differences among groups). A relatively higher than expected proportion of early prostate cancer antigen positivity was present in

Surgical and pathological outcomes of laparoscopic surgery for transverse colon cancer.

Science.gov (United States)

Lee, Y S; Lee, I K; Kang, W K; Cho, H M; Park, J K; Oh, S T; Kim, J G; Kim, Y H

2008-07-01

Several multi-institutional prospective randomized trials have demonstrated short-term benefits using laparoscopy. Now the laparoscopic approach is accepted as an alternative to open surgery for colon cancer. However, in prior trials, the transverse colon was excluded. Therefore, it has not been determined whether laparoscopy can be used in the setting of transverse colon cancer. This study evaluated the peri-operative clinical outcomes and oncological quality by pathologic outcomes of laparoscopic surgery for transverse colon cancer. Analysis of the medical records of patients who underwent laparoscopic colorectal resection from August 2004 to November 2007 was made. Computed tomography, barium enema, and colonoscopy were performed to localize the tumor preoperatively. Extended right hemicolectomy, transverse colectomy, and extended left hemicolectomy were performed for transverse colon cancer. Surgical outcomes and pathologic outcomes were compared between transverse colon cancer (TCC) and other site colon cancer (OSCC). Of the 312 colorectal cancer patients, 94 patients underwent laparoscopic surgery for OSCC, and 34 patients underwent laparoscopic surgery for TCC. Patients with TCC were similar to patients with OSCC in age, gender, body mass index, operating time, blood loss, time to pass flatus, start of diet, hospital stay, tumor size, distal resection margin, proximal resection margin, number of lymph nodes, and radial margin. One case in TCC and three cases in OSCC were converted to open surgery. Laparoscopic surgery for transverse colon cancer and OSCC had similar peri-operative clinical and acceptable pathological outcomes.
Myopodin methylation is a prognostic biomarker and predicts antiangiogenic response in advanced kidney cancer.

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Pompas-Veganzones, N; Sandonis, V; Perez-Lanzac, Alberto; Beltran, M; Beardo, P; Juárez, A; Vazquez, F; Cozar, J M; Alvarez-Ossorio, J L; Sanchez-Carbayo, Marta

2016-10-01

Myopodin is a cytoskeleton protein that shuttles to the nucleus depending on the cellular differentiation and stress. It has shown tumor suppressor functions. Myopodin methylation status was useful for staging bladder and colon tumors and predicting clinical outcome. To our knowledge, myopodin has not been tested in kidney cancer to date. The purpose of this study was to evaluate whether myopodin methylation status could be clinically useful in renal cancer (1) as a prognostic biomarker and 2) as a predictive factor of response to antiangiogenic therapy in patients with metastatic disease. Methylation-specific polymerase chain reactions (MS-PCR) were used to evaluate myopodin methylation in 88 kidney tumors. These belonged to patients with localized disease and no evidence of disease during follow-up (n = 25) (group 1), and 63 patients under antiangiogenic therapy (sunitinib, sorafenib, pazopanib, and temsirolimus), from which group 2 had non-metastatic disease at diagnosis (n = 32), and group 3 showed metastatic disease at diagnosis (n = 31). Univariate and multivariate Cox analyses were utilized to assess outcome and response to antiangiogenic agents taking progression, disease-specific survival, and overall survival as clinical endpoints. Myopodin was methylated in 50 out of the 88 kidney tumors (56.8 %). Among the 88 cases analyzed, 10 of them recurred (11.4 %), 51 progressed (57.9 %), and 40 died of disease (45.4 %). Myopodin methylation status correlated to MSKCC Risk score (p = 0.050) and the presence of distant metastasis (p = 0.039). Taking all patients, an unmethylated myopodin identified patients with shorter progression-free survival, disease-specific survival, and overall survival. Using also in univariate and multivariate models, an unmethylated myopodin predicted response to antiangiogenic therapy (groups 2 and 3) using progression-free survival, disease-specific, and overall survival as clinical endpoints. Myopodin was revealed
The Singapore Liver Cancer Recurrence (SLICER Score for relapse prediction in patients with surgically resected hepatocellular carcinoma.

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Soo Fan Ang

Full Text Available Surgery is the primary curative option in patients with hepatocellular carcinoma (HCC. Current prognostic models for HCC are developed on datasets of primarily patients with advanced cancer, and may be less relevant to resectable HCC. We developed a postoperative nomogram, the Singapore Liver Cancer Recurrence (SLICER Score, to predict outcomes of HCC patients who have undergone surgical resection.Records for 544 consecutive patients undergoing first-line curative surgery for HCC in one institution from 1992-2007 were reviewed, with 405 local patients selected for analysis. Freedom from relapse (FFR was the primary outcome measure. An outcome-blinded modeling strategy including clustering, data reduction and transformation was used. We compared the performance of SLICER in estimating FFR with other HCC prognostic models using concordance-indices and likelihood analysis.A nomogram predicting FFR was developed, incorporating non-neoplastic liver cirrhosis, multifocality, preoperative alpha-fetoprotein level, Child-Pugh score, vascular invasion, tumor size, surgical margin and symptoms at presentation. Our nomogram outperformed other HCC prognostic models in predicting FFR by means of log-likelihood ratio statistics with good calibration demonstrated at 3 and 5 years post-resection and a concordance index of 0.69. Using decision curve analysis, SLICER also demonstrated superior net benefit at higher threshold probabilities.The SLICER score enables well-calibrated individualized predictions of relapse following curative HCC resection, and may represent a novel tool for biomarker research and individual counseling.
Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome

International Nuclear Information System (INIS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; Moore, Kathleen; Liu, Hong; Zheng, Bin

2016-01-01

To investigate the feasibility of automated segmentation of visceral and subcutaneous fat areas from computed tomography (CT) images of ovarian cancer patients and applying the computed adiposity-related image features to predict chemotherapy outcome. A computerized image processing scheme was developed to segment visceral and subcutaneous fat areas, and compute adiposity-related image features. Then, logistic regression models were applied to analyze association between the scheme-generated assessment scores and progression-free survival (PFS) of patients using a leave-one-case-out cross-validation method and a dataset involving 32 patients. The correlation coefficients between automated and radiologist’s manual segmentation of visceral and subcutaneous fat areas were 0.76 and 0.89, respectively. The scheme-generated prediction scores using adiposity-related radiographic image features significantly associated with patients’ PFS (p < 0.01). Using a computerized scheme enables to more efficiently and robustly segment visceral and subcutaneous fat areas. The computed adiposity-related image features also have potential to improve accuracy in predicting chemotherapy outcome
Review of the quality of total mesorectal excision does not improve the prediction of outcome.

Science.gov (United States)

Demetter, P; Jouret-Mourin, A; Silversmit, G; Vandendael, T; Sempoux, C; Hoorens, A; Nagy, N; Cuvelier, C; Van Damme, N; Penninckx, F

2016-09-01

A fair to moderate concordance in grading of the total mesorectal excision (TME) surgical specimen by local pathologists and a central review panel has been observed in the PROCARE (Project on Cancer of the Rectum) project. The aim of the present study was to evaluate the difference, if any, in the accuracy of predicting the oncological outcome through TME grading by local pathologists or by the review panel. The quality of the TME specimen was reviewed for 482 surgical specimens registered on a prospective database between 2006 and 2011. Patients with a Stage IV tumour, with unknown incidence date or without follow-up information were excluded, resulting in a study population of 383 patients. Quality assessment of the specimen was based on three grades including mesorectal resection (MRR), intramesorectal resection (IMR) and muscularis propria resection (MPR). Using univariable Cox regression models, local and review panel histopathological gradings of the quality of TME were assessed as predictors of local recurrence, distant metastasis and disease-free and overall survival. Differences in the predictions between local and review grading were determined. Resection planes were concordant in 215 (56.1%) specimens. Downgrading from MRR to MPR was noted in 23 (6.0%). There were no significant differences in the prediction error between the two models; local and central review TME grading predicted the outcome equally well. Any difference in grading of the TME specimen between local histopathologists and the review panel had no significant impact on the prediction of oncological outcome for this patient cohort. Grading of the quality of TME as reported by local histopathologists can therefore be used for outcome analysis. Quality control of TME grading is not warranted provided the histopathologist is adequately trained. Colorectal Disease © 2016 The Association of Coloproctology of Great Britain and Ireland.
Clinical Outcomes of Colorectal Cancer in Kenya | Saidi | Annals of ...

African Journals Online (AJOL)

Background The incidence of colorectal cancer in Africa is increasing. True data on clinical outcomes of the disease is hampered by follow up challenges. Method Follow up data of 233 patients treated for colorectal cancer between 2005 and 2010 at various Nairobi hospitals were evaluated. The primary outcome was ...
Concurrent Preoperative Presence of Hydronephrosis and Flank Pain Independently Predicts Worse Outcome of Upper Tract Urothelial Carcinoma.

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Yeh, Hsin-Chih; Jan, Hau-Chern; Wu, Wen-Jeng; Li, Ching-Chia; Li, Wei-Ming; Ke, Hung-Lung; Huang, Shu-Pin; Liu, Chia-Chu; Lee, Yung-Chin; Yang, Sheau-Fang; Liang, Peir-In; Huang, Chun-Nung

2015-01-01

To investigate the impact of preoperative hydronephrosis and flank pain on prognosis of patients with upper tract urothelial carcinoma. In total, 472 patients with upper tract urothelial carcinoma managed by radical nephroureterectomy were included from Kaohsiung Medical University Hospital Healthcare System. Clinicopathological data were collected retrospectively for analysis. The significance of hydronephrosis, especially when combined with flank pain, and other relevant factors on overall and cancer-specific survival were evaluated. Of the 472 patients, 292 (62%) had preoperative hydronephrosis and 121 (26%) presented with flank pain. Preoperative hydronephrosis was significantly associated with age, hematuria, flank pain, tumor location, and pathological tumor stage. Concurrent presence of hydronephrosis and flank pain was a significant predictor of non-organ-confined disease (multivariate-adjusted hazard ratio = 2.10, P = 0.025). Kaplan-Meier analysis showed significantly poorer overall and cancer-specific survival in patients with preoperative hydronephrosis (P = 0.005 and P = 0.026, respectively) and in patients with flank pain (P hydronephrosis and flank pain independently predicted adverse outcome (hazard ratio = 1.98, P = 0.016 for overall survival and hazard ratio = 1.87, P = 0.036 for and cancer-specific survival, respectively) in multivariate Cox proportional hazards models. In addition, concurrent presence of hydronephrosis and flank pain was also significantly predictive of worse survival in patient with high grade or muscle-invasive disease. Notably, there was no difference in survival between patients with hydronephrosis but devoid of flank pain and those without hydronephrosis. Concurrent preoperative presence of hydronephrosis and flank pain predicted non-organ-confined status of upper tract urothelial carcinoma. When accompanied with flank pain, hydronephrosis represented an independent predictor for worse outcome in patients with upper tract
Outcome Prediction after Radiotherapy with Medical Big Data.

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Magome, Taiki

2016-01-01

Data science is becoming more important in many fields. In medical physics field, we are facing huge data every day. Treatment outcomes after radiation therapy are determined by complex interactions between clinical, biological, and dosimetrical factors. A key concept of recent radiation oncology research is to predict the outcome based on medical big data for personalized medicine. Here, some reports, which are analyzing medical databases with machine learning techniques, were reviewed and feasibility of outcome prediction after radiation therapy was discussed. In addition, some strategies for saving manual labors to analyze huge data in medical physics were discussed.
Systematic review of outcomes after intersphincteric resection for low rectal cancer.

LENUS (Irish Health Repository)

Martin, S T

2012-05-01

For a select group of patients proctectomy with intersphincteric resection (ISR) for low rectal cancer may be a viable alternative to abdominoperineal resection, with good oncological outcomes while preserving sphincter function. The purpose of this systematic review was to evaluate the current evidence regarding oncological outcomes, morbidity and mortality, and functional outcomes after ISR for low rectal cancer.
Predicting prostate biopsy outcome: prostate health index (phi) and prostate cancer antigen 3 (PCA3) are useful biomarkers.

Science.gov (United States)

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Marino, Ada; Sorrentino, Alessandra; Di Carlo, Angelina; Autorino, Riccardo; Di Lorenzo, Giuseppe; Buonerba, Carlo; Altieri, Vincenzo; Mariano, Angela; Macchia, Vincenzo; Terracciano, Daniela

2012-08-16

Indication for prostate biopsy is presently mainly based on prostate-specific antigen (PSA) serum levels and digital-rectal examination (DRE). In view of the unsatisfactory accuracy of these two diagnostic exams, research has focused on novel markers to improve pre-biopsy prostate cancer detection, such as phi and PCA3. The purpose of this prospective study was to assess the diagnostic accuracy of phi and PCA3 for prostate cancer using biopsy as gold standard. Phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay) and other established biomarkers (tPSA, fPSA and %fPSA) were assessed before a 18-core prostate biopsy in a group of 251 subjects at their first biopsy. Values of %p2PSA and phi were significantly higher in patients with PCa compared with PCa-negative group (pphi and PCA3 are predictive of malignancy. In conclusion, %p2PSA, phi and PCA3 may predict a diagnosis of PCa in men undergoing their first prostate biopsy. PCA3 score is more useful in discriminating between HGPIN and non-cancer. Copyright © 2012 Elsevier B.V. All rights reserved.
DNA Repair Biomarkers Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer

International Nuclear Information System (INIS)

Alexander, Brian M.; Wang Xiaozhe; Niemierko, Andrzej; Weaver, David T.; Mak, Raymond H.; Roof, Kevin S.; Fidias, Panagiotis; Wain, John; Choi, Noah C.

2012-01-01

Purpose: The addition of neoadjuvant chemoradiotherapy prior to surgical resection for esophageal cancer has improved clinical outcomes in some trials. Pathologic complete response (pCR) following neoadjuvant therapy is associated with better clinical outcome in these patients, but only 22% to 40% of patients achieve pCR. Because both chemotherapy and radiotherapy act by inducing DNA damage, we analyzed proteins selected from multiple DNA repair pathways, using quantitative immunohistochemistry coupled with a digital pathology platform, as possible biomarkers of treatment response and clinical outcome. Methods and Materials: We identified 79 patients diagnosed with esophageal cancer between October 1994 and September 2002, with biopsy tissue available, who underwent neoadjuvant chemoradiotherapy prior to surgery at the Massachusetts General Hospital and used their archived, formalin-fixed, paraffin-embedded biopsy samples to create tissue microarrays (TMA). TMA sections were stained using antibodies against proteins in various DNA repair pathways including XPF, FANCD2, PAR, MLH1, PARP1, and phosphorylated MAPKAP kinase 2 (pMK2). Stained TMA slides were evaluated using machine-based image analysis, and scoring incorporated both the intensity and the quantity of positive tumor nuclei. Biomarker scores and clinical data were assessed for correlations with clinical outcome. Results: Higher scores for MLH1 (p = 0.018) and lower scores for FANCD2 (p = 0.037) were associated with pathologic response to neoadjuvant chemoradiation on multivariable analysis. Staining of MLH1, PARP1, XPF, and PAR was associated with recurrence-free survival, and staining of PARP1 and FANCD2 was associated with overall survival on multivariable analysis. Conclusions: DNA repair proteins analyzed by immunohistochemistry may be useful as predictive markers for response to neoadjuvant chemoradiotherapy in patients with esophageal cancer. These results are hypothesis generating and need
The predictive and prognostic potential of plasma telomerase reverse transcriptase (TERT) RNA in rectal cancer patients

Science.gov (United States)

Rampazzo, Enrica; Del Bianco, Paola; Bertorelle, Roberta; Boso, Caterina; Perin, Alessandro; Spiro, Giovanna; Bergamo, Francesca; Belluco, Claudio; Buonadonna, Angela; Palazzari, Elisa; Leonardi, Sara; De Paoli, Antonino; Pucciarelli, Salvatore; De Rossi, Anita

2018-01-01

Background: Preoperative chemoradiotherapy (CRT) followed by surgery is the standard care for locally advanced rectal cancer, but tumour response to CRT and disease outcome are variable. The current study aimed to investigate the effectiveness of plasma telomerase reverse transcriptase (TERT) levels in predicting tumour response and clinical outcome. Methods: 176 rectal cancer patients were included. Plasma samples were collected at baseline (before CRT=T0), 2 weeks after CRT was initiated (T1), post-CRT and before surgery (T2), and 4–8 months after surgery (T3) time points. Plasma TERT mRNA levels and total cell-free RNA were determined using real-time PCR. Results: Plasma levels of TERT were significantly lower at T2 (P<0.0001) in responders than in non-responders. Post-CRT TERT levels and the differences between pre- and post-CRT TERT levels independently predicted tumour response, and the prediction model had an area under curve of 0.80 (95% confidence interval (CI) 0.73–0.87). Multiple analysis demonstrated that patients with detectable TERT levels at T2 and T3 time points had a risk of disease progression 2.13 (95% CI 1.10–4.11)-fold and 4.55 (95% CI 1.48–13.95)-fold higher, respectively, than those with undetectable plasma TERT levels. Conclusions: Plasma TERT levels are independent markers of tumour response and are prognostic of disease progression in rectal cancer patients who undergo neoadjuvant therapy. PMID:29449673
Preoperative cancer cachexia and short-term outcomes following surgery.

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Mason, Meredith C; Garcia, Jose M; Sansgiry, Shubhada; Walder, Annette; Berger, David H; Anaya, Daniel A

2016-10-01

Cancer cachexia is an important measure of physiologic reserve associated with worse survival and represents an actionable factor for the cancer population. However, the incidence of cachexia in surgical cancer patients and its impact on postoperative outcomes are currently unknown. A prospective cohort study enrolling patients having elective cancer surgery (2012-2014) at a Veterans Affairs tertiary referral center. Preoperative cancer cachexia (weight loss ≥5% over 6-mo period before surgery) was the predictor of interest. The primary outcome was 60-d postoperative complications (VA Surgical Quality Improvement Program). Patients were grouped by body mass index (BMI) category (cachexia and BMI was tested for the primary outcome. Multivariate logistic regression was used to examine the association between preoperative cachexia and postoperative complications. Of 253 patients, 16.6% had preoperative cachexia, and 51.8% developed ≥ 1 postoperative complications. Complications were more common in cachectic patients (64.3% versus 49.3%, P = 0.07). This association varied by BMI category, and interaction analysis was significant for those with normal or underweight BMI (BMI cachexia was associated with higher odds of postoperative complications (odds ratios, 5.08 [95% confidence intervals, 1.18-21.88]; P = 0.029). Additional predictors of complications included major surgery (3.19 [1.24-8.21], P = 0.01), ostomy (4.43 [1.68-11.72], P = 0.003), and poor baseline performance status (2.31 [1.05-5.08], P = 0.03). Cancer cachexia is common in surgical patients, and is an important predictor of postoperative complications, though its effect varies by BMI. As a modifiable predictor of worse outcomes, future studies should examine the role of cachexia treatment before cancer surgery. Copyright © 2016 Elsevier Inc. All rights reserved.
Proteomic-coupled-network analysis of T877A-androgen receptor interactomes can predict clinical prostate cancer outcomes between White (non-Hispanic and African-American groups.

Directory of Open Access Journals (Sweden)

Naif Zaman

Full Text Available The androgen receptor (AR remains an important contributor to the neoplastic evolution of prostate cancer (CaP. CaP progression is linked to several somatic AR mutational changes that endow upon the AR dramatic gain-of-function properties. One of the most common somatic mutations identified is Thr877-to-Ala (T877A, located in the ligand-binding domain, that results in a receptor capable of promiscuous binding and activation by a variety of steroid hormones and ligands including estrogens, progestins, glucocorticoids, and several anti-androgens. In an attempt to further define somatic mutated AR gain-of-function properties, as a consequence of its promiscuous ligand binding, we undertook a proteomic/network analysis approach to characterize the protein interactome of the mutant T877A-AR in LNCaP cells under eight different ligand-specific treatments (dihydrotestosterone, mibolerone, R1881, testosterone, estradiol, progesterone, dexamethasone, and cyproterone acetate. In extending the analysis of our multi-ligand complexes of the mutant T877A-AR we observed significant enrichment of specific complexes between normal and primary prostatic tumors, which were furthermore correlated with known clinical outcomes. Further analysis of certain mutant T877A-AR complexes showed specific population preferences distinguishing primary prostatic disease between white (non-Hispanic vs. African-American males. Moreover, these cancer-related AR-protein complexes demonstrated predictive survival outcomes specific to CaP, and not for breast, lung, lymphoma or medulloblastoma cancers. Our study, by coupling data generated by our proteomics to network analysis of clinical samples, has helped to define real and novel biological pathways in complicated gain-of-function AR complex systems.
Risk adjusted surgical audit in gynaecological oncology: P-POSSUM does not predict outcome.

Science.gov (United States)

Das, N; Talaat, A S; Naik, R; Lopes, A D; Godfrey, K A; Hatem, M H; Edmondson, R J

2006-12-01

To assess the Physiological and Operative Severity Score for the enumeration of mortality and morbidity (POSSUM) and its validity for use in gynaecological oncology surgery. All patients undergoing gynaecological oncology surgery at the Northern Gynaecological Oncology Centre (NGOC) Gateshead, UK over a period of 12months (2002-2003) were assessed prospectively. Mortality and morbidity predictions using the Portsmouth modification of the POSSUM algorithm (P-POSSUM) were compared to the actual outcomes. Performance of the model was also evaluated using the Hosmer and Lemeshow Chi square statistic (testing the goodness of fit). During this period 468 patients were assessed. The P-POSSUM appeared to over predict mortality rates for our patients. It predicted a 7% mortality rate for our patients compared to an observed rate of 2% (35 predicted deaths in comparison to 10 observed deaths), a difference that was statistically significant (H&L chi(2)=542.9, d.f. 8, prisk of mortality for gynaecological oncology patients undergoing surgery. The P-POSSUM algorithm will require further adjustments prior to adoption for gynaecological cancer surgery as a risk adjusted surgical audit tool.
Prognostic value of response to external radiation in stage IIIB cancer cervix in predicting clinical outcomes: A retrospective analysis of 556 patients from India

International Nuclear Information System (INIS)

Saibishkumar, Elantholi P.; Patel, Firuza D.; Sharma, Suresh C.; Karunanidhi, Gunaseelan; Ghoshal, Sushmita; Kumar, Vinay; Kapoor, Rakesh

2006-01-01

Background and purpose: To evaluate the prognostic significance of response to external beam radiation (EBRT) in predicting the clinical outcomes in stage IIIB cancer cervix and to find out factors affecting response to EBRT. Patients and methods: This retrospective study included 556 patients of cancer cervix stage IIIB treated between 1996 and 2001 with EBRT (46 Gy/23fx/4.5 weeks) followed by intracavitary radiotherapy (ICRT). At the end of EBRT, response to EBRT was grouped as 'no gross residual tumor'(NRT) or 'gross residual tumor'(GRT). Results: Follow up ranged from 2 to 93 months with a median of 36 months. Median dose to point A was 81 Gy. At the end of EBRT, 393 patients (70.7%) attained NRT response. NRT responders had significantly better 5 year pelvic control, disease free survival (DFS) and overall survival (OS) than those who had a GRT response (75.6 vs. 54.6%; 60.6 vs. 31.9% and 62.6 vs. 33.7%, respectively; all P values <0.0001). Apart from response to EBRT, overall treatment time also has emerged as an independent factor to affect all clinical outcomes in multivariate analysis but age had significant impact on pelvic control only. Age was the only factor, which significantly influenced the response to EBRT in univariate as well as multivariate analysis (P=<0.001, OR=1.973, 95% C.I. 1.357-2.868). Patients with age more than 50 years had more NRT response (77%) than patients with age less than 50 years (63.8%). Conclusions: Patients who attain NRT response to EBRT will have an impressive long term pelvic control, DFS and OS in stage IIIB cancer cervix. Older patients (≥50 years) attain significantly higher NRT rates than younger patients
Combining Gene Signatures Improves Prediction of Breast Cancer Survival

Science.gov (United States)

Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

2011-01-01

Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast
Combining gene signatures improves prediction of breast cancer survival.

Directory of Open Access Journals (Sweden)

Xi Zhao

Full Text Available BACKGROUND: Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123 and test set (n = 81, respectively. Gene sets from eleven previously published gene signatures are included in the study. PRINCIPAL FINDINGS: To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014. Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001. The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. CONCLUSION: Combining the predictive strength of multiple gene signatures improves
Correlation of bevacizumab-induced hypertension and outcomes of metastatic colorectal cancer patients treated with bevacizumab: a systematic review and meta-analysis.

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Cai, Jun; Ma, Hong; Huang, Fang; Zhu, Dichao; Bi, Jianping; Ke, Yang; Zhang, Tao

2013-11-28

With the wide application of targeted drug therapies, the relevance of prognostic and predictive markers in patient selection has become increasingly important. Bevacizumab is commonly used in combination with chemotherapy in the treatment of metastatic colorectal cancer. However, there are currently no predictive or prognostic biomarkers for bevacizumab. Several clinical studies have evaluated bevacizumab-induced hypertension in patients with metastatic colorectal cancer. This meta-analysis was performed to better determine the association of bevacizumab-induced hypertension with outcome in patients with metastatic colorectal cancer, and to assess whether bevacizumab-induced hypertension can be used as a prognostic factor in these patients. We performed a systematic review and meta-analysis on seven published studies to investigate the relationship between hypertension and outcome of patients with metastatic colorectal cancer treated with bevacizumab. Our primary endpoint was progression-free survival (PFS). Secondary endpoints were overall survival (OS) and overall response rate (ORR). Hazard ratios (HRs) for PFS and OS were extracted from each trial, and the log of the relative risk ratio (RR) was estimated for ORR. The occurrence of bevacizumab-induced hypertension in patients was highly associated with improvements in PFS (HR = 0.57, 95% CI: 0.46-0.72; P hypertension. Bevacizumab-induced hypertension may represent a prognostic factor in patients with metastatic colorectal cancer.
The association between smoking and breast cancer characteristics and outcome.

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Goldvaser, Hadar; Gal, Omer; Rizel, Shulamith; Hendler, Daniel; Neiman, Victoria; Shochat, Tzippy; Sulkes, Aaron; Brenner, Baruch; Yerushalmi, Rinat

2017-09-06

Smoking is associated with an increased incidence of hormone receptor positive breast cancer. Data regarding worse breast cancer outcome in smokers are accumulating. Current literature regarding the impact of smoking on breast cancer characteristics is limited. We evaluated the impact of smoking on breast cancer characteristics and outcome. This was a retrospective single center study. All women diagnosed from 4/2005 through 3/2012 and treated in our institute for early, estrogen receptor positive, human epidermal growth factor receptor 2 (HER2) negative breast cancer, whose tumors were sent for Oncotype DX analysis were included. Medical records were reviewed for demographics, clinico-pathological parameters, treatment and outcome. Data regarding smoking were retrieved according to patients' history at the first visit in the oncology clinic. Patients were grouped and compared according to smoking history (ever smokers vs. never smokers), smoking status (current vs. former and never smokers) and smoking intensity (pack years ≥30 vs. the rest of the cohort). Outcomes were adjusted in multivariate analyses and included age, menopausal status, ethnicity, tumor size, nodal status and grade. A total of 662 women were included. 28.2% had a history of smoking, 16.6% were current smokers and 11.3% were heavy smokers. Smoking had no impact on tumor size, nodal involvement and Oncotype DX recurrence score. Angiolymphatic and perineural invasion rates were higher in current smokers than in the rest of the cohort (10.4% vs. 5.1%, p = 0.045, 8.3% vs. 3.5%, p = 0.031, respectively). Smoking had no other impact on histological characteristics. Five-year disease free survival and overall survival rates were 95.7% and 98.5%, respectively. Smoking had no impact on outcomes. Adjusted disease free survival and overall survival did not influence the results. Smoking had no clinically significant influence on tumor characteristics and outcome among women with estrogen receptor

Prediction of outcome in patients with low back pain

DEFF Research Database (Denmark)

Kongsted, Alice; Andersen, Cathrine Hedegaard; Mørk Hansen, Martin

2016-01-01

The clinical course of low back pain (LBP) cannot be accurately predicted by existing prediction tools. Therefore clinicians rely largely on their experience and clinical judgement. The objectives of this study were to investigate 1) which patient characteristics were associated with chiropractors...... intensity (0-10) and disability (RMDQ) after 2-weeks, 3-months, and 12-months. The course of LBP in 859 patients was predicted to be short (54%), prolonged (36%), or chronic (7%). Clinicians' expectations were most strongly associated with education, LBP history, radiating pain, and neurological signs......' expectations of outcome from a LBP episode, 2) if clinicians' expectations related to outcome, 3) how accurate clinical predictions were as compared to those of the STarT Back Screening Tool (SBT), and 4) if accuracy was improved by combining clinicians' expectations and the SBT. Outcomes were measured as LBP...
{sup 18}F-alfatide PET/CT may predict short-term outcome of concurrent chemoradiotherapy in patients with advanced non-small cell lung cancer

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Luan, Xiaohui [Shandong Cancer Hospital affiliated to Shandong University, Department of Radiation Oncology, Jinan, Shandong (China); University of Jinan-Shandong Academy of Medical Sciences, School of Medicine and Life Sciences, Jinan (China); Huang, Yong; Sun, Xiaorong; Ma, Li; Teng, Xuepeng; Lu, Hong [Shandong Cancer Hospital affiliated to Shandong University, Department of Radiology, Jinan, Shandong (China); Gao, Song [Jining Infectious Diseases Hospital, Department of Oncology, Jining, Shandong (China); Wang, Suzhen; Yu, Jinming; Yuan, Shuanghu [Shandong Cancer Hospital affiliated to Shandong University, Department of Radiation Oncology, Jinan, Shandong (China)

2016-12-15

The study aims to investigate the role of {sup 18}F-alfatide positron emission tomography/computed tomography (PET/CT) in predicting the short-term outcome of concurrent chemoradiotherapy (CCRT) in patients with advanced non-small cell lung cancer (NSCLC). Eighteen patients with advanced NSCLC had undergone {sup 18}F-alfatide PET/CT scans before CCRT and PET/CT parameters including maximum and mean standard uptake values (SUV{sub max}/SUV{sub mean}), peak standard uptake values (SUV{sub peak}) and tumor volume (TV{sub PET} and TV{sub CT}) were obtained. The SUV{sub max} of tumor and normal tissues (lung, blood pool and muscle) were measured, and their ratios were denoted as T/NT (T/NT{sub lung}, T/NT{sub blood} and T/NT{sub muscle}). Statistical methods included the Two-example t test, Wilcoxon rank-sum test, Receiver-operating characteristic (ROC) curve analysis and logistic regression analyses. We found that SUV{sub max}, SUV{sub peak}, T/NT{sub lung}, T/NT{sub blood} and T/NT{sub muscle} were higher in non-responders than in responders (P = 0.0024, P = 0.016, P < 0.001, P = 0.003, P = 0.004). According to ROC curve analysis, the thresholds of SUV{sub max}, SUV{sub peak}, T/NT{sub lung}, T/NT{sub blood} and T/NT{sub muscle} were 5.65, 4.46, 7.11, 5.41, and 11.75, respectively. The five parameters had high sensitivity, specificity and accuracy in distinguishing non-responders and responders. Multivariate logistic regression analyses showed that T/NT{sub lung} was an independent predictor of the short-term outcome of CCRT in patients with advanced NSCLC (P = 0.032). {sup 18}F-alfatide PET/CT may be useful in predicting the short-term outcome of CCRT in patients with advanced NSCLC. (orig.)
Outcomes of colon resection in patients with metastatic colon cancer.

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Moghadamyeghaneh, Zhobin; Hanna, Mark H; Hwang, Grace; Mills, Steven; Pigazzi, Alessio; Stamos, Michael J; Carmichael, Joseph C

2016-08-01

Patients with advanced colorectal cancer have a high incidence of postoperative complications. We sought to identify outcomes of patients who underwent resection for colon cancer by cancer stage. The National Surgical Quality Improvement Program database was used to evaluate all patients who underwent colon resection with a diagnosis of colon cancer from 2012 to 2014. Multivariate logistic regression analysis was performed to investigate patient outcomes by cancer stage. A total of 7,786 colon cancer patients who underwent colon resection were identified. Of these, 10.8% had metastasis at the time of operation. Patients with metastatic disease had significantly increased risks of perioperative morbidity (adjusted odds ratio [AOR]: 1.44, P = .01) and mortality (AOR: 3.72, P = .01). Patients with metastatic disease were significantly younger (AOR: .99, P colon cancer have metastatic disease. Postoperative morbidity and mortality are significantly higher than in patients with localized disease. Published by Elsevier Inc.
The Breast and Cervical Cancer Early Detection Program, Medicaid, and breast cancer outcomes among Ohio's underserved women.

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Koroukian, Siran M; Bakaki, Paul M; Htoo, Phyo Than; Han, Xiaozhen; Schluchter, Mark; Owusu, Cynthia; Cooper, Gregory S; Rose, Johnie; Flocke, Susan A

2017-08-15

As an organized screening program, the national Breast and Cervical Cancer Early Detection Program (BCCEDP) was launched in the early 1990s to improve breast cancer outcomes among underserved women. To analyze the impact of the BCCEDP on breast cancer outcomes in Ohio, this study compared cancer stages and mortality across BCCEDP participants, Medicaid beneficiaries, and "all others." This study linked data across the Ohio Cancer Incidence Surveillance System, Medicaid, the BCCEDP database, death certificates, and the US Census and identified 26,426 women aged 40 to 64 years who had been diagnosed with incident invasive breast cancer during the years 2002-2008 (deaths through 2010). The study groups were as follows: BCCEDP participants (1-time or repeat users), Medicaid beneficiaries (women enrolled in Medicaid before their cancer diagnosis [Medicaid/prediagnosis] or around the time of their cancer diagnosis [Medicaid/peridiagnosis]), and all others (women identified as neither BCCEDP participants nor Medicaid beneficiaries). The outcomes included advanced-stage cancer at diagnosis and mortality. A multivariable logistic and survival analysis was conducted to examine the independent association between the BCCEDP and Medicaid status and the outcomes. The percentage of women presenting with advanced-stage disease was highest among women in the Medicaid/peridiagnosis group (63.4%) and lowest among BCCEDP repeat users (38.6%). With adjustments for potential confounders and even in comparison with Medicaid/prediagnosis beneficiaries, those in the Medicaid/peridiagnosis group were twice as likely to be diagnosed with advanced-stage disease (adjusted odds ratio, 2.20; 95% confidence interval, 1.83-2.66). Medicaid/peridiagnosis women are at particularly high risk to be diagnosed with advanced-stage disease. Efforts to reduce breast cancer disparities must target this group of women before they present to Medicaid. Cancer 2017;123:3097-106. © 2017 American Cancer Society
An exploratory, large-scale study of pain and quality of life outcomes in cancer patients with moderate or severe pain, and variables predicting improvement.

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Maximiano, Constanza; López, Iker; Martín, Cristina; Zugazabeitia, Luis; Martí-Ciriquián, Juan L; Núñez, Miguel A; Contreras, Jorge; Herdman, Michael; Traseira, Susana; Provencio, Mariano

2018-01-01

There have been few large-scale, real world studies in Spain to assess change in pain and quality of life (QOL) outcomes in cancer patients with moderate to severe pain. This study aimed to assess changes on both outcomes after 3 months of usual care and to investigate factors associated with change in QoL. Large, multi-centre, observational study in patients with lung, head and neck, colorectal or breast cancer experiencing a first episode of moderate to severe pain while attending one of the participating centres. QoL was assessed using the EuroQol-5D questionnaire and pain using the Brief Pain Inventory (BPI). Instruments were administered at baseline and after 3 months of follow up. Multivariate analyses were used to assess the impact of treatment factors, demographic and clinical variables, pain and other symptoms on QoL scores. 1711 patients were included for analysis. After 3 months of usual care, a significant improvement was observed in pain and QoL in all four cancer groups (pbreast cancer patients showed the largest gains. Poorer baseline performance status (ECOG) and the presence of anxiety/depression were associated with significantly poorer QOL outcomes. Improvements in BPI pain scores were associated with improved QoL. In the four cancer types studied, pain and QoL outcomes improved considerably after 3 months of usual care. Improvements in pain made a substantial contribution to QoL gains whilst the presence of anxiety and depression and poor baseline performance status significantly constrained improvement.
Feasibility test of a UK-scalable electronic system for regular collection of patient-reported outcome measures and linkage with clinical cancer registry data: The electronic Patient-reported Outcomes from Cancer Survivors (ePOCS system

Directory of Open Access Journals (Sweden)

Velikova Galina

2011-10-01

Full Text Available Abstract Background Cancer survivors can face significant physical and psychosocial challenges; there is a need to identify and predict which survivors experience what sorts of difficulties. As highlighted in the UK National Cancer Survivorship Initiative, routine post-diagnostic collection of patient reported outcome measures (PROMs is required; to be most informative, PROMs must be linked and analysed with patients' diagnostic and treatment information. We have designed and built a potentially cost-efficient UK-scalable electronic system for collecting PROMs via the internet, at regular post-diagnostic time-points, for linking these data with patients' clinical data in cancer registries, and for electronically managing the associated patient monitoring and communications; the electronic Patient-reported Outcomes from Cancer Survivors (ePOCS system. This study aims to test the feasibility of the ePOCS system, by running it for 2 years in two Yorkshire NHS Trusts, and using the Northern and Yorkshire Cancer Registry and Information Service. Methods/Design Non-metastatic breast, colorectal and prostate cancer patients (largest survivor groups, within 6 months post-diagnosis, will be recruited from hospitals in the Yorkshire Cancer Network. Participants will be asked to complete PROMS, assessing a range of health-related quality-of-life outcomes, at three time-points up to 15 months post-diagnosis, and subsequently to provide opinion on the ePOCS system via a feedback questionnaire. Feasibility will be examined primarily in terms of patient recruitment and retention rates, the representativeness of participating patients, the quantity and quality of collected PROMs data, patients' feedback, the success and reliability of the underpinning informatics, and the system running costs. If sufficient data are generated during system testing, these will be analysed to assess the health-related quality-of-life outcomes reported by patients, and to explore
Fear of cancer recurrence and its predictive factors among Iranian cancer patients

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Alireza Mohajjel Aghdam

2014-01-01

Full Text Available Context: Fear of cancer recurrence (FOCR is one of the most important psychological problems among cancer patients. In extensive review of related literature there were no articles on FOCR among Iranian cancer patients. Aim: The aim of present study was to investigation FOCR and its predictive factors among Iranian cancer patients. Materials and Methods: In this descriptive-correlational study 129 cancer patients participated. For data collection, the demographic checklist and short form of fear of progression questionnaire was used. Logistic regression was used to determine predictive factors of FOCR. Result: Mean score of FOCR among participants was 44.8 and about 50% of them had high level of FOCR. The most important worries of participants were about their family and the future of their children and their lesser worries were about the physical symptoms and fear of physical damage because of cancer treatments. Also, women, breast cancer patient, and patients with lower level of education have more FOCR. Discussion: There is immediate need for supportive care program designed for Iranian cancer patients aimed at decreasing their FOCR. Especially, breast cancer patients and the patient with low educational level need more attention.
SVM and SVM Ensembles in Breast Cancer Prediction

OpenAIRE

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction per...
Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning.

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Kesler, Shelli R; Rao, Arvind; Blayney, Douglas W; Oakley-Girvan, Ingrid A; Karuturi, Meghan; Palesh, Oxana

2017-01-01

We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34-65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy ( p breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment.
Serum protein profile at remission can accurately assess therapeutic outcomes and survival for serous ovarian cancer.

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Jinhua Wang

Full Text Available BACKGROUND: Biomarkers play critical roles in early detection, diagnosis and monitoring of therapeutic outcome and recurrence of cancer. Previous biomarker research on ovarian cancer (OC has mostly focused on the discovery and validation of diagnostic biomarkers. The primary purpose of this study is to identify serum biomarkers for prognosis and therapeutic outcomes of ovarian cancer. EXPERIMENTAL DESIGN: Forty serum proteins were analyzed in 70 serum samples from healthy controls (HC and 101 serum samples from serous OC patients at three different disease phases: post diagnosis (PD, remission (RM and recurrence (RC. The utility of serum proteins as OC biomarkers was evaluated using a variety of statistical methods including survival analysis. RESULTS: Ten serum proteins (PDGF-AB/BB, PDGF-AA, CRP, sFas, CA125, SAA, sTNFRII, sIL-6R, IGFBP6 and MDC have individually good area-under-the-curve (AUC values (AUC = 0.69-0.86 and more than 10 three-marker combinations have excellent AUC values (0.91-0.93 in distinguishing active cancer samples (PD & RC from HC. The mean serum protein levels for RM samples are usually intermediate between HC and OC patients with active cancer (PD & RC. Most importantly, five proteins (sICAM1, RANTES, sgp130, sTNFR-II and sVCAM1 measured at remission can classify, individually and in combination, serous OC patients into two subsets with significantly different overall survival (best HR = 17, p<10(-3. CONCLUSION: We identified five serum proteins which, when measured at remission, can accurately predict the overall survival of serous OC patients, suggesting that they may be useful for monitoring the therapeutic outcomes for ovarian cancer.
Relationship of Predicted Risk of Developing Invasive Breast Cancer, as Assessed with Three Models, and Breast Cancer Mortality among Breast Cancer Patients.

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Mark E Sherman

Full Text Available Breast cancer risk prediction models are used to plan clinical trials and counsel women; however, relationships of predicted risks of breast cancer incidence and prognosis after breast cancer diagnosis are unknown.Using largely pre-diagnostic information from the Breast Cancer Surveillance Consortium (BCSC for 37,939 invasive breast cancers (1996-2007, we estimated 5-year breast cancer risk (<1%; 1-1.66%; ≥1.67% with three models: BCSC 1-year risk model (BCSC-1; adapted to 5-year predictions; Breast Cancer Risk Assessment Tool (BCRAT; and BCSC 5-year risk model (BCSC-5. Breast cancer-specific mortality post-diagnosis (range: 1-13 years; median: 5.4-5.6 years was related to predicted risk of developing breast cancer using unadjusted Cox proportional hazards models, and in age-stratified (35-44; 45-54; 55-69; 70-89 years models adjusted for continuous age, BCSC registry, calendar period, income, mode of presentation, stage and treatment. Mean age at diagnosis was 60 years.Of 6,021 deaths, 2,993 (49.7% were ascribed to breast cancer. In unadjusted case-only analyses, predicted breast cancer risk ≥1.67% versus <1.0% was associated with lower risk of breast cancer death; BCSC-1: hazard ratio (HR = 0.82 (95% CI = 0.75-0.90; BCRAT: HR = 0.72 (95% CI = 0.65-0.81 and BCSC-5: HR = 0.84 (95% CI = 0.75-0.94. Age-stratified, adjusted models showed similar, although mostly non-significant HRs. Among women ages 55-69 years, HRs approximated 1.0. Generally, higher predicted risk was inversely related to percentages of cancers with unfavorable prognostic characteristics, especially among women 35-44 years.Among cases assessed with three models, higher predicted risk of developing breast cancer was not associated with greater risk of breast cancer death; thus, these models would have limited utility in planning studies to evaluate breast cancer mortality reduction strategies. Further, when offering women counseling, it may be useful to note that high
Stage-specific predictive models for breast cancer survivability.

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Kate, Rohit J; Nadig, Ramya

2017-01-01

Survivability rates vary widely among various stages of breast cancer. Although machine learning models built in past to predict breast cancer survivability were given stage as one of the features, they were not trained or evaluated separately for each stage. To investigate whether there are differences in performance of machine learning models trained and evaluated across different stages for predicting breast cancer survivability. Using three different machine learning methods we built models to predict breast cancer survivability separately for each stage and compared them with the traditional joint models built for all the stages. We also evaluated the models separately for each stage and together for all the stages. Our results show that the most suitable model to predict survivability for a specific stage is the model trained for that particular stage. In our experiments, using additional examples of other stages during training did not help, in fact, it made it worse in some cases. The most important features for predicting survivability were also found to be different for different stages. By evaluating the models separately on different stages we found that the performance widely varied across them. We also demonstrate that evaluating predictive models for survivability on all the stages together, as was done in the past, is misleading because it overestimates performance. Copyright Â© 2016 Elsevier Ireland Ltd. All rights reserved.
Prediction of cancer incidence in Tyrol/Austria for year of diagnosis 2020.

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Oberaigner, Willi; Geiger-Gritsch, Sabine

2014-10-01

Prediction of the number of incident cancer cases is very relevant for health planning purposes and allocation of resources. The shift towards elder age groups in central European populations in the next decades is likely to contribute to an increase in cancer incidence for many cancer sites. In Tyrol, cancer incidence data have been registered on a high level of completeness for more than 20 years. We therefore aimed to compute well-founded predictions of cancer incidence for Tyrol for the year 2020 for all frequent cancer sites and for all cancer sites combined. After defining a prediction base range for every cancer site, we extrapolated the age-specific time trends in the prediction base range following a linear model for increasing and a log-linear model for decreasing time trends. The extrapolated time trends were evaluated for the year 2020 applying population figures supplied by Statistics Austria. Compared with the number of annual incident cases for the year 2009 for all cancer sites combined except non-melanoma skin cancer, we predicted an increase of 235 (15 %) and 362 (21 %) for females and males, respectively. For both sexes, more than 90 % of the increase is attributable to the shift toward older age groups in the next decade. The biggest increase in absolute numbers is seen for females in breast cancer (92, 21 %), lung cancer (64, 52 %), colorectal cancer (40, 24 %), melanoma (38, 30 %) and the haematopoietic system (37, 35 %) and for males in prostate cancer (105, 25 %), colorectal cancer (91, 45 %), the haematopoietic system (71, 55 %), bladder cancer (69, 100 %) and melanoma (64, 52 %). The increase in the number of incident cancer cases of 15 % in females and 21 % in males in the next decade is very relevant for planning purposes. However, external factors cause uncertainty in the prediction of some cancer sites (mainly prostate cancer and colorectal cancer) and the prediction intervals are still broad. Therefore
Economic and quality-of-life outcomes in head and neck cancer

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Harrison, Louis B.

1996-01-01

Head and neck cancer offers a special and unique challenge to physicians and patients. Treatment of cancers in this part of the body, especially surgical resection, can cause profound changes in quality-of-life. The patient's ability to work, earn a living, articulate speech, communicate, have social interaction, and live a normal life, can be affected in a major way. Therefore, physicians and patients must look beyond the obvious oncologic outcomes of locoregional control, distant metastasis free survival, and overall survival. These outcomes must be assessed along with detailed, quality-of-life and economic outcomes, in order to properly manage patients. It is also mandatory that patients have a clear understanding of all their treatment options, and the implications of these options on cancer control and quality-of-life. This panel will focus on the available methods to assess quality-of-life and economic outcomes in head and neck cancer management. It will also highlight areas where new oncologic strategies are utilized which emphasize organ and function preservation. This latter area is an important aspect of modern clinical research and practice. In particular, management of cancers of the tongue, larynx, and hypopharynx offer special opportunities. Resection of these organs can produce debilitating functional outcomes. New multidisciplinary approaches to treat patients while avoiding primary resection have been developed. The oncologic and quality-of-life/economic outcomes will be assessed for these organ preserving strategies
Accordion complication grading predicts short-term outcome after right colectomy.

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Klos, Coen L; Safar, Bashar; Hunt, Steven R; Wise, Paul E; Birnbaum, Elisa H; Mutch, Matthew G; Fleshman, James W; Dharmarajan, Sekhar

2014-08-01

The Accordion severity grading system is a novel system to score the severity of postoperative complications in a standardized fashion. This study aims to demonstrate the validity of the Accordion system in colorectal surgery by correlating severity grades with short-term outcomes after right colectomy for colon cancer. This is a retrospective cohort review of patients who underwent right colectomy for cancer between January 1, 2002, and January 31, 2007, at a single tertiary care referral center. Complications were categorized according to the Accordion severity grading system: grades 1 (mild), 2 (moderate), 3-5 (severe), and 6 (death). Outcome measures were hospital stay, 30-d readmission rate and 1-y survival. Correlation between Accordion grades and outcome measures is reflected by Spearman rho (ρ). One-year survival was obtained per Kaplan-Meier method and compared by logrank test for trend. Significance was set at P ≤ 0.05. Overall, 235 patients underwent right colectomy for cancer of which 122 (51.9%) had complications. In total, 52 (43%) had an Accordion grade 1 complication; 44 (36%) grade 2; four (3%) grade 3; 11 (9%) grade 4; seven (6%) grade 5; and four (3%) grade 6. There was significant correlation between Accordion grades and hospital stay (ρ = 0.495, P trend in 1-y survival as complication severity by Accordion grade increased (P = 0.02). The Accordion grading system is a useful tool to estimate short-term outcomes after right colectomy for cancer. High-grade Accordion complications are associated with longer hospital stay and increased risk of readmission and mortality. Published by Elsevier Inc.
FDG PET/CT radiomics for predicting the outcome of locally advanced rectal cancer

International Nuclear Information System (INIS)

Lovinfosse, Pierre; Hustinx, Roland; Polus, Marc; Daele, Daniel van; Martinive, Philippe; Daenen, Frederic; Hatt, Mathieu; Visvikis, Dimitris; Koopmansch, Benjamin; Lambert, Frederic; Coimbra, Carla; Seidel, Laurence; Albert, Adelin; Delvenne, Philippe

2018-01-01

The aim of this study was to investigate the prognostic value of baseline 18 F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC). Eighty-six patients with LARC underwent 18 F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis. Logistic regression was used to predict the pathological response by the Dworak tumor regression grade (TRG) in the 66 patients treated with neoadjuvant chemoradiotherapy (nCRT). The median follow-up of patients was 41 months. Seventeen patients (19.7%) had recurrent disease and 18 (20.9 %) died, either due to cancer progression (n = 10) or from another cause while in complete remission (n = 8). DSS was 95% at 1 year, 93% at 2 years and 87% at 4 years. Weight loss, surgery and the texture parameter coarseness were significantly associated with DSS in multivariate analyses. DFS was 94 % at 1 year, 86 % at 2 years and 79 % at 4 years. From a multivariate standpoint, tumoral differentiation and the texture parameters homogeneity and coarseness were significantly associated with DFS. OS was 93% at 1 year, 87% at 2 years and 79% after 4 years. cT, surgery, SUVmean, dissimilarity and contrast from the neighborhood intensity-difference matrix (contrast NGTDM ) were significantly and independently associated with OS. Finally, RAS-mutational status (KRAS and NRAS mutations) and TLG were significant predictors of pathological response to nCRT (TRG 3-4). Textural analysis of baseline 18 F-FDG PET/CT provides strong independent predictors of survival in patients with LARC, with better predictive power than intensity- and volume
Baseline peripheral blood leukocytosis: Biological marker predicts outcome in oropharyngeal cancer, regardless of HPV-status.

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Gouw, Zeno A R; Paul de Boer, Jan; Navran, Arash; van den Brekel, Michiel W M; Sonke, Jan-Jakob; Al-Mamgani, Abrahim

2018-03-01

To study the prognostic value of abnormalities in baseline complete blood count in patients with oropharyngeal cancer (OPC) treated with (chemo) radiation. The prognostic value of baseline complete blood count on outcome in 234 patients with OPC treated between 2010 and 2015 was examined in multivariate analysis together with other conventional prognostic variables including HPV-status, tumor stage, tumor and nodal size. The 3-year overall survival (OS), disease-free survival (DFS), locoregional control (LRC), and distant control (DC) of the whole group were 74%, 64%, 79%, and 88%, respectively. Leukocytosis and HPV-status were the only significant prognosticators for OS and DFS at the multivariate analysis. Patients without leukocytosis had a significantly better DC compared to those with leukocytosis (92% and 70%, respectively, p HPV-negative OPC had significantly worse LRC compared to HPV-positive patients (67% and 90%, respectively, p HPV-positive group with leukocytosis compared to those without leukocytosis were 69% and 95%, respectively (p HPV-negative patients were 41% vs. 61%, respectively (p = 0.010). This is the first study to date reporting the independent impact of leukocytosis and HPV-status on outcome of patients with OPC. The poor outcome of patients with leukocytosis is mainly caused by the worse DC. The significant impact of leukocytosis on outcome was even more pronounced in HPV-positive patients. These biomarkers could help identifying patients with poor prognosis at baseline requiring intensification of local and/or systemic treatment while treatment de-intensification might be offered to the low-risk group. Copyright © 2018 Elsevier Ltd. All rights reserved.
P53 overexpression and outcome of radiation therapy in head and neck cancers

International Nuclear Information System (INIS)

Kim, In Ah; Choi, Ihl Bhong; Kang, Ki Mun; Jang, Ji Young; Kim, Kyung Mi; Park, Kyung Shin; Kim, Young Shin; Kang, Chang Suk; Cho, Seung Ho; Kim, Hyung Tae

1999-01-01

Experimental studies have implicated the wild type p53 in cellular response to radiation. Whether altered p53 function can lead to changes in clinical radiocurability remains an area of ongoing study. This study was performed to investigate whether any correlation between change of p53 and outcome of curative radiation therapy in patients with head and neck cancers. Immunohistochemical analysis with a mouse monoclonal antibody (D0-7) specific for human p53 was used to detect to overexpression of protein in formalin fixed, paraffin-embedded tumor sample from 55 head and neck cancer patients treated with curative radiation therapy (median dose of 7020 cGy) from February 1988 to March 1996 at St. Mary's Hospital. Overexpression of p53 was correlated with locoregional control and survival using Kaplan-Meier method. A Cox regression multivariate analysis was performed that included all clinical variables and status of p53 expression. Thirty-seven (67.2%) patients showed overexpression of p53 by immunohistochemical staining in their tumor. One hundred percent of oral cavity, 76% of laryngeal, 66.7% of oropharyngeal, 66.7% of hypopharyngeal cancer showed p53 overexpression (p=0.05). The status of p53 had significant relationship with stage of disease (p=0.03) and history of smoking (p=0.001). The overexpression of p53 was not predictive of response rate to radiation therapy. The locoregional control was not significantly affected by p53 status. Overexpression of p53 didn't have any prognostic implication for disease free survival and overall survival. Primary site and stage of disease were significant prognostic factors for survival. The p53 overexpression as detected by immunohistochemical staining had significant correlation with stage, primary site of disease and smoking habit of patients. The p53 overexpression didn't have any predictive value for outcome of curative radiation therapy in a group of head and neck cancers
P53 overexpression and outcome of radiation therapy in head and neck cancers

Energy Technology Data Exchange (ETDEWEB)

Kim, In Ah; Choi, Ihl Bhong; Kang, Ki Mun; Jang, Ji Young; Kim, Kyung Mi; Park, Kyung Shin; Kim, Young Shin; Kang, Chang Suk; Cho, Seung Ho; Kim, Hyung Tae [College of Medicine, The Catholic Univ., Seoul (Korea, Republic of)

1999-03-01

Experimental studies have implicated the wild type p53 in cellular response to radiation. Whether altered p53 function can lead to changes in clinical radiocurability remains an area of ongoing study. This study was performed to investigate whether any correlation between change of p53 and outcome of curative radiation therapy in patients with head and neck cancers. Immunohistochemical analysis with a mouse monoclonal antibody (D0-7) specific for human p53 was used to detect to overexpression of protein in formalin fixed, paraffin-embedded tumor sample from 55 head and neck cancer patients treated with curative radiation therapy (median dose of 7020 cGy) from February 1988 to March 1996 at St. Mary's Hospital. Overexpression of p53 was correlated with locoregional control and survival using Kaplan-Meier method. A Cox regression multivariate analysis was performed that included all clinical variables and status of p53 expression. Thirty-seven (67.2%) patients showed overexpression of p53 by immunohistochemical staining in their tumor. One hundred percent of oral cavity, 76% of laryngeal, 66.7% of oropharyngeal, 66.7% of hypopharyngeal cancer showed p53 overexpression (p=0.05). The status of p53 had significant relationship with stage of disease (p=0.03) and history of smoking (p=0.001). The overexpression of p53 was not predictive of response rate to radiation therapy. The locoregional control was not significantly affected by p53 status. Overexpression of p53 didn't have any prognostic implication for disease free survival and overall survival. Primary site and stage of disease were significant prognostic factors for survival. The p53 overexpression as detected by immunohistochemical staining had significant correlation with stage, primary site of disease and smoking habit of patients. The p53 overexpression didn't have any predictive value for outcome of curative radiation therapy in a group of head and neck cancers.
ROCK I Has More Accurate Prognostic Value than MET in Predicting Patient Survival in Colorectal Cancer.

Science.gov (United States)

Li, Jian; Bharadwaj, Shruthi S; Guzman, Grace; Vishnubhotla, Ramana; Glover, Sarah C

2015-06-01

Colorectal cancer remains the second leading cause of death in the United States despite improvements in incidence rates and advancements in screening. The present study evaluated the prognostic value of two tumor markers, MET and ROCK I, which have been noted in other cancers to provide more accurate prognoses of patient outcomes than tumor staging alone. We constructed a tissue microarray from surgical specimens of adenocarcinomas from 108 colorectal cancer patients. Using immunohistochemistry, we examined the expression levels of tumor markers MET and ROCK I, with a pathologist blinded to patient identities and clinical outcomes providing the scoring of MET and ROCK I expression. We then used retrospective analysis of patients' survival data to provide correlations with expression levels of MET and ROCK I. Both MET and ROCK I were significantly over-expressed in colorectal cancer tissues, relative to the unaffected adjacent mucosa. Kaplan-Meier survival analysis revealed that patients' 5-year survival was inversely correlated with levels of expression of ROCK I. In contrast, MET was less strongly correlated with five-year survival. ROCK I provides better efficacy in predicting patient outcomes, compared to either tumor staging or MET expression. As a result, ROCK I may provide a less invasive method of assessing patient prognoses and directing therapeutic interventions. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Impact of diabetes on oncologic outcome of colorectal cancer patients: colon vs. rectal cancer.

Directory of Open Access Journals (Sweden)

Justin Y Jeon

Full Text Available BACKGROUND: To evaluate the impact of diabetes on outcomes in colorectal cancer patients and to examine whether this association varies by the location of tumor (colon vs. rectum. PATIENTS AND METHODS: This study includes 4,131 stage I-III colorectal cancer patients, treated between 1995 and 2007 (12.5% diabetic, 53% colon, 47% rectal in South Korea. Cox proportional hazards modeling was used to determine the prognostic influence of DM on survival endpoints. RESULTS: Colorectal cancer patients with DM had significantly worse disease-free survival (DFS [hazard ratio (HR 1.17, 95% confidence interval (CI: 1.00-1.37] compared with patients without DM. When considering colon and rectal cancer independently, DM was significantly associated with worse overall survival (OS (HR: 1.46, 95% CI: 1.11-1.92, DFS (HR: 1.45, 95% CI: 1.15-1.84 and recurrence-free survival (RFS (HR: 1.32, 95% CI: 0.98-1.76 in colon cancer patients. No association for OS, DFS or RFS was observed in rectal cancer patients. There was significant interaction of location of tumor (colon vs. rectal cancer with DM on OS (P = 0.009 and DFS (P = 0.007. CONCLUSIONS: This study suggests that DM negatively impacts survival outcomes of patients with colon cancer but not rectal cancer.
Presentation patterns and outcomes of patients with cancer accessing care in emergency departments in Victoria, Australia.

Science.gov (United States)

van der Meer, Dania M; Weiland, Tracey J; Philip, Jennifer; Jelinek, George A; Boughey, Mark; Knott, Jonathan; Marck, Claudia H; Weil, Jennifer L; Lane, Heather P; Dowling, Anthony J; Kelly, Anne-Maree

2016-03-01

People with cancer attend emergency departments (EDs) for many reasons. Improved understanding of the specific needs of these patients may assist in optimizing health service delivery. ED presentation and hospital utilization characteristics were explored for people with cancer and compared with those patients without cancer. This descriptive, retrospective, multicentre cohort study used hospital administrative data. Descriptive and inferential statistics were used to summarise and compare ED presentation characteristics amongst cancer and non-cancer groups. Predictive analyses were used to identify ED presentation features predictive of hospital admission for cancer patients. Outcomes of interest were level of acuity, ED and inpatient length of stay, re-presentation rates and admission rates amongst cancer patients and non-cancer patients. ED (529,377) presentations occurred over the 36 months, of which 2.4% (n = 12,489) were cancer-related. Compared with all other attendances, cancer-related attendances had a higher level of acuity, requiring longer management time and length of stay in ED. Re-presentation rates for people with cancer were nearly double those of others (64 vs 33%, p < 0.001), with twice the rate of hospital admission (90 vs 46%, p < 0.001), longer inpatient length of stay (5.6 vs 2.8 days, p < 0.001) and had higher inpatient mortality (7.9 vs 1.0%, p < 0.001). Acuity and arriving by ambulance were significant predictors of hospital admission, with cancer-related attendances having ten times the odds of admission compared to other attendances (OR = 10.4, 95% CI 9.8-11.1). ED presentations by people with cancer represent a more urgent, complex caseload frequently requiring hospital admission when compared to other presentations, suggesting that for optimal cancer care, close collaboration and integration of oncology, palliative care and emergency medicine providers are needed to improve pathways of care.
Is there any role of positron emission tomography computed tomography for predicting resectability of gallbladder cancer?

Science.gov (United States)

Kim, Jaihwan; Ryu, Ji Kon; Kim, Chulhan; Paeng, Jin Chul; Kim, Yong-Tae

2014-05-01

The role of integrated (18)F-2-fluoro-2-deoxy-D-glucose positron emission tomography computed tomography (PET-CT) is uncertain in gallbladder cancer. The aim of this study was to show the role of PET-CT in gallbladder cancer patients. Fifty-three patients with gallbladder cancer underwent preoperative computed tomography (CT) and PET-CT scans. Their medical records were retrospectively reviewed. Twenty-six patients underwent resection. Based on the final outcomes, PET-CT was in good agreement (0.61 to 0.80) with resectability whereas CT was in acceptable agreement (0.41 to 0.60) with resectability. When the diagnostic accuracy of the predictions for resectability was calculated with the ROC curve, the accuracy of PET-CT was higher than that of CT in patients who underwent surgical resection (P=0.03), however, there was no difference with all patients (P=0.12). CT and PET-CT had a discrepancy in assessing curative resection in nine patients. These consisted of two false negative and four false positive CT results (11.3%) and three false negative PET-CT results (5.1%). PET-CT was in good agreement with the final outcomes compared to CT. As a complementary role of PEC-CT to CT, PET-CT tended to show better prediction about resectability than CT, especially due to unexpected distant metastasis.
Breast cancer risk factors and outcome: a global perspective

NARCIS (Netherlands)

Bhoo Pathy, N.

2011-01-01

The burden of breast cancer had been increasing in Asia. However, little is known regarding the presentation, management and outcome of breast cancer among multi-ethnic Asian women. Asian ethnicities, lifestyles, health beliefs, and even life expectancies are substantially different from those of
SVM and SVM Ensembles in Breast Cancer Prediction.

Science.gov (United States)

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.
SVM and SVM Ensembles in Breast Cancer Prediction.

Directory of Open Access Journals (Sweden)

Min-Wei Huang

Full Text Available Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.
Preoperative computed tomography of the chest in lung cancer patients: the predictive value of calcified lymph nodes for the perioperative outcomes of video-assisted thoracoscopic surgery lobectomy

Energy Technology Data Exchange (ETDEWEB)

Jin, Kwang Nam; Lee, Youkyung; Wi, Jae Yeon [Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Department of Radiology, Seoul (Korea, Republic of); Moon, Hyeon-Jong; Sung, Yong Won [Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Department of Cardiothoracic Surgery, Seoul (Korea, Republic of)

2013-12-15

To determine the predictive value of identifying calcified lymph nodes (LNs) for the perioperative outcomes of video-assisted thoracoscopic surgery (VATS). Fifty-six consecutive patients who underwent VATS lobectomy for lung cancer were included. We evaluated the number and location of calcified LNs on computed tomography (CT). We investigated clinical parameters, including percentage forced expiratory volume in 1 s (FEV{sub 1}%), surgery duration, chest tube indwelling duration, and length of hospital stay. We performed linear regression analysis and multiple comparisons of perioperative outcomes. Mean number of calcified LNs per patient was 0.9 (range, 0-6), mostly located in the hilar-interlobar zone (43.8 %). For surgery duration (mean, 5.0 h), FEV{sub 1}% and emphysema severity were independent predictors (P = 0.010 and 0.003, respectively). The number of calcified LNs was an independent predictor for chest tube indwelling duration (P = 0.030) and length of hospital stay (P = 0.046). Mean duration of chest tube indwelling and hospital stay was 8.8 days and 12.7 days in no calcified LN group; 9.2 and 13.2 in 1 calcified LN group; 12.8 and 19.7 in {>=}2 calcified LNs group, respectively. The presence of calcified LNs on CT can help predict more complicated perioperative course following VATS lobectomy. (orig.)
Module-Based Outcome Prediction Using Breast Cancer Compendia

NARCIS (Netherlands)

Van Vliet, M.H.; Klijn, C.N.; Wessels, L.F.; Reinders, M.J.T.

2007-01-01

Background. The availability of large collections of microarray datasets (compendia), or knowledge about grouping of genes into pathways (gene sets), is typically not exploited when training predictors of disease outcome. These can be useful since a compendium increases the number of samples, while
Machine Learning and Neurosurgical Outcome Prediction: A Systematic Review.

Science.gov (United States)

Senders, Joeky T; Staples, Patrick C; Karhade, Aditya V; Zaki, Mark M; Gormley, William B; Broekman, Marike L D; Smith, Timothy R; Arnaout, Omar

2018-01-01

Accurate measurement of surgical outcomes is highly desirable to optimize surgical decision-making. An important element of surgical decision making is identification of the patient cohort that will benefit from surgery before the intervention. Machine learning (ML) enables computers to learn from previous data to make accurate predictions on new data. In this systematic review, we evaluate the potential of ML for neurosurgical outcome prediction. A systematic search in the PubMed and Embase databases was performed to identify all potential relevant studies up to January 1, 2017. Thirty studies were identified that evaluated ML algorithms used as prediction models for survival, recurrence, symptom improvement, and adverse events in patients undergoing surgery for epilepsy, brain tumor, spinal lesions, neurovascular disease, movement disorders, traumatic brain injury, and hydrocephalus. Depending on the specific prediction task evaluated and the type of input features included, ML models predicted outcomes after neurosurgery with a median accuracy and area under the receiver operating curve of 94.5% and 0.83, respectively. Compared with logistic regression, ML models performed significantly better and showed a median absolute improvement in accuracy and area under the receiver operating curve of 15% and 0.06, respectively. Some studies also demonstrated a better performance in ML models compared with established prognostic indices and clinical experts. In the research setting, ML has been studied extensively, demonstrating an excellent performance in outcome prediction for a wide range of neurosurgical conditions. However, future studies should investigate how ML can be implemented as a practical tool supporting neurosurgical care. Copyright © 2017 Elsevier Inc. All rights reserved.
Cancer-related symptoms predict psychological wellbeing among prostate cancer survivors: results from the PiCTure study.

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Sharp, Linda; O'Leary, Eamonn; Kinnear, Heather; Gavin, Anna; Drummond, Frances J

2016-03-01

Prostate cancer treatments are associated with a range of symptoms and physical side-effects. Cancer can also adversely impact on psychological wellbeing. Because many prostate cancer-related symptoms and side-effects are potentially modifiable, we investigated associations between symptoms and psychological wellbeing among prostate cancer survivors. Postal questionnaires were distributed to men diagnosed with prostate cancer 2-18 years previously identified through cancer registries. General and prostate cancer-specific symptoms were assessed using the EORTC QLQ-C30 and QLQ-PR25, with higher symptom scores indicating more/worse symptomatology. Psychological wellbeing was assessed by the DASS-21. Associations between symptoms and each outcome were investigated using multivariate logistic regression, controlling for socio-demographic and clinical factors. A total 3348 men participated (response rate = 54%). Seventeen percent (95%CI 15.2%-17.9%), 16% (95%CI 15.1%-17.8%) and 11% (95%CI 9.5%-11.8%) of survivors scored in the range for depression, anxiety and distress on the DASS scales, respectively. In multivariate models, risk of depression on the DASS scale was significantly higher in men with higher urinary and androgen deprivation therapy (ADT)-related symptoms, and higher scores for fatigue, insomnia and financial difficulties. Risk of anxiety on the DASS scale was higher in men with higher scores for urinary, bowel and ADT-related symptoms and fatigue, dyspnoea and financial difficulties. Risk of distress on the DASS scale was positively associated with urinary, bowel and ADT-related symptoms, fatigue, insomnia and financial difficulties. Cancer-related symptoms significantly predict psychological wellbeing among prostate cancer survivors. Greater use of interventions and medications and to alleviate symptoms might improve psychological wellbeing of prostate cancer survivors. Copyright © 2015 John Wiley & Sons, Ltd.
Predicting sports betting outcomes

OpenAIRE

Flis, Borut

2014-01-01

We wish to build a model, which could predict the outcome of basketball games. The goal was to achieve an sufficient enough accuracy to make a profit in sports betting. One learning example is a game in the NBA regular season. Every example has multiple features, which describe the opposing teams. We tried many methods, which return the probability of the home team winning and the probability of the away team winning. These probabilities are used for risk analysis. We used the best model in h...
Comparison of Physician-Predicted to Measured Low Vision Outcomes

Science.gov (United States)

Chan, Tiffany L.; Goldstein, Judith E.; Massof, Robert W.

2013-01-01

Purpose To compare low vision rehabilitation (LVR) physicians’ predictions of the probability of success of LVR to patients’ self-reported outcomes after provision of usual outpatient LVR services; and to determine if patients’ traits influence physician ratings. Methods The Activity Inventory (AI), a self-report visual function questionnaire, was administered pre and post-LVR to 316 low vision patients served by 28 LVR centers that participated in a collaborative observational study. The physical component of the Short Form-36, Geriatric Depression Scale, and Telephone Interview for Cognitive Status were also administered pre-LVR to measure physical capability, depression and cognitive status. Following patient evaluation, 38 LVR physicians estimated the probability of outcome success (POS), using their own criteria. The POS ratings and change in functional ability were used to assess the effects of patients’ baseline traits on predicted outcomes. Results A regression analysis with a hierarchical random effects model showed no relationship between LVR physician POS estimates and AI-based outcomes. In another analysis, Kappa statistics were calculated to determine the probability of agreement between POS and AI-based outcomes for different outcome criteria. Across all comparisons, none of the kappa values were significantly different from 0, which indicates the rate of agreement is equivalent to chance. In an exploratory analysis, hierarchical mixed effects regression models show that POS ratings are associated with information about the patient’s cognitive functioning and the combination of visual acuity and functional ability, as opposed to visual acuity or functional ability alone. Conclusions Physicians’ predictions of LVR outcomes appear to be influenced by knowledge of patients’ cognitive functioning and the combination of visual acuity and functional ability - information physicians acquire from the patient’s history and examination. However
Outcome manipulation in corporate prediction markets

DEFF Research Database (Denmark)

Ottaviani, Marco; Sørensen, Peter Norman

2007-01-01

This paper presents a framework for applying prediction markets to corporate decision-making. The analysis is motivated by the recent surge of interest in markets as information aggregation devices and their potential use within firms. We characterize the amount of outcome manipulation that results...
Serum protein profiling using an aptamer array predicts clinical outcomes of stage IIA colon cancer: A leave-one-out crossvalidation

Science.gov (United States)

Huh, Jung Wook; Kim, Sung Chun; Sohn, Insuk; Jung, Sin-Ho; Kim, Hee Cheol

2016-01-01

Background In this study, we established and validated a model for predicting prognosis of stage IIA colon cancer patients based on expression profiles of aptamers in serum. Methods Bloods samples were collected from 227 consecutive patients with pathologic T3N0M0 (stage IIA) colon cancer. We incubated 1,149 serum molecule-binding aptamer pools of clinical significance with serum from patients to obtain aptamers bound to serum molecules, which were then amplified and marked. Oligonucleotide arrays were constructed with the base sequences of the 1,149 aptamers, and the marked products identified above were reacted with one another to produce profiles of the aptamers bound to serum molecules. These profiles were organized into low- and high-risk groups of colon cancer patients based on clinical information for the serum samples. Cox proportional hazards model and leave-one-out cross-validation (LOOCV) were used to evaluate predictive performance. Results During a median follow-up period of 5 years, 29 of the 227 patients (11.9%) experienced recurrence. There were 212 patients (93.4%) in the low-risk group and 15 patients (6.6%) in the high-risk group in our aptamer prognosis model. Postoperative recurrence significantly correlated with age and aptamer risk stratification (p = 0.046 and p = 0.001, respectively). In multivariate analysis, aptamer risk stratification (p recurrence. Disease-free survival curves calculated according to aptamer risk level predicted through a LOOCV procedure and age showed significant differences (p < 0.001 from permutations). Conclusion Aptamer risk stratification can be a valuable prognostic factor in stage II colon cancer patients. PMID:26908450
Blood biomarkers are helpful in the prediction of response to chemoradiation in rectal cancer: A prospective, hypothesis driven study on patients with locally advanced rectal cancer

International Nuclear Information System (INIS)

Buijsen, Jeroen; Stiphout, Ruud G. van; Menheere, Paul P.C.A.; Lammering, Guido; Lambin, Philippe

2014-01-01

Purpose/objective: Chemoradiation (CRT) has been shown to lead to downsizing of an important portion of rectal cancers. In order to tailor treatment at an earlier stage during treatment, predictive models are being developed. Adding blood biomarkers may be attractive for prediction, as they can be collected very easily and determined with excellent reproducibility in clinical practice. The hypothesis of this study was that blood biomarkers related to tumor load, hypoxia and inflammation can help to predict response to CRT in rectal cancer. Material/methods: 295 patients with locally advanced rectal cancer who were planned to undergo CRT were prospectively entered into a biobank protocol ( (NCT01067872)). Blood samples were drawn before start of CRT. Nine biomarkers were selected, based on a previously defined hypothesis, and measured in a standardized way by a certified lab: CEA, CA19-9, LDH, CRP, IL-6, IL-8, CA IX, osteopontin and 25-OH-vitamin D. Outcome was analyzed in two ways: pCR vs. non-pCR and responders (defined as ypT0-2N0) vs. non-responders (all other ypTN stages). Results: 276 patients could be analyzed. 20.7% developed a pCR and 47.1% were classified as responders. In univariate analysis CEA (p = 0.001) and osteopontin (p = 0.012) were significant predictors for pCR. Taking response as outcome CEA (p < 0.001), IL-8 (p < 0.001) and osteopontin (p = 0.004) were significant predictors. In multivariate analysis CEA was the strongest predictor for pCR (OR 0.92, p = 0.019) and CEA and IL-8 predicted for response (OR 0.97, p = 0.029 and OR 0.94, p = 0.036). The model based on biomarkers only had an AUC of 0.65 for pCR and 0.68 for response; the strongest model included clinical data, PET-data and biomarkers and had an AUC of 0.81 for pCR and 0.78 for response. Conclusion: CEA and IL-8 were identified as predictive biomarkers for tumor response and PCR after CRT in rectal cancer. Incorporation of these blood biomarkers leads to an additional accuracy of
Gene Expression Profiles for Predicting Metastasis in Breast Cancer: A Cross-Study Comparison of Classification Methods

Directory of Open Access Journals (Sweden)

Mark Burton

2012-01-01

Full Text Available Machine learning has increasingly been used with microarray gene expression data and for the development of classifiers using a variety of methods. However, method comparisons in cross-study datasets are very scarce. This study compares the performance of seven classification methods and the effect of voting for predicting metastasis outcome in breast cancer patients, in three situations: within the same dataset or across datasets on similar or dissimilar microarray platforms. Combining classification results from seven classifiers into one voting decision performed significantly better during internal validation as well as external validation in similar microarray platforms than the underlying classification methods. When validating between different microarray platforms, random forest, another voting-based method, proved to be the best performing method. We conclude that voting based classifiers provided an advantage with respect to classifying metastasis outcome in breast cancer patients.
Core Outcomes for Colorectal Cancer Surgery: A Consensus Study.

Directory of Open Access Journals (Sweden)

Angus G K McNair

2016-08-01

Full Text Available Colorectal cancer (CRC is a major cause of worldwide morbidity and mortality. Surgical treatment is common, and there is a great need to improve the delivery of such care. The gold standard for evaluating surgery is within well-designed randomized controlled trials (RCTs; however, the impact of RCTs is diminished by a lack of coordinated outcome measurement and reporting. A solution to these issues is to develop an agreed standard "core" set of outcomes to be measured in all trials to facilitate cross-study comparisons, meta-analysis, and minimize outcome reporting bias. This study defines a core outcome set for CRC surgery.The scope of this COS includes clinical effectiveness trials of surgical interventions for colorectal cancer. Excluded were nonsurgical oncological interventions. Potential outcomes of importance to patients and professionals were identified through systematic literature reviews and patient interviews. All outcomes were transcribed verbatim and categorized into domains by two independent researchers. This informed a questionnaire survey that asked stakeholders (patients and professionals from United Kingdom CRC centers to rate the importance of each domain. Respondents were resurveyed following group feedback (Delphi methods. Outcomes rated as less important were discarded after each survey round according to predefined criteria, and remaining outcomes were considered at three consensus meetings; two involving international professionals and a separate one with patients. A modified nominal group technique was used to gain the final consensus. Data sources identified 1,216 outcomes of CRC surgery that informed a 91 domain questionnaire. First round questionnaires were returned from 63 out of 81 (78% centers, including 90 professionals, and 97 out of 267 (35% patients. Second round response rates were high for all stakeholders (>80%. Analysis of responses lead to 45 and 23 outcome domains being retained after the first and
Combining Pathway Identification and Breast Cancer Survival Prediction via Screening-Network Methods

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Antonella Iuliano

2018-06-01

Full Text Available Breast cancer is one of the most common invasive tumors causing high mortality among women. It is characterized by high heterogeneity regarding its biological and clinical characteristics. Several high-throughput assays have been used to collect genome-wide information for many patients in large collaborative studies. This knowledge has improved our understanding of its biology and led to new methods of diagnosing and treating the disease. In particular, system biology has become a valid approach to obtain better insights into breast cancer biological mechanisms. A crucial component of current research lies in identifying novel biomarkers that can be predictive for breast cancer patient prognosis on the basis of the molecular signature of the tumor sample. However, the high dimension and low sample size of data greatly increase the difficulty of cancer survival analysis demanding for the development of ad-hoc statistical methods. In this work, we propose novel screening-network methods that predict patient survival outcome by screening key survival-related genes and we assess the capability of the proposed approaches using METABRIC dataset. In particular, we first identify a subset of genes by using variable screening techniques on gene expression data. Then, we perform Cox regression analysis by incorporating network information associated with the selected subset of genes. The novelty of this work consists in the improved prediction of survival responses due to the different types of screenings (i.e., a biomedical-driven, data-driven and a combination of the two before building the network-penalized model. Indeed, the combination of the two screening approaches allows us to use the available biological knowledge on breast cancer and complement it with additional information emerging from the data used for the analysis. Moreover, we also illustrate how to extend the proposed approaches to integrate an additional omic layer, such as copy number
Predictive values of symptoms in relation to cancer diagnosis

DEFF Research Database (Denmark)

Krasnik, Ivan; Andersen, John Sahl

a manual describing the symptoms that should engender reasonable suspicion of malignancy (“alarm symptoms”) to the general practitioner. Objectives: To investigate the evidence in the literature of the predictive value (PPV) placed on the”alarm symptoms” for colon cancer, breast cancer, prostate cancer...... years (6,6%-21,2%), but much lower in younger age groups. ”Change in bowel habits” and ”Significant general symptoms” are more uncertain (3,5%-8,5%). Breast cancer: ”Palpable suspect tumor” is well supported (8,1%-24%). The predictive value of ”Pitting of the skin”, ”Papil-areola eczema......Background/significance: Poorer prognosis for cancer patients in Denmark than in comparable countries has been shown and contributed to the introduction of accelerated diagnostic trajectories for patients suspicious for cancer in 2008. For all types of cancers the National Board of Health developed...
Epidural analgesia during open radical prostatectomy does not improve long-term cancer-related outcome: a retrospective study in patients with advanced prostate cancer.

Directory of Open Access Journals (Sweden)

Patrick Y Wuethrich

Full Text Available BACKGROUND: A beneficial effect of regional anesthesia on cancer related outcome in various solid tumors has been proposed. The data on prostate cancer is conflicting and reports on long-term cancer specific survival are lacking. METHODS: In a retrospective, single-center study, outcomes of 148 consecutive patients with locally advanced prostate cancer pT3/4 who underwent retropubic radical prostatectomy (RRP with general anesthesia combined with intra- and postoperative epidural analgesia (n=67 or with postoperative ketorolac-morphine analgesia (n=81 were reviewed. The median observation time was 14.00 years (range 10.87-17.75 yrs. Biochemical recurrence (BCR-free, local and distant recurrence-free, cancer-specific, and overall survival were estimated using the Kaplan-Meier technique. Multivariate Cox proportional-hazards regression models were used to analyze clinicopathologic variables associated with disease progression and death. RESULTS: The survival estimates for BCR-free, local and distant recurrence-free, cancer-specific survival and overall survival did not differ between the two groups (P=0.64, P=0.75, P=0.18, P=0.32 and P=0.07. For both groups, higher preoperative PSA (hazard ratio (HR 1.02, 95% confidence interval (CI 1.01-1.02, P<0.0001, increased specimen Gleason score (HR 1.24, 95% CI 1.06-1.46, P=0.007 and positive nodal status (HR 1.66, 95% CI 1.03-2.67, P=0.04 were associated with higher risk of BCR. Increased specimen Gleason score predicted death from prostate cancer (HR 2.46, 95% CI 1.65-3.68, P<0.0001. CONCLUSIONS: General anaesthesia combined with epidural analgesia did not reduce the risk of cancer progression or improve survival after RRP for prostate cancer in this group of patients at high risk for disease progression with a median observation time of 14.00 yrs.

Prediction of processing tomato peeling outcomes

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Peeling outcomes of processing tomatoes were predicted using multivariate analysis of Magnetic Resonance (MR) images. Tomatoes were obtained from a whole-peel production line. Each fruit was imaged using a 7 Tesla MR system, and a multivariate data set was created from 28 different images. After ...
Mucinous Histology Signifies Poor Oncologic Outcome in Young Patients With Colorectal Cancer.

Science.gov (United States)

Soliman, Basem G; Karagkounis, Georgios; Church, James M; Plesec, Thomas; Kalady, Matthew F

2018-05-01

The incidence of colorectal cancer in the young (under age 40) is increasing, and this population has worse oncologic outcomes. Mucinous histology is a potential prognostic factor in colorectal cancer, but has not been evaluated specifically in young patients. The objective of the study was to determine factors associated with poor outcome in young patients with colorectal cancer (≤40 years) and to determine relationships between mucinous histology and oncologic outcomes in this population. This is a retrospective study. Patients from a single-institution tertiary care center were studied. A total of 224 patients with colorectal cancer under 40 years of age diagnosed between 1990 and 2010 were included (mean age, 34.7 years; 51.3% female). 34 patients (15.2%) had mucinous histology. There were no interventions. Oncologic outcomes were analyzed according to the presence of mucinous histology. The mucinous and nonmucin colorectal cancer study populations were statistically similar in age, sex, tumor location, pathological stage, differentiation, and adjuvant chemotherapy use. Five-year disease-free survival was 29.1% versus 71.3% (p colorectal cancers recurred earlier at a median time of 36.4 months versus 94.2 months for nonmucin colorectal cancers (p colorectal cancer. This is associated with early and high recurrence rates, despite use of standard neoadjuvant and adjuvant regimens. Physicians need to be aware of this association and potentially explore novel treatment options. See Video Abstract at http://links.lww.com/DCR/A575.
Area-level variations in cancer care and outcomes.

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Keating, Nancy L; Landrum, Mary Beth; Lamont, Elizabeth B; Bozeman, Samuel R; McNeil, Barbara J

2012-05-01

: Substantial regional variations in health-care spending exist across the United States; yet, care and outcomes are not better in higher-spending areas. Most studies have focused on care in fee-for-service Medicare; whether spillover effects exist in settings without financial incentives for more care is unknown. : We studied care for cancer patients in fee-for-service Medicare and the Veterans Health Administration (VA) to understand whether processes and outcomes of care vary with area-level Medicare spending. : An observational study using logistic regression to assess care by area-level measures of Medicare spending. : Patients with lung, colorectal, or prostate cancers diagnosed during 2001-2004 in Surveillance, Epidemiology, and End Results (SEER) areas or the VA. The SEER cohort included fee-for-service Medicare patients aged older than 65 years. : Recommended and preference-sensitive cancer care and mortality. : In fee-for-service Medicare, higher-spending areas had higher rates of recommended care (curative surgery and adjuvant chemotherapy for early-stage non-small-cell lung cancer and chemotherapy for stage III colon cancer) and preference-sensitive care (chemotherapy for stage IV lung and colon cancer and primary treatment of local/regional prostate cancer) and had lower lung cancer mortality. In the VA, we observed minimal variation in care by area-level Medicare spending. : Our findings suggest that intensity of care for Medicare beneficiaries is not driving variations in VA care, despite some overlap in physician networks. Although the Dartmouth Atlas work has been of unprecedented importance in demonstrating variations in Medicare spending, new measures may be needed to better understand variations in other populations.
Procalcitonin Improves the Glasgow Prognostic Score for Outcome Prediction in Emergency Patients with Cancer: A Cohort Study

Directory of Open Access Journals (Sweden)

Anna Christina Rast

2015-01-01

Full Text Available The Glasgow Prognostic Score (GPS is useful for predicting long-term mortality in cancer patients. Our aim was to validate the GPS in ED patients with different cancer-related urgency and investigate whether biomarkers would improve its accuracy. We followed consecutive medical patients presenting with a cancer-related medical urgency to a tertiary care hospital in Switzerland. Upon admission, we measured procalcitonin (PCT, white blood cell count, urea, 25-hydroxyvitamin D, corrected calcium, C-reactive protein, and albumin and calculated the GPS. Of 341 included patients (median age 68 years, 61% males, 81 (23.8% died within 30 days after admission. The GPS showed moderate prognostic accuracy (AUC 0.67 for mortality. Among the different biomarkers, PCT provided the highest prognostic accuracy (odds ratio 1.6 (95% confidence interval 1.3 to 1.9, P<0.001, AUC 0.69 and significantly improved the GPS to a combined AUC of 0.74 (P=0.007. Considering all investigated biomarkers, the AUC increased to 0.76 (P<0.001. The GPS performance was significantly improved by the addition of PCT and other biomarkers for risk stratification in ED cancer patients. The benefit of early risk stratification by the GPS in combination with biomarkers from different pathways should be investigated in further interventional trials.
Predicting outcome of acute kidney transplant rejection using

NARCIS (Netherlands)

Rekers, Niels Vincent

2014-01-01

Acute kidney transplant rejection is an important risk factors for adverse graft outcome. Once diagnosed, it remains difficult to predict the risk of graft loss and the response to anti-rejection treatment. The aim of this thesis was to identify biomarkers during acute rejection, which predict the
Tumor stromal vascular endothelial growth factor A is predictive of poor outcome in inflammatory breast cancer

International Nuclear Information System (INIS)

Arias-Pulido, Hugo; Chaher, Nabila; Gong, Yun; Qualls, Clifford; Vargas, Jake; Royce, Melanie

2012-01-01

Inflammatory breast cancer (IBC) is a highly angiogenic disease; thus, antiangiogenic therapy should result in a clinical response. However, clinical trials have demonstrated only modest responses, and the reasons for these outcomes remain unknown. Therefore, the purpose of this retrospective study was to determine the prognostic value of protein levels of vascular endothelial growth factor (VEGF-A), one of the main targets of antiangiogenic therapy, and its receptors (VEGF-R1 and -R2) in IBC tumor specimens. Specimens from IBC and normal breast tissues were obtained from Algerian patients. Tumor epithelial and stromal staining of VEGF-A, VEGF-R1, and VEGF-R2 was evaluated by immunohistochemical analysis in tumors and normal breast tissues; this expression was correlated with clinicopathological variables and breast cancer-specific survival (BCSS) and disease-free survival (DFS) duration. From a set of 117 IBC samples, we evaluated 103 ductal IBC tissues and 25 normal specimens. Significantly lower epithelial VEGF-A immunostaining was found in IBC tumor cells than in normal breast tissues (P <0.01), cytoplasmic VEGF-R1 and nuclear VEGF-R2 levels were slightly higher, and cytoplasmic VEGF-R2 levels were significantly higher (P = 0.04). Sixty-two percent of IBC tumors had high stromal VEGF-A expression. In univariate analysis, stromal VEGF-A levels predicted BCSS and DFS in IBC patients with estrogen receptor-positive (P <0.01 for both), progesterone receptor-positive (P = 0.04 and P = 0.03), HER2+ (P = 0.04 and P = 0.03), and lymph node involvement (P <0.01 for both). Strikingly, in a multivariate analysis, tumor stromal VEGF-A was identified as an independent predictor of poor BCSS (hazard ratio [HR]: 5.0; 95% CI: 2.0-12.3; P <0.01) and DFS (HR: 4.2; 95% CI: 1.7-10.3; P <0.01). To our knowledge, this is the first study to demonstrate that tumor stromal VEGF-A expression is a valuable prognostic indicator of BCSS and DFS at diagnosis and can therefore be used to
Prediction of lung cancer patient survival via supervised machine learning classification techniques.

Science.gov (United States)

Lynch, Chip M; Abdollahi, Behnaz; Fuqua, Joshua D; de Carlo, Alexandra R; Bartholomai, James A; Balgemann, Rayeanne N; van Berkel, Victor H; Frieboes, Hermann B

2017-12-01

Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not well understood which types of techniques would yield more predictive information, and which data attributes should be used in order to determine this information. In this study, a number of supervised learning techniques is applied to the SEER database to classify lung cancer patients in terms of survival, including linear regression, Decision Trees, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), and a custom ensemble. Key data attributes in applying these methods include tumor grade, tumor size, gender, age, stage, and number of primaries, with the goal to enable comparison of predictive power between the various methods The prediction is treated like a continuous target, rather than a classification into categories, as a first step towards improving survival prediction. The results show that the predicted values agree with actual values for low to moderate survival times, which constitute the majority of the data. The best performing technique was the custom ensemble with a Root Mean Square Error (RMSE) value of 15.05. The most influential model within the custom ensemble was GBM, while Decision Trees may be inapplicable as it had too few discrete outputs. The results further show that among the five individual models generated, the most accurate was GBM with an RMSE value of 15.32. Although SVM underperformed with an RMSE value of 15.82, statistical analysis singles the SVM as the only model that generated a distinctive output. The results of the models are consistent with a classical Cox proportional hazards model used as a reference technique. We conclude that application of these supervised learning techniques to lung cancer data in the SEER database may be of use to estimate patient survival time
Yoga & Cancer Interventions: A Review of the Clinical Significance of Patient Reported Outcomes for Cancer Survivors

Directory of Open Access Journals (Sweden)

S. Nicole Culos-Reed

2012-01-01

Full Text Available Limited research suggests yoga may be a viable gentle physical activity option with a variety of health-related quality of life, psychosocial and symptom management benefits. The purpose of this review was to determine the clinical significance of patient-reported outcomes from yoga interventions conducted with cancer survivors. A total of 25 published yoga intervention studies for cancer survivors from 2004–2011 had patient-reported outcomes, including quality of life, psychosocial or symptom measures. Thirteen of these studies met the necessary criteria to assess clinical significance. Clinical significance for each of the outcomes of interest was examined based on 1 standard error of the measurement, 0.5 standard deviation, and relative comparative effect sizes and their respective confidence intervals. This review describes in detail these patient-reported outcomes, how they were obtained, their relative clinical significance and implications for both clinical and research settings. Overall, clinically significant changes in patient-reported outcomes suggest that yoga interventions hold promise for improving cancer survivors' well-being. This research overview provides new directions for examining how clinical significance can provide a unique context for describing changes in patient-reported outcomes from yoga interventions. Researchers are encouraged to employ indices of clinical significance in the interpretation and discussion of results from yoga studies.
Pretreatment clinical findings predict outcome for patients receiving preoperative radiation for rectal cancer

International Nuclear Information System (INIS)

Myerson, Robert J.; Singh, Anurag; Birnbaum, Elisa H.; Fry, Robert D.; Fleshman, James W.; Kodner, Ira J.; Lockett, Mary Ann; Picus, Joel; Walz, Bruce J.; Read, Thomas E.

2001-01-01

adverse clinical factors were present: 0 for none, 1 for one or two, 2 for three or four. This sorted outcome highly significantly (p≤0.002, Tarone Ware), with 5-year LC/FFR of 98%/85% (score 0), 90%/72% (score 1), and 74%/58% (score 2). The scoring system sorts the data for both subgroups of surgeons; however, there are substantial differences in LC on the basis of the surgeon's experience. For colorectal specialists (251 cases), the 5-year LC is 100%, 94%, and 78% for scores of 0, 1, and 2, respectively (p=0.004). For the more mixed group of nonspecialist surgeons (133 cases), LC is 98%, 80%, and 65% for scores of 0, 1, and 2 (p=0.008). In multivariate analysis, the clinical score and surgeon's background retained independent predictive value, even when pathologic stage was included. Conclusions: For many patients with rectal cancer, adjuvant treatment can be administered in a well-tolerated sequential fashion--moderate doses of preoperative radiation followed by surgery followed by postoperative chemotherapy to address the risk of occult metastatic disease. A clinical scoring system has been presented here that would suggest that the local control is excellent for lesions with a score of 0 or (if the surgeon is experienced) 1, and therefore sequential treatment could be considered. Cases with a clinical score of 2 should be strongly considered for protocols evaluating more aggressive preoperative treatment, such as combined modality preoperative treatment
PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

Science.gov (United States)

Wishart, Gordon C; Azzato, Elizabeth M; Greenberg, David C; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D P

2010-01-01

The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Differences in overall actual and predicted mortality were detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.
MicroRNAs as biomarkers for early breast cancer diagnosis, prognosis and therapy prediction.

Science.gov (United States)

Nassar, Farah J; Nasr, Rihab; Talhouk, Rabih

2017-04-01

Breast cancer is a major health problem that affects one in eight women worldwide. As such, detecting breast cancer at an early stage anticipates better disease outcome and prolonged patient survival. Extensive research has shown that microRNA (miRNA) are dysregulated at all stages of breast cancer. miRNA are a class of small noncoding RNA molecules that can modulate gene expression and are easily accessible and quantifiable. This review highlights miRNA as diagnostic, prognostic and therapy predictive biomarkers for early breast cancer with an emphasis on the latter. It also examines the challenges that lie ahead in their use as biomarkers. Noteworthy, this review addresses miRNAs reported in patients with early breast cancer prior to chemotherapy, radiotherapy, surgical procedures or distant metastasis (unless indicated otherwise). In this context, miRNA that are mentioned in this review were significantly modulated using more than one statistical test and/or validated by at least two studies. A standardized protocol for miRNA assessment is proposed starting from sample collection to data analysis that ensures comparative analysis of data and reproducibility of results. Copyright © 2016 Elsevier Inc. All rights reserved.
Prediction of Bladder Cancer Recurrences Using Artificial Neural Networks

Science.gov (United States)

Zulueta Guerrero, Ekaitz; Garay, Naiara Telleria; Lopez-Guede, Jose Manuel; Vilches, Borja Ayerdi; Iragorri, Eider Egilegor; Castaños, David Lecumberri; de La Hoz Rastrollo, Ana Belén; Peña, Carlos Pertusa

Even if considerable advances have been made in the field of early diagnosis, there is no simple, cheap and non-invasive method that can be applied to the clinical monitorisation of bladder cancer patients. Moreover, bladder cancer recurrences or the reappearance of the tumour after its surgical resection cannot be predicted in the current clinical setting. In this study, Artificial Neural Networks (ANN) were used to assess how different combinations of classical clinical parameters (stage-grade and age) and two urinary markers (growth factor and pro-inflammatory mediator) could predict post surgical recurrences in bladder cancer patients. Different ANN methods, input parameter combinations and recurrence related output variables were used and the resulting positive and negative prediction rates compared. MultiLayer Perceptron (MLP) was selected as the most predictive model and urinary markers showed the highest sensitivity, predicting correctly 50% of the patients that would recur in a 2 year follow-up period.
Gender and Bladder Cancer: A Collaborative Review of Etiology, Biology, and Outcomes.

Science.gov (United States)

Dobruch, Jakub; Daneshmand, Siamak; Fisch, Margit; Lotan, Yair; Noon, Aidan P; Resnick, Matthew J; Shariat, Shahrokh F; Zlotta, Alexandre R; Boorjian, Stephen A

2016-02-01

The incidence of bladder cancer is three to four times greater in men than in women. However, women are diagnosed with more advanced disease at presentation and have less favorable outcomes after treatment. To review the literature on potential biologic mechanisms underlying differential gender risk for bladder cancer, and evidence regarding gender disparities in bladder cancer presentation, management, and outcomes. A literature search of English-language publications that included an analysis of the association of gender with bladder cancer was performed using Pubmed. Ninety-seven articles were selected for analysis with the consensus of all authors. It has been shown that the gender difference in bladder cancer incidence is independent of differences in exposure risk, including smoking status. Potential molecular mechanisms include disparate metabolism of carcinogens by hepatic enzymes between men and women, resulting in differential exposure of the urothelium to carcinogens. In addition, the activity of the sex steroid hormone pathway may play a role in bladder cancer development, with demonstration that both androgens and estrogens have biologic effects in bladder cancer in vitro and in vivo. Importantly, gender differences exist in the timeliness and completeness of hematuria evaluation, with women experiencing a significantly greater delay in urologic referral and undergoing guideline-concordant imaging less frequently. Correspondingly, women have more advanced tumors at the time of bladder cancer diagnosis. Interestingly, higher cancer-specific mortality has been noted among women even after adjusting for tumor stage and treatment modality. Numerous potential biologic and epidemiologic factors probably underlie the gender differences observed for bladder cancer incidence, stage at diagnosis, and outcomes. Continued evaluation to define clinical applications for manipulation of the sex steroid pathway and to improve the standardization of hematuria
[Encopresis--predictive factors and outcome].

Science.gov (United States)

Mehler-Wex, Claudia; Scheuerpflug, Peter; Peschke, Nicole; Roth, Michael; Reitzle, Karl; Warnke, Andreas

2005-10-01

comparison of diagnostic, clinical and therapeutic features and their predictive value for the outcome of encopresis in children and adolescents. 85 children and adolescents (aged 9.6 +/- 3.2 years) with severe encopresis (ICD 10: F98.1) were investigated during inpatient treatment and 35 of them again 5.5 +/- 1.8 years later. Mentally retarded patients were excluded. Inpatient therapy consisted of treating constipation and/or stool regulation by means of laxatives, behavioural approaches, and the specific therapy of comorbid psychiatric disorders. During inpatient treatment 22% of the patients experienced total remission, 8% an unchanged persistence of symptoms. Of the 35 patients studied at follow-up 5.5 years later, 40% were symptom-free. As main result, prognostic outcome depended significantly on sufficient treatment of obstipation. Another important factor was the specific therapeutic approach to psychiatric comorbidity, especially to ADHD. The outcome for patients with comorbid ICD 10: F43 was significantly better than for the other patients. Those who were symptom-free at discharge had significantly better long-term outcomes. Decisive to the success of encopresis treatment were the stool regulation and the specific therapy of associated psychiatric illnesses, in particular of ADHD. Inpatient treatment revealed significantly better long-term outcomes where total remission had been achieved by the time of discharge from hospital.
FDG PET/CT radiomics for predicting the outcome of locally advanced rectal cancer

Energy Technology Data Exchange (ETDEWEB)

Lovinfosse, Pierre; Hustinx, Roland [University of Liege, Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics CHU, Liege (Belgium); Polus, Marc; Daele, Daniel van [Centre Hospitalier Universitaire de Liege, Department of Gastro-enterology, Liege (Belgium); Martinive, Philippe [CHU and University of Liege, Division of Radiation Oncology, Department of Medical Physics, Liege (Belgium); Daenen, Frederic [Centre Hospitalier Regional de la Citadelle, Department of Nuclear Medicine, Liege (Belgium); Hatt, Mathieu; Visvikis, Dimitris [LaTIM, INSERM UMR 1101, Brest (France); Koopmansch, Benjamin; Lambert, Frederic [UniLab Liege, Centre Hospitalier Universitaire de Liege, Center for Human Genetic, Molecular Haemato-Oncology Unit, Liege (Belgium); Coimbra, Carla [Centre Hospitalier Universitaire de Liege, Department of Abdominal Surgery and Transplantation, Liege (Belgium); Seidel, Laurence; Albert, Adelin [Centre Hospitalier Universitaire de Liege, Department of Biostatistics and Medico-economic Information, Liege (Belgium); Delvenne, Philippe [Centre Hospitalier Universitaire de Liege, Department of Pathology, Liege (Belgium)

2018-03-15

The aim of this study was to investigate the prognostic value of baseline {sup 18}F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC). Eighty-six patients with LARC underwent {sup 18}F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis. Logistic regression was used to predict the pathological response by the Dworak tumor regression grade (TRG) in the 66 patients treated with neoadjuvant chemoradiotherapy (nCRT). The median follow-up of patients was 41 months. Seventeen patients (19.7%) had recurrent disease and 18 (20.9 %) died, either due to cancer progression (n = 10) or from another cause while in complete remission (n = 8). DSS was 95% at 1 year, 93% at 2 years and 87% at 4 years. Weight loss, surgery and the texture parameter coarseness were significantly associated with DSS in multivariate analyses. DFS was 94 % at 1 year, 86 % at 2 years and 79 % at 4 years. From a multivariate standpoint, tumoral differentiation and the texture parameters homogeneity and coarseness were significantly associated with DFS. OS was 93% at 1 year, 87% at 2 years and 79% after 4 years. cT, surgery, SUVmean, dissimilarity and contrast from the neighborhood intensity-difference matrix (contrast{sub NGTDM}) were significantly and independently associated with OS. Finally, RAS-mutational status (KRAS and NRAS mutations) and TLG were significant predictors of pathological response to nCRT (TRG 3-4). Textural analysis of baseline {sup 18}F-FDG PET/CT provides strong independent predictors of survival in patients with LARC, with better predictive power than
Association Between Preoperative Nutritional Status and Postoperative Outcome in Head and Neck Cancer Patients.

Science.gov (United States)

Leung, John S L; Seto, Alfred; Li, George K H

2017-04-01

Head and neck cancer patients treated with surgery often experience significant postoperative morbidities. Administering preoperative nutritional intervention may improve surgical outcomes, but there is currently a paucity of data reviewing the association between preoperative nutritional status and postoperative outcome. It is therefore of importance to investigate this association among head and neck cancer patients. To assess the association between preoperative nutritional status and postoperative outcome in head and neck cancer patients treated with surgery, a retrospective study of 70 head and neck cancer patients who were surgically treated between 2013 and 2014 in a tertiary referral head and neck surgery center in Hong Kong was conducted. Clinical data regarding preoperative nutritional status and postoperative outcome were retrieved from a computer record system. Logistic and linear regressions were used to analyze the appropriate parameters. A higher preoperative albumin level was associated with lower rates of postoperative complications and better wound healing (P cancer patients, preoperative intervention strategies that boost albumin levels could be considered for improving surgical outcome.
Prostate cancer in Port Harcourt, Nigeria: features and outcome ...

African Journals Online (AJOL)

Background: To present the clinical features and outcome of management of patients with prostate cancer in Port Harcourt, Nigeria. Methods: A retrospective study of patients with prostate cancer managed in 14 years at the University of Port Harcourt Teaching Hospital. Results: Of 154,594 men above 40 years old who ...
Prostate Cancer Predictive Simulation Modelling, Assessing the Risk Technique (PCP-SMART): Introduction and Initial Clinical Efficacy Evaluation Data Presentation of a Simple Novel Mathematical Simulation Modelling Method, Devised to Predict the Outcome of Prostate Biopsy on an Individual Basis.

Science.gov (United States)

Spyropoulos, Evangelos; Kotsiris, Dimitrios; Spyropoulos, Katherine; Panagopoulos, Aggelos; Galanakis, Ioannis; Mavrikos, Stamatios

2017-02-01

We developed a mathematical "prostate cancer (PCa) conditions simulating" predictive model (PCP-SMART), from which we derived a novel PCa predictor (prostate cancer risk determinator [PCRD] index) and a PCa risk equation. We used these to estimate the probability of finding PCa on prostate biopsy, on an individual basis. A total of 371 men who had undergone transrectal ultrasound-guided prostate biopsy were enrolled in the present study. Given that PCa risk relates to the total prostate-specific antigen (tPSA) level, age, prostate volume, free PSA (fPSA), fPSA/tPSA ratio, and PSA density and that tPSA ≥ 50 ng/mL has a 98.5% positive predictive value for a PCa diagnosis, we hypothesized that correlating 2 variables composed of 3 ratios (1, tPSA/age; 2, tPSA/prostate volume; and 3, fPSA/tPSA; 1 variable including the patient's tPSA and the other, a tPSA value of 50 ng/mL) could operate as a PCa conditions imitating/simulating model. Linear regression analysis was used to derive the coefficient of determination (R 2 ), termed the PCRD index. To estimate the PCRD index's predictive validity, we used the χ 2 test, multiple logistic regression analysis with PCa risk equation formation, calculation of test performance characteristics, and area under the receiver operating characteristic curve analysis using SPSS, version 22 (P regression revealed the PCRD index as an independent PCa predictor, and the formulated risk equation was 91% accurate in predicting the probability of finding PCa. On the receiver operating characteristic analysis, the PCRD index (area under the curve, 0.926) significantly (P < .001) outperformed other, established PCa predictors. The PCRD index effectively predicted the prostate biopsy outcome, correctly identifying 9 of 10 men who were eventually diagnosed with PCa and correctly ruling out PCa for 9 of 10 men who did not have PCa. Its predictive power significantly outperformed established PCa predictors, and the formulated risk equation
Peritumoral eosinophils predict recurrence in colorectal cancer.

Science.gov (United States)

Harbaum, Lars; Pollheimer, Marion J; Kornprat, Peter; Lindtner, Richard A; Bokemeyer, Carsten; Langner, Cord

2015-03-01

In colorectal cancer, the presence and extent of eosinophil granulocyte infiltration may render important prognostic information. However, it remains unclear whether an increasing number of eosinophils might simply be linked to the overall inflammatory cell reaction or represent a self-contained, antitumoral mechanism that needs to be documented and promoted therapeutically. Peri- and intratumoral eosinophil counts were retrospectively assessed in 381 primary colorectal cancers from randomly selected patients. Tumors were diagnosed in American Joint Committee on Cancer (AJCC)/Union Internationale Contre le Cancer (UICC) stage I in 21%, stage II in 32%, stage III in 33%, and stage IV in 14%. Presence and extent of eosinophils was related to various histopathological parameters as well as patients' outcome. Overall, peri- and intratumoral eosinophils were observed in 86 and 75% cancer specimens. The peritumoral eosinophil count correlated strongly with the intratumoral eosinophil count (R=0.69; Peosinophil counts were significantly associated with lower T and N classification, better tumor differentiation, absence of vascular invasion, as well as improved progression-free and cancer-specific survival. However, only peritumoral eosinophils, but not intratumoral, were an independent prognosticator of favorable progression-free (hazard ratio 0.75; 95% confidence interval 0.58-0.98; P=0.04) and cancer-specific survival (hazard ratio 0.7; 95% confidence interval 0.52-0.93; P=0.01)-independent of the intensity of overall inflammatory cell reaction. This was also found for patients with AJCC/UICC stage II disease, wherein the presence of peritumoral eosinophils was significantly associated with favorable outcome. In conclusion, the number of peritumoral eosinophils had a significant favorable impact on prognosis of colorectal cancer patients independent of the overall tumor-associated inflammatory response. Evaluation of peritumoral eosinophils represents a promising
Long-Term Quality of Life Outcome After Proton Beam Monotherapy for Localized Prostate Cancer

Energy Technology Data Exchange (ETDEWEB)

Coen, John J., E-mail: jcoen@partners.org [Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Paly, Jonathan J.; Niemierko, Andrzej; Weyman, Elizabeth [Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Rodrigues, Anita [Department of Medical Oncology, Massachusetts General Hospital, Boston, MA (United States); Shipley, William U.; Zietman, Anthony L. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Talcott, James A. [Department of Medical Oncology, Massachusetts General Hospital, Boston, MA (United States)

2012-02-01

Objectives: High-dose external radiation for localized prostate cancer results in favorable clinical outcomes and low toxicity rates. Here, we report long-term quality of life (QOL) outcome for men treated with conformal protons. Methods: QOL questionnaires were sent at specified intervals to 95 men who received proton radiation. Of these, 87 men reported 3- and/or 12-month outcomes, whereas 73 also reported long-term outcomes (minimum 2 years). Symptom scores were calculated at baseline, 3 months, 12 months, and long-term follow-up. Generalized estimating equation models were constructed to assess longitudinal outcomes while accounting for correlation among repeated measures in an individual patient. Men were stratified into functional groups from their baseline questionnaires (normal, intermediate, or poor function) for each symptom domain. Long-term QOL changes were assessed overall and within functional groups using the Wilcoxon signed-rank test. Results: Statistically significant changes in all four symptom scores were observed in the longitudinal analysis. For the 73 men reporting long-term outcomes, there were significant change scores for incontinence (ID), bowel (BD) and sexual dysfunction (SD), but not obstructive/irritative voiding dysfunction (OID). When stratified by baseline functional category, only men with normal function had increased scores for ID and BD. For SD, there were significant changes in men with both normal and intermediate function, but not poor function. Conclusions: Patient reported outcomes are sensitive indicators of treatment-related morbidity. These results quantitate the long-term consequences of proton monotherapy for prostate cancer. Analysis by baseline functional category provides an individualized prediction of long-term QOL scores. High dose proton radiation was associated with small increases in bowel dysfunction and incontinence, with more pronounced changes in sexual dysfunction.

Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers.

Science.gov (United States)

Klimov, Sergey; Rida, Padmashree Cg; Aleskandarany, Mohammed A; Green, Andrew R; Ellis, Ian O; Janssen, Emiel Am; Rakha, Emad A; Aneja, Ritu

2017-09-05

Although distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most common underlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis. Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiple variables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed at identifying a biomarker signature to predict particular sites of DM in TNBC. A clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, to develop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasis to each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Cox univariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariable analyses. Our final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher risk of developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predicting site-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status. Our novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specific sites of metastasis, and potentially unravel biomarkers previously unknown in site tropism.
Negative predictive value of multiparametric MRI for prostate cancer detection: Outcome of 5-year follow-up in men with negative findings on initial MRI studies

Energy Technology Data Exchange (ETDEWEB)

Itatani, R., E-mail: banguliao@gmail.com [Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Kumamoto 860-8556 (Japan); Department of Radiology, Kumamoto Chuo Hospital, 1-5-1, Tainoshima, Kumamoto 862-0965 (Japan); Namimoto, T. [Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Kumamoto 860-8556 (Japan); Atsuji, S.; Katahira, K.; Morishita, S. [Department of Radiology, Kumamoto Chuo Hospital, 1-5-1, Tainoshima, Kumamoto 862-0965 (Japan); Kitani, K.; Hamada, Y. [Department of Urology, Kumamoto Chuo Hospital, 1-5-1, Tainoshima, Kumamoto 862-0965 (Japan); Kitaoka, M. [Department of Pathology, Kumamoto Chuo Hospital, 1-5-1, Tainoshima, Kumamoto 862-0965 (Japan); Nakaura, T. [Department of Diagnostic Radiology, Amakusa Medical Center, Kameba 854-1, Amakusa, Kumamoto 863-0046 (Japan); Yamashita, Y. [Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Kumamoto 860-8556 (Japan)

2014-10-15

Highlights: • We assess the negative predictive value of multiparametric MRI for prostate cancer. • Patients with positive prostate biopsy findings were defined as false-negative. • Patients with negative initial prostate biopsy findings were followed up for 5 years. • The negative predictive value was 89.6% for significant prostate cancer. • MRI is a useful tool to rule out significant prostate cancer before biopsy. - Abstract: Objective: To assess the clinical negative predictive value (NPV) of multiparametric MRI (mp-MRI) for prostate cancer in a 5-year follow-up. Materials and methods: One hundred ninety-three men suspected of harboring prostate cancer with negative MRI findings were included. Patients with positive transrectal ultrasound (TRUS)-guided biopsy findings were defined as false-negative. Patients with negative initial TRUS-guided biopsy findings were followed up and only patients with negative findings by digital rectal examination, MRI, and repeat biopsy and no increase in PSA at 5-year follow-up were defined as “clinically negative”. The clinical NPV of mp-MRI was calculated. For quantitative analysis, mean signal intensity on T2-weighted images and the mean apparent diffusion coefficient value on ADC maps of the initial MRI studies were compared between peripheral-zone (PZ) cancer and the normal PZ based on pathologic maps of patients who had undergone radical prostatectomy. Results: The clinical NPV of mp-MRI was 89.6% for significant prostate cancer. Small cancers, prostatitis, and benign prostatic hypertrophy masking prostate cancer returned false-negative results. Quantitative analysis showed that there was no significant difference between PZ cancer and the normal PZ. Conclusion: The mp-MRI revealed a high clinical NPV and is a useful tool to rule out clinically significant prostate cancer before biopsy.
Negative predictive value of multiparametric MRI for prostate cancer detection: Outcome of 5-year follow-up in men with negative findings on initial MRI studies

International Nuclear Information System (INIS)

Itatani, R.; Namimoto, T.; Atsuji, S.; Katahira, K.; Morishita, S.; Kitani, K.; Hamada, Y.; Kitaoka, M.; Nakaura, T.; Yamashita, Y.

2014-01-01

Highlights: • We assess the negative predictive value of multiparametric MRI for prostate cancer. • Patients with positive prostate biopsy findings were defined as false-negative. • Patients with negative initial prostate biopsy findings were followed up for 5 years. • The negative predictive value was 89.6% for significant prostate cancer. • MRI is a useful tool to rule out significant prostate cancer before biopsy. - Abstract: Objective: To assess the clinical negative predictive value (NPV) of multiparametric MRI (mp-MRI) for prostate cancer in a 5-year follow-up. Materials and methods: One hundred ninety-three men suspected of harboring prostate cancer with negative MRI findings were included. Patients with positive transrectal ultrasound (TRUS)-guided biopsy findings were defined as false-negative. Patients with negative initial TRUS-guided biopsy findings were followed up and only patients with negative findings by digital rectal examination, MRI, and repeat biopsy and no increase in PSA at 5-year follow-up were defined as “clinically negative”. The clinical NPV of mp-MRI was calculated. For quantitative analysis, mean signal intensity on T2-weighted images and the mean apparent diffusion coefficient value on ADC maps of the initial MRI studies were compared between peripheral-zone (PZ) cancer and the normal PZ based on pathologic maps of patients who had undergone radical prostatectomy. Results: The clinical NPV of mp-MRI was 89.6% for significant prostate cancer. Small cancers, prostatitis, and benign prostatic hypertrophy masking prostate cancer returned false-negative results. Quantitative analysis showed that there was no significant difference between PZ cancer and the normal PZ. Conclusion: The mp-MRI revealed a high clinical NPV and is a useful tool to rule out clinically significant prostate cancer before biopsy
Predicting Outcome in Patients with Rhabdomyosarcoma: Role of [18F]Fluorodeoxyglucose Positron Emission Tomography

International Nuclear Information System (INIS)

Casey, Dana L.; Wexler, Leonard H.; Fox, Josef J.; Dharmarajan, Kavita V.; Schoder, Heiko; Price, Alison N.; Wolden, Suzanne L.

2014-01-01

Purpose: To evaluate whether [ 18 F]fluorodeoxyglucose positron emission tomography (FDG-PET) response of the primary tumor after induction chemotherapy predicts outcomes in rhabdomyosarcoma (RMS). Methods and Materials: After excluding those with initial tumor resection, 107 patients who underwent FDG-PET after induction chemotherapy at Memorial Sloan Kettering Cancer Center from 2002 to 2013 were reviewed. Local control (LC), progression-free survival (PFS), and overall survival (OS) were calculated according to FDG-PET response and maximum standardized uptake value (SUV) at baseline (PET1/SUV1), after induction chemotherapy (PET2/SUV2), and after local therapy (PET3/SUV3). Receiver operator characteristic curves were used to determine the optimal cutoff for dichotomization of SUV1 and SUV2 values. Results: The SUV1 (<9.5 vs ≥9.5) was predictive of PFS (P=.02) and OS (P=.02), but not LC. After 12 weeks (median) of induction chemotherapy, 45 patients had negative PET2 scans and 62 had positive scans: 3-year PFS was 72% versus 44%, respectively (P=.01). The SUV2 (<1.5 vs ≥1.5) was similarly predictive of PFS (P=.005) and was associated with LC (P=.02) and OS (P=.03). A positive PET3 scan was predictive of worse PFS (P=.0009), LC (P=.05), and OS (P=.03). Conclusions: [ 18 F]fluorodeoxyglucose positron emission tomography is an early indicator of outcomes in patients with RMS. Future prospective trials may incorporate FDG-PET response data for risk-adapted therapy and early assessment of new treatment regimens
Obesity and adverse breast cancer risk and outcome: Mechanistic insights and strategies for intervention.

Science.gov (United States)

Picon-Ruiz, Manuel; Morata-Tarifa, Cynthia; Valle-Goffin, Janeiro J; Friedman, Eitan R; Slingerland, Joyce M

2017-09-01

Answer questions and earn CME/CNE Recent decades have seen an unprecedented rise in obesity, and the health impact thereof is increasingly evident. In 2014, worldwide, more than 1.9 billion adults were overweight (body mass index [BMI], 25-29.9 kg/m 2 ), and of these, over 600 million were obese (BMI ≥30 kg/m 2 ). Although the association between obesity and the risk of diabetes and coronary artery disease is widely known, the impact of obesity on cancer incidence, morbidity, and mortality is not fully appreciated. Obesity is associated both with a higher risk of developing breast cancer, particularly in postmenopausal women, and with worse disease outcome for women of all ages. The first part of this review summarizes the relationships between obesity and breast cancer development and outcomes in premenopausal and postmenopausal women and in those with hormone receptor-positive and -negative disease. The second part of this review addresses hypothesized molecular mechanistic insights that may underlie the effects of obesity to increase local and circulating proinflammatory cytokines, promote tumor angiogenesis and stimulate the most malignant cancer stem cell population to drive cancer growth, invasion, and metastasis. Finally, a review of observational studies demonstrates that increased physical activity is associated with lower breast cancer risk and better outcomes. The effects of recent lifestyle interventions to decrease sex steroids, insulin/insulin-like growth factor-1 pathway activation, and inflammatory biomarkers associated with worse breast cancer outcomes in obesity also are discussed. Although many observational studies indicate that exercise with weight loss is associated with improved breast cancer outcome, further prospective studies are needed to determine whether weight reduction will lead to improved patient outcomes. It is hoped that several ongoing lifestyle intervention trials, which are reviewed herein, will support the systematic
Development of Castration Resistant Prostate Cancer can be Predicted by a DNA Hypermethylation Profile.

Science.gov (United States)

Angulo, Javier C; Andrés, Guillermo; Ashour, Nadia; Sánchez-Chapado, Manuel; López, Jose I; Ropero, Santiago

2016-03-01

Detection of DNA hypermethylation has emerged as a novel molecular biomarker for prostate cancer diagnosis and evaluation of prognosis. We sought to define whether a hypermethylation profile of patients with prostate cancer on androgen deprivation would predict castrate resistant prostate cancer. Genome-wide methylation analysis was performed using a methylation cancer panel in 10 normal prostates and 45 tumor samples from patients placed on androgen deprivation who were followed until castrate resistant disease developed. Castrate resistant disease was defined according to EAU (European Association of Urology) guideline criteria. Two pathologists reviewed the Gleason score, Ki-67 index and neuroendocrine differentiation. Hierarchical clustering analysis was performed and relationships with outcome were investigated by Cox regression and log rank analysis. We found 61 genes that were significantly hypermethylated in greater than 20% of tumors analyzed. Three clusters of patients were characterized by a DNA methylation profile, including 1 at risk for earlier castrate resistant disease (log rank p = 0.019) and specific mortality (log rank p = 0.002). Hypermethylation of ETV1 (HR 3.75) and ZNF215 (HR 2.89) predicted disease progression despite androgen deprivation. Hypermethylation of IRAK3 (HR 13.72), ZNF215 (HR 4.81) and SEPT9 (HR 7.64) were independent markers of prognosis. Prostate specific antigen greater than 25 ng/ml, Gleason pattern 5, Ki-67 index greater than 12% and metastasis at diagnosis also predicted a negative response to androgen deprivation. Study limitations included the retrospective design and limited number of cases. Epigenetic silencing of the mentioned genes could be novel molecular markers for the prognosis of advanced prostate cancer. It might predict castrate resistance during hormone deprivation and, thus, disease specific mortality. Gene hypermethylation is associated with disease progression in patients who receive hormone therapy. It
[Predictive factors of the outcomes of prenatal hydronephrosis.

Science.gov (United States)

Bragagnini, Paolo; Estors, Blanca; Delgado, Reyes; Rihuete, Miguel Ángel; Gracia, Jesús

2016-12-01

To determine prenatal and postnatal independent predictors of poor outcome, spontaneous resolution, or the need for surgery in patients with prenatal hydronephrosis. We performed a retrospective study of patients with prenatal hydronephrosis. The renal pelvis APD was measured in the third prenatal trimester ultrasound, as well as in the first and second postnatal ultrasound. Other variables were taken into account, both prenatal and postnatal. For statistical analysis we used Student t-test, chi-square test, survival analysis, logrank test, and ROC curves. We included 218 patients with 293 renal units (RU). Of these, 147/293 (50.2%) RU were operated. 76/293 (25.9%) RU had spontaneous resolution and other 76/293 (25.9%) RU had poor outcome. As risk factors for surgery we found low birth weight (OR 3.84; 95% CI 1.24-11.84), prematurity (OR 4.17; 95% CI 1.35-12.88), duplication (OR 4.99; 95% CI 2.21-11.23) and the presence of nephrourological underlying pathology (OR 53.54; 95% CI 26.23-109.27). For the non-spontaneous resolution, we found as risk factors the alterations of amniotic fluid volume (RR 1.46; 95% CI 1.33-1.60) as well as the underlying nephrourological pathology and duplication. In the poor outcome, we found as risk factors the alterations of amniotic fluid volume (OR 4.54; 95% CI 1.31-15.62), the presence of nephrourological pathology (OR 4.81 95% CI 2.60-8.89) and RU that was operated (OR 4.23, 95% CI 2.35-7.60). The APD of the renal pelvis in all three ultrasounds were reliable for surgery prediction (area under the curve 0.65; 0.82; 0.71) or spontaneous resolution (area under the curve 0.80; 0.91; 0.80), only the first postnatal ultrasound has predictive value in the poor outcome (area under the curve 0.73). The higher sensitivity and specificity of the APD as predictor value was on the first postnatal ultrasound, 14.60 mm for surgery; 11.35 mm for spontaneous resolution and 15.50 mm for poor outcome. The higher APD in the renal pelvis in any of the
Predicting Recurrence and Progression of Noninvasive Papillary Bladder Cancer at Initial Presentation Based on Quantitative Gene Expression Profiles

DEFF Research Database (Denmark)

Birkhahn, M.; Mitra, A.P.; Williams, Johan

2010-01-01

Background: Currently, tumor grade is the best predictor of outcome at first presentation of noninvasive papillary (Ta) bladder cancer. However, reliable predictors of Ta tumor recurrence and progression for individual patients, which could optimize treatment and follow-up schedules based...... on specific tumor biology, are yet to be identified. Objective: To identify genes predictive for recurrence and progression in Ta bladder cancer at first presentation using a quantitative, pathway-specific approach. Design, setting, and participants: Retrospective study of patients with Ta G2/3 bladder tumors...... at initial presentation with three distinct clinical outcomes: absence of recurrence (n = 16), recurrence without progression (n = 16), and progression to carcinoma in situ or invasive disease (n = 16). Measurements: Expressions of 24 genes that feature in relevant pathways that are deregulated in bladder...
Individual Prediction of Heart Failure Among Childhood Cancer Survivors

NARCIS (Netherlands)

Chow, Eric J.; Chen, Yan; Kremer, Leontien C.; Breslow, Norman E.; Hudson, Melissa M.; Armstrong, Gregory T.; Border, William L.; Feijen, Elizabeth A. M.; Green, Daniel M.; Meacham, Lillian R.; Meeske, Kathleen A.; Mulrooney, Daniel A.; Ness, Kirsten K.; Oeffinger, Kevin C.; Sklar, Charles A.; Stovall, Marilyn; van der Pal, Helena J.; Weathers, Rita E.; Robison, Leslie L.; Yasui, Yutaka

2015-01-01

Purpose To create clinically useful models that incorporate readily available demographic and cancer treatment characteristics to predict individual risk of heart failure among 5-year survivors of childhood cancer. Patients and Methods Survivors in the Childhood Cancer Survivor Study (CCSS) free of
Value of neutrophil-to-lymphocyte ratio for predicting lung cancer prognosis: A meta-analysis of 7,219 patients.

Science.gov (United States)

Yu, Yu; Qian, Lei; Cui, Jiuwei

2017-09-01

Current evidence suggests that the neutrophil-to-lymphocyte ratio (NLR) may be a biomarker for poor prognosis in lung cancer, although this association remains controversial. Therefore, a meta-analysis was performed to evaluate the association between NLR and lung cancer outcome. A systematic literature search was performed through the PubMed, Embase and Cochrane Library databases (until July 30, 2016), to identify studies evaluating the association between NLR and overall survival (OS) and/or progression-free survival (PFS) among patients with lung cancer. Based on the results of this search, data from 18 studies involving 7,219 patients with lung cancer were evaluated. The pooled hazard ratio (HR) suggested that elevated pretreatment NLR predicted poor OS [HR=1.46, 95% confidence interval (CI): 1.30-1.64] and poor PFS (HR=1.42, 95% CI: 1.15-1.75) among patients with lung cancer. Subgroup analysis revealed that the prognostic value of NLR for predicting poor OS increased among patients who underwent surgery (HR=1.50, 95% CI: 1.21-1.84) or patients with early-stage disease (HR=1.64, 95% CI: 1.37-1.97). An NLR cut-off value of ≥4 significantly predicted poor OS (HR=1.56, 95% CI: 1.31-1.85) and PFS (HR=1.54, 95% CI: 1.13-1.82), particularly in the cases of small-cell lung cancer. Thus, the results of the present meta-analysis suggested that an elevated pretreatment NLR (e.g., ≥4) may be considered as a biomarker for poor prognosis in patients with lung cancer.
The prognostic significance of HOTAIR for predicting clinical outcome in patients with digestive system tumors.

Science.gov (United States)

Ma, Gaoxiang; Wang, Qiaoyan; Lv, Chunye; Qiang, Fulin; Hua, Qiuhan; Chu, Haiyan; Du, Mulong; Tong, Na; Jiang, Yejuan; Wang, Meilin; Zhang, Zhengdong; Wang, Jian; Gong, Weida

2015-12-01

Although some studies have assessed the prognostic value of HOTAIR in patients with digestive system tumors, the relationship between the HOTAIR and outcome of digestive system tumors remains unknown. The PubMed was searched to identify the eligible studies. Here, we performed a meta-analysis with 11 studies, including a total of 903 cases. Pooled hazard ratios (HRs) and 95 % confidence interval (CI) of HOTAIR for cancer survival were calculated. We found that the pooled HR elevated HOTAIR expression in tumor tissues was 2.36 (95 % CI 1.88-2.97) compared with patients with low HOTAIR expression. Moreover, subgroup analysis revealed that HOTAIR overexpression was also markedly associated with short survival for esophageal squamous cell carcinoma (HR 2.19, 95 % CI 1.62-2.94) and gastric cancer (HR 1.66, 95 % CI 1.02-2.68). In addition, up-regulated HOTAIR was significantly related to survival of digestive system cancer among the studies with more follow-up time (follow time ≥ 5 years) (HR 2.51, 95 % CI 1.99-3.17). When stratified by HR resource and number of patients, the result indicated consistent results with the overall analysis. Subgroup analysis on ethnicities did not change the prognostic influence of elevated HOTAIR expression. Additionally, we conducted an independent validation cohort including 71 gastric cancer cases, in which patients with up-regulated HOTAIR expression had an unfavorable outcome with HR of 2.10 (95 % CI 1.10-4.03). The results suggest that aberrant HOTAIR expression may serve as a candidate positive marker to predict the prognosis of patients with carcinoma of digestive system.
Predictors and outcomes for chronic tracheostomy after chemoradiation for advanced laryngohypopharyngeal cancer.

Science.gov (United States)

Jefferson, Gina D; Wenig, Barry L; Spiotto, Michael T

2016-02-01

After concurrent chemoradiation for head and neck squamous cell cancer, patients with laryngeal incompetence may not recover function. We assessed variables predicting tracheostomy dependence as a measure of poor laryngeal function after chemoradiation. Retrospective Analysis of 109 patients treated with chemoradiation for locoregionally advanced laryngohypopharyngeal squamous cell cancers between 1992 and 2013. Median follow-up was 17.0 and 17.2 months for tracheostomy and nontracheostomy dependent patients, respectively. For all patients, multivariate analysis demonstrated persistent tracheostomy was associated with pretreatment tracheostomy, subglottic extension, three-dimensional conformal radiotherapy (3DCRT) and postradiotherapy lymphadenectomy. When analyzed by primary site, tracheostomy dependence was associated with pretreatment tracheostomy, subglottic extension, and 3DCRT in larynx primaries, and with pretreatment tracheostomy and feeding tube dependency in hypopharynx primaries. Tracheostomy dependence did not impact local control, progression-free survival or overall survival on univariate analysis. After curative chemoradiation, long-term tracheostomy was associated with pretreatment tracheostomy, subglottic extension, postradiotherapy lymphadenectomy, and 3DCRT but did not impact outcomes. These factors may inform treatment decision making regarding organ preservation approaches for locally advanced laryngeal and hypopharyngeal cancers. 4. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.
Use of molecular markers for predicting therapy response in cancer patients.

LENUS (Irish Health Repository)

Duffy, Michael J

2012-02-01

Predictive markers are factors that are associated with upfront response or resistance to a particular therapy. Predictive markers are important in oncology as tumors of the same tissue of origin vary widely in their response to most available systemic therapies. Currently recommended oncological predictive markers include both estrogen and progesterone receptors for identifying patients with breast cancers likely to benefit from hormone therapy, HER-2 for the identification of breast cancer patients likely to benefit from trastuzumab, specific K-RAS mutations for the identification of patients with advanced colorectal cancer unlikely to benefit from either cetuximab or panitumumab and specific EGFR mutations for selecting patients with advanced non-small-cell lung cancer for treatment with tyrosine kinase inhibitors such as gefitinib and erlotinib. The availability of predictive markers should increase drug efficacy and decrease toxicity, thus leading to a more personalized approach to cancer treatment.
Short-term outcomes following laparoscopic resection for colon cancer.

LENUS (Irish Health Repository)

Kavanagh, Dara O

2011-03-01

Laparoscopic resection for colon cancer has been proven to have a similar oncological efficacy compared to open resection. Despite this, it is performed by a minority of colorectal surgeons. The aim of our study was to evaluate the short-term clinical, oncological and survival outcomes in all patients undergoing laparoscopic resection for colon cancer.
Surgical and pathological outcomes of laparoscopic surgery for transverse colon cancer

OpenAIRE

Lee, Y. S.; Lee, I. K.; Kang, W. K.; Cho, H. M.; Park, J. K.; Oh, S. T.; Kim, J. G.; Kim, Y. H.

2008-01-01

Purpose Several multi-institutional prospective randomized trials have demonstrated short-term benefits using laparoscopy. Now the laparoscopic approach is accepted as an alternative to open surgery for colon cancer. However, in prior trials, the transverse colon was excluded. Therefore, it has not been determined whether laparoscopy can be used in the setting of transverse colon cancer. This study evaluated the peri-operative clinical outcomes and oncological quality by pathologic outcomes o...
Predicting future major depression and persistent depressive symptoms: Development of a prognostic screener and PHQ-4 cutoffs in breast cancer patients.

Science.gov (United States)

Weihs, Karen L; Wiley, Joshua F; Crespi, Catherine M; Krull, Jennifer L; Stanton, Annette L

2018-02-01

Create a brief, self-report screener for recently diagnosed breast cancer patients to identify patients at risk of future depression. Breast cancer patients (N = 410) within 2 ± 1 months after diagnosis provided data on depression vulnerability. Depression outcomes were defined as a high depressive symptom trajectory or a major depressive episode during 16 months after diagnosis. Stochastic gradient boosting of regression trees identified 7 items highly predictive for the depression outcomes from a pool of 219 candidate depression vulnerability items. Three of the 7 items were from the Patient Health Questionnaire 4 (PHQ-4), a validated screener for current anxiety/depressive disorder that has not been tested to identify risk for future depression. Thresholds classifying patients as high or low risk on the new Depression Risk Questionnaire 7 (DRQ-7) and the PHQ-4 were obtained. Predictive performance of the DRQ-7 and PHQ-4 was assessed on a holdout validation subsample. DRQ-7 items assess loneliness, irritability, persistent sadness, and low acceptance of emotion as well as 3 items from the PHQ-4 (anhedonia, depressed mood, and worry). A DRQ-7 score of ≥6/23 identified depression outcomes with 0.73 specificity, 0.83 sensitivity, 0.68 positive predictive value, and 0.86 negative predictive value. A PHQ-4 score of ≥3/12 performed moderately well but less accurately than the DRQ-7 (net reclassification improvement = 10%; 95% CI [0.5-16]). The DRQ-7 and the PHQ-4 with a new cutoff score are clinically accessible screeners for risk of depression in newly diagnosed breast cancer patients. Use of the screener to select patients for preventive interventions awaits validation of the screener in other samples. Copyright © 2017 John Wiley & Sons, Ltd.
Methylation of cancer-stem-cell-associated Wnt target genes predicts poor prognosis in colorectal cancer patients

NARCIS (Netherlands)

de Sousa E Melo, Felipe; Colak, Selcuk; Buikhuisen, Joyce; Koster, Jan; Cameron, Kate; de Jong, Joan H.; Tuynman, Jurriaan B.; Prasetyanti, Pramudita R.; Fessler, Evelyn; van den Bergh, Saskia P.; Rodermond, Hans; Dekker, Evelien; van der Loos, Chris M.; Pals, Steven T.; van de Vijver, Marc J.; Versteeg, Rogier; Richel, Dick J.; Vermeulen, Louis; Medema, Jan Paul

2011-01-01

Gene signatures derived from cancer stem cells (CSCs) predict tumor recurrence for many forms of cancer. Here, we derived a gene signature for colorectal CSCs defined by high Wnt signaling activity, which in agreement with previous observations predicts poor prognosis. Surprisingly, however, we
Using predictive analytics and big data to optimize pharmaceutical outcomes.

Science.gov (United States)

Hernandez, Inmaculada; Zhang, Yuting

2017-09-15

The steps involved, the resources needed, and the challenges associated with applying predictive analytics in healthcare are described, with a review of successful applications of predictive analytics in implementing population health management interventions that target medication-related patient outcomes. In healthcare, the term big data typically refers to large quantities of electronic health record, administrative claims, and clinical trial data as well as data collected from smartphone applications, wearable devices, social media, and personal genomics services; predictive analytics refers to innovative methods of analysis developed to overcome challenges associated with big data, including a variety of statistical techniques ranging from predictive modeling to machine learning to data mining. Predictive analytics using big data have been applied successfully in several areas of medication management, such as in the identification of complex patients or those at highest risk for medication noncompliance or adverse effects. Because predictive analytics can be used in predicting different outcomes, they can provide pharmacists with a better understanding of the risks for specific medication-related problems that each patient faces. This information will enable pharmacists to deliver interventions tailored to patients' needs. In order to take full advantage of these benefits, however, clinicians will have to understand the basics of big data and predictive analytics. Predictive analytics that leverage big data will become an indispensable tool for clinicians in mapping interventions and improving patient outcomes. Copyright © 2017 by the American Society of Health-System Pharmacists, Inc. All rights reserved.
Integrating patient reported outcomes with clinical cancer registry data: a feasibility study of the electronic Patient-Reported Outcomes From Cancer Survivors (ePOCS) system.

Science.gov (United States)

Ashley, Laura; Jones, Helen; Thomas, James; Newsham, Alex; Downing, Amy; Morris, Eva; Brown, Julia; Velikova, Galina; Forman, David; Wright, Penny

2013-10-25

Routine measurement of Patient Reported Outcomes (PROs) linked with clinical data across the patient pathway is increasingly important for informing future care planning. The innovative electronic Patient-reported Outcomes from Cancer Survivors (ePOCS) system was developed to integrate PROs, collected online at specified post-diagnostic time-points, with clinical and treatment data in cancer registries. This study tested the technical and clinical feasibility of ePOCS by running the system with a sample of potentially curable breast, colorectal, and prostate cancer patients in their first 15 months post diagnosis. Patients completed questionnaires comprising multiple Patient Reported Outcome Measures (PROMs) via ePOCS within 6 months (T1), and at 9 (T2) and 15 (T3) months, post diagnosis. Feasibility outcomes included system informatics performance, patient recruitment, retention, representativeness and questionnaire completion (response rate), patient feedback, and administration burden involved in running the system. ePOCS ran efficiently with few technical problems. Patient participation was 55.21% (636/1152) overall, although varied by approach mode, and was considerably higher among patients approached face-to-face (61.4%, 490/798) than by telephone (48.8%, 21/43) or letter (41.0%, 125/305). Older and less affluent patients were less likely to join (both Pplanning and for targeting service provision.
Outcome Prediction in Mathematical Models of Immune Response to Infection.

Directory of Open Access Journals (Sweden)

Manuel Mai

Full Text Available Clinicians need to predict patient outcomes with high accuracy as early as possible after disease inception. In this manuscript, we show that patient-to-patient variability sets a fundamental limit on outcome prediction accuracy for a general class of mathematical models for the immune response to infection. However, accuracy can be increased at the expense of delayed prognosis. We investigate several systems of ordinary differential equations (ODEs that model the host immune response to a pathogen load. Advantages of systems of ODEs for investigating the immune response to infection include the ability to collect data on large numbers of 'virtual patients', each with a given set of model parameters, and obtain many time points during the course of the infection. We implement patient-to-patient variability v in the ODE models by randomly selecting the model parameters from distributions with coefficients of variation v that are centered on physiological values. We use logistic regression with one-versus-all classification to predict the discrete steady-state outcomes of the system. We find that the prediction algorithm achieves near 100% accuracy for v = 0, and the accuracy decreases with increasing v for all ODE models studied. The fact that multiple steady-state outcomes can be obtained for a given initial condition, i.e. the basins of attraction overlap in the space of initial conditions, limits the prediction accuracy for v > 0. Increasing the elapsed time of the variables used to train and test the classifier, increases the prediction accuracy, while adding explicit external noise to the ODE models decreases the prediction accuracy. Our results quantify the competition between early prognosis and high prediction accuracy that is frequently encountered by clinicians.

ASTRAL, DRAGON and SEDAN scores predict stroke outcome more accurately than physicians.

Science.gov (United States)

Ntaios, G; Gioulekas, F; Papavasileiou, V; Strbian, D; Michel, P

2016-11-01

ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated. Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome. In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score (mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates (P DRAGON score estimates (P DRAGON score estimates (P DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke. © 2016 EAN.
Neurophysiological prediction of neurological good and poor outcome in post-anoxic coma.

Science.gov (United States)

Grippo, A; Carrai, R; Scarpino, M; Spalletti, M; Lanzo, G; Cossu, C; Peris, A; Valente, S; Amantini, A

2017-06-01

Investigation of the utility of association between electroencephalogram (EEG) and somatosensory-evoked potentials (SEPs) for the prediction of neurological outcome in comatose patients resuscitated after cardiac arrest (CA) treated with therapeutic hypothermia, according to different recording times after CA. Glasgow Coma Scale, EEG and SEPs performed at 12, 24 and 48-72 h after CA were assessed in 200 patients. Outcome was evaluated by Cerebral Performance Category 6 months after CA. Within 12 h after CA, grade 1 EEG predicted good outcome and bilaterally absent (BA) SEPs predicted poor outcome. Because grade 1 EEG and BA-SEPs were never found in the same patient, the recording of both EEG and SEPs allows us to correctly prognosticate a greater number of patients with respect to the use of a single test within 12 h after CA. At 48-72 h after CA, both grade 2 EEG and BA-SEPs predicted poor outcome with FPR=0.0%. When these neurophysiological patterns are both present in the same patient, they confirm and strengthen their prognostic value, but because they also occurred independently in eight patients, poor outcome is predictable in a greater number of patients. The combination of EEG/SEP findings allows prediction of good and poor outcome (within 12 h after CA) and of poor outcome (after 48-72 h). Recording of EEG and SEPs in the same patients allows always an increase in the number of cases correctly classified, and an increase of the reliability of prognostication in a single patient due to concordance of patterns. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
The prognostic significance of UCA1 for predicting clinical outcome in patients with digestive system malignancies.

Science.gov (United States)

Liu, Fang-Teng; Dong, Qing; Gao, Hui; Zhu, Zheng-Ming

2017-06-20

Urothelial Carcinoma Associated 1 (UCA1) was an originally identified lncRNA in bladder cancer. Previous studies have reported that UCA1 played a significant role in various types of cancer. This study aimed to clarify the prognostic value of UCA1 in digestive system cancers. The meta-analysis of 15 studies were included, comprising 1441 patients with digestive system cancers. The pooled results of 14 studies indicated that high expression of UCA1 was significantly associated with poorer OS in patients with digestive system cancers (HR: 1.89, 95 % CI: 1.52-2.26). In addition, UCA1 could be as an independent prognostic factor for predicting OS of patients (HR: 1.85, 95 % CI: 1.45-2.25). The pooled results of 3 studies indicated a significant association between UCA1 and DFS in patients with digestive system cancers (HR = 2.50; 95 % CI = 1.30-3.69). Statistical significance was also observed in subgroup meta-analysis. Furthermore, the clinicopathological values of UCA1 were discussed in esophageal cancer, colorectal cancer and pancreatic cancer. A comprehensive retrieval was performed to search studies evaluating the prognostic value of UCA1 in digestive system cancers. Many databases were involved, including PubMed, Web of Science, Embase and Chinese National Knowledge Infrastructure and Wanfang database. Quantitative meta-analysis was performed with standard statistical methods and the prognostic significance of UCA1 in digestive system cancers was qualified. Elevated level of UCA1 indicated the poor clinical outcome for patients with digestive system cancers. It may serve as a new biomarker related to prognosis in digestive system cancers.
Prediction of Outcome in Acute Lower Gastrointestinal Bleeding Using Gradient Boosting.

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Lakshmana Ayaru

Full Text Available There are no widely used models in clinical care to predict outcome in acute lower gastro-intestinal bleeding (ALGIB. If available these could help triage patients at presentation to appropriate levels of care/intervention and improve medical resource utilisation. We aimed to apply a state-of-the-art machine learning classifier, gradient boosting (GB, to predict outcome in ALGIB using non-endoscopic measurements as predictors.Non-endoscopic variables from patients with ALGIB attending the emergency departments of two teaching hospitals were analysed retrospectively for training/internal validation (n=170 and external validation (n=130 of the GB model. The performance of the GB algorithm in predicting recurrent bleeding, clinical intervention and severe bleeding was compared to a multiple logic regression (MLR model and two published MLR-based prediction algorithms (BLEED and Strate prediction rule.The GB algorithm had the best negative predictive values for the chosen outcomes (>88%. On internal validation the accuracy of the GB algorithm for predicting recurrent bleeding, therapeutic intervention and severe bleeding were (88%, 88% and 78% respectively and superior to the BLEED classification (64%, 68% and 63%, Strate prediction rule (78%, 78%, 67% and conventional MLR (74%, 74% 62%. On external validation the accuracy was similar to conventional MLR for recurrent bleeding (88% vs. 83% and therapeutic intervention (91% vs. 87% but superior for severe bleeding (83% vs. 71%.The gradient boosting algorithm accurately predicts outcome in patients with acute lower gastrointestinal bleeding and outperforms multiple logistic regression based models. These may be useful for risk stratification of patients on presentation to the emergency department.
Applications of machine learning in cancer prediction and prognosis.

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Cruz, Joseph A; Wishart, David S

2007-02-11

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on "older" technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.
Single-Incision Laparoscopic Colectomy for Cancer: Short-Term Outcomes and Comparative Analysis

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Rodrigo Pedraza

2013-01-01

Full Text Available Introduction. Single-incision laparoscopic colectomy (SILC is a viable and safe technique; however, there are no single-institution studies comparing outcomes of SILC for colon cancer with well-established minimally invasive techniques. We evaluated the short-term outcomes following SILC for cancer compared to a group of well-established minimally invasive techniques. Methods. Fifty consecutive patients who underwent SILC for colon cancer were compared to a control group composed of 50 cases of minimally invasive colectomies performed with either conventional multiport or hand-assisted laparoscopic technique. The groups were paired based on the type of procedure. Demographics, intraoperative, and postoperative outcomes were assessed. Results. With the exception of BMI, demographics were similar between both groups. Most of the procedures were right colectomies ( and anterior resections (. There were no significant differences in operative time (127.9 versus 126.7 min, conversions (0 versus 1, complications (14% versus 8%, length of stay (4.5 versus 4.0 days, readmissions (2% versus 2%, and reoperations (2% versus 2%. Oncological outcomes were also similar between groups. Conclusions. SILC is an oncologically sound alternative for the management of colon cancer and results in similar short-term outcomes as compared with well-established minimally invasive techniques.
Perceived Masculinity Predicts U.S. Supreme Court Outcomes

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2016-01-01

Previous studies suggest a significant role of language in the court room, yet none has identified a definitive correlation between vocal characteristics and court outcomes. This paper demonstrates that voice-based snap judgments based solely on the introductory sentence of lawyers arguing in front of the Supreme Court of the United States predict outcomes in the Court. In this study, participants rated the opening statement of male advocates arguing before the Supreme Court between 1998 and 2012 in terms of masculinity, attractiveness, confidence, intelligence, trustworthiness, and aggressiveness. We found significant correlation between vocal characteristics and court outcomes and the correlation is specific to perceived masculinity even when judgment of masculinity is based only on less than three seconds of exposure to a lawyer’s speech sample. Specifically, male advocates are more likely to win when they are perceived as less masculine. No other personality dimension predicts court outcomes. While this study does not aim to establish any causal connections, our findings suggest that vocal characteristics may be relevant in even as solemn a setting as the Supreme Court of the United States. PMID:27737008
Perceived Masculinity Predicts U.S. Supreme Court Outcomes.

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Daniel Chen

Full Text Available Previous studies suggest a significant role of language in the court room, yet none has identified a definitive correlation between vocal characteristics and court outcomes. This paper demonstrates that voice-based snap judgments based solely on the introductory sentence of lawyers arguing in front of the Supreme Court of the United States predict outcomes in the Court. In this study, participants rated the opening statement of male advocates arguing before the Supreme Court between 1998 and 2012 in terms of masculinity, attractiveness, confidence, intelligence, trustworthiness, and aggressiveness. We found significant correlation between vocal characteristics and court outcomes and the correlation is specific to perceived masculinity even when judgment of masculinity is based only on less than three seconds of exposure to a lawyer's speech sample. Specifically, male advocates are more likely to win when they are perceived as less masculine. No other personality dimension predicts court outcomes. While this study does not aim to establish any causal connections, our findings suggest that vocal characteristics may be relevant in even as solemn a setting as the Supreme Court of the United States.
Evaluation of outcome prediction and disease extension by quantitative 2-deoxy-2-[18F] fluoro-D-glucose with positron emission tomography in patients with small cell lung cancer

International Nuclear Information System (INIS)

Arslan, N.; Tuncel, M.; Kuzhan, O.; Alagoz, E.; Budakoglu, B.; Ozet, A.; Ozguven, M.A.

2011-01-01

The objective of this study is to determine whether 2-deoxy-2-[18F] fluoro-D-glucose with positron emission tomography (FDG-PET) imaging and quantitative PET parameters can predict outcome and differentiate patients with limited disease (LD) from extensive disease (ED) in patients with small cell lung cancer (SCLC). We retrospectively evaluated data from 25 patients who underwent either initial staging (Group A, n 12) or restaging (Group B, n 13) by conventional imaging methods and FDG-PET according to the simplified staging scheme developed by the Veterans Administration Lung Cancer Study Group-2. FDG-PET images were both visually and quantitatively evaluated with standardized uptake value (SUV) max , SUV ave , total metabolic tumor volume (with SUV max >%50 and SUV max >2.5), total lesion glycolysis (TLG) (with SUV max >%50 and SUV max >2.5). The correlation between quantitative PET parameters, disease stages and survival were analyzed. By conventional methods 14 of 25 (56%) patients were reported to have LD and 11 of 25 (44%) had ED. FDG-PET scan upstaged 9 out of 25 (36%) and downstaged 2 out of 25 (%8) patients. Among the quantitative PET parameters, TLGs were the only PET parameters that differentiated between Group A and Group B patients. FDG-PET staging (p=0.019) could predict significant survival difference between stages on contrary to conventional staging (p=0.055). Moreover, TLG [SUV max >%50] was the only quantitative PET parameter that could predict survival (p=0.027). FDG-PET imaging is a valuable tool in the management of patients with SCLC for a more accurate staging. The use of quantitative PET parameters may have a role in prediction of stage and survival. (author)
Workload and surgeon's specialty for outcome after colorectal cancer surgery

DEFF Research Database (Denmark)

Archampong, David; Borowski, David; Wille-Jørgensen, Peer

2012-01-01

A large body of research has focused on investigating the effects of healthcare provider volume and specialization on patient outcomes including outcomes of colorectal cancer surgery. However there is conflicting evidence about the role of such healthcare provider characteristics in the management...
Adverse mental health outcomes in breast cancer survivors compared to women who did not have cancer: systematic review protocol.

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Carreira, Helena; Williams, Rachael; Müller, Martin; Harewood, Rhea; Bhaskaran, Krishnan

2017-08-14

Recent increasing trends in breast cancer incidence and survival have resulted in unprecedented numbers of cancer survivors in the general population. A cancer diagnosis may have a profound psychological impact, and breast cancer treatments often cause long-term physical sequelae, potentially affecting women's mental health. The aim of this systematic review is to identify and summarise all studies that have compared mental health outcomes in breast cancer survivors, versus women who did not have cancer. This study will be a systematic review of the literature. Four databases, including MEDLINE and PsycINFO, will be searched to identify potentially relevant studies. The search expressions will use a Boolean logic, including terms for the target population (women who have had breast cancer), outcomes (psychiatric disorders) and comparators (e.g. risk, hazard). All mental disorders will be eligible, except those with onset normally occurring during childhood or strong genetic basis (e.g. Huntington disease). The eligibility of the studies will be assessed in two phases: (1) considering the information provided in the title and abstract; (2) evaluating the full text. Studies including women diagnosed with breast cancer 1 year or more ago and that provide original data on mental health outcomes will be eligible. Studies in which all women were undergoing surgery, chemotherapy or radiotherapy, or hospitalised or institutionalised, will be excluded, as well as studies that include patients selected on the basis of symptomatology. Two investigators will do the screening of the references and the data extraction independently, with results compared and discrepancies resolved by involving a third investigator when necessary. Study quality and risk of bias will be assessed across six broad domains. Results will be summarised by outcome, and summary measures of frequency and/or association will be computed if possible. This review will summarise the evidence on the mental
The impact of the Internet on cancer outcomes.

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Eysenbach, Gunther

2003-01-01

Each day, more than 12.5 million health-related computer searches are conducted on the World Wide Web. Based on a meta-analysis of 24 published surveys, the author estimates that in the developed world, about 39% of persons with cancer are using the Internet, and approximately 2.3 million persons living with cancer worldwide are online. In addition, 15% to 20% of persons with cancer use the Internet "indirectly" through family and friends. Based on a comprehensive review of the literature, the available evidence on how persons with cancer are using the Internet and the effect of Internet use on persons with cancer is summarized. The author distinguishes four areas of Internet use: communication (electronic mail), community (virtual support groups), content (health information on the World Wide Web), and e-commerce. A conceptual framework summarizing the factors involved in a possible link between Internet use and cancer outcomes is presented, and future areas for research are highlighted.
South African Breast Cancer and HIV Outcomes Study: Methods and Baseline Assessment

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Herbert Cubasch

2017-04-01

Full Text Available Purpose: In low- and middle-income, HIV-endemic regions of sub-Saharan Africa, morbidity and mortality from the common epithelial cancers of the developed world are rising. Even among HIV-infected individuals, access to antiretroviral therapy has enhanced life expectancy, shifting the distribution of cancer diagnoses toward non–AIDS-defining malignancies, including breast cancer. Building on our prior research, we recently initiated the South African Breast Cancer and HIV Outcomes study. Methods: We will recruit a cohort of 3,000 women newly diagnosed with breast cancer at hospitals in high (average, 20% HIV prevalence areas, in Johannesburg, Durban, Pietermaritzburg, and Empangeni. At baseline, we will collect information on demographic, behavioral, clinical, and other factors related to access to health care. Every 3 months in year 1 and every 6 months thereafter, we will collect interview and chart data on treatment, symptoms, cancer progression, comorbidities, and other factors. We will compare survival rates of HIV-infected and uninfected women with newly diagnosed breast cancer and their likelihood of receiving suboptimal anticancer therapy. We will identify determinants of suboptimal therapy and context-specific modifiable factors that future interventions can target to improve outcomes. We will explore molecular mechanisms underlying potentially aggressive breast cancer in both HIV-infected and uninfected patients, as well as the roles of pathogens, states of immune activation, and inflammation in disease progression. Conclusion: Our goals are to contribute to development of evidence-based guidelines for the management of breast cancer in HIV-positive women and to improve outcomes for all patients with breast cancer in resource-constrained settings.
Applying a new mammographic imaging marker to predict breast cancer risk

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Aghaei, Faranak; Danala, Gopichandh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

2018-02-01

Identifying and developing new mammographic imaging markers to assist prediction of breast cancer risk has been attracting extensive research interest recently. Although mammographic density is considered an important breast cancer risk, its discriminatory power is lower for predicting short-term breast cancer risk, which is a prerequisite to establish a more effective personalized breast cancer screening paradigm. In this study, we presented a new interactive computer-aided detection (CAD) scheme to generate a new quantitative mammographic imaging marker based on the bilateral mammographic tissue density asymmetry to predict risk of cancer detection in the next subsequent mammography screening. An image database involving 1,397 women was retrospectively assembled and tested. Each woman had two digital mammography screenings namely, the "current" and "prior" screenings with a time interval from 365 to 600 days. All "prior" images were originally interpreted negative. In "current" screenings, these cases were divided into 3 groups, which include 402 positive, 643 negative, and 352 biopsy-proved benign cases, respectively. There is no significant difference of BIRADS based mammographic density ratings between 3 case groups (p cancer detection in the "current" screening. Study demonstrated that this new imaging marker had potential to yield significantly higher discriminatory power to predict short-term breast cancer risk.
Reliability of computerized cephalometric outcome predictions of mandibular set-back surgery

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Stefanović Neda

2011-01-01

Full Text Available Introduction. A successful treatment outcome in dentofacial deformity patients commonly requires combined orthodontic-surgical therapy. This enables us to overcome functional, aesthetic and psychological problems. Since most patients state aesthetics as the primary motive for seeking therapy, cephalometric predictions of treatment outcome have become the essential part of treatment planning, especially in combined orthodontic-surgical cases. Objective. The aim of this study was to evaluate the validity and reliability of computerized orthognathic surgery outcome predictions generated using the Nemotec Dental Studio NX 2005 software. Methods. The sample of the study consisted of 31 patients diagnosed with mandibular prognathism who were surgically treated at the Hospital for Maxillofacial Surgery in Belgrade. Investigation was done on lateral cephalograms made before and after surgical treatment. Cephalograms were digitized and analyzed using computer software. According to measurements made on superimposed pre- and postsurgical cephalograms, the patients were retreated within the software and the predictions were assessed by measuring seven angular and three linear parameters. Prediction measurements were then compared with the actual outcome. Results. Results showed statistically significant changes between posttreatment and predicted values for parameters referring to lower lip and mentolabial sulcus position. Conclusion. Computerized cephalometric predictions for hard-tissue structures in the sagittal and vertical planes, as well as the VTO parameters, generated using the Nemotec Dental Studio NX 2005 software are reliable, while lower lip and mentolabial sulcus position predictions are not reliable enough.
Western Validation of a Novel Gastric Cancer Prognosis Prediction Model in US Gastric Cancer Patients.

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Woo, Yanghee; Goldner, Bryan; Son, Taeil; Song, Kijun; Noh, Sung Hoon; Fong, Yuman; Hyung, Woo Jin

2018-03-01

A novel prediction model for accurate determination of 5-year overall survival of gastric cancer patients was developed by an international collaborative group (G6+). This prediction model was created using a single institution's database of 11,851 Korean patients and included readily available and clinically relevant factors. Already validated using external East Asian cohorts, its applicability in the American population was yet to be determined. Using the Surveillance, Epidemiology, and End Results (SEER) dataset, 2014 release, all patients diagnosed with gastric adenocarcinoma who underwent surgical resection between 2002 and 2012, were selected. Characteristics for analysis included: age, sex, depth of tumor invasion, number of positive lymph nodes, total lymph nodes retrieved, presence of distant metastasis, extent of resection, and histology. Concordance index (C-statistic) was assessed using the novel prediction model and compared with the prognostic index, the seventh edition of the TNM staging system. Of the 26,019 gastric cancer patients identified from the SEER database, 15,483 had complete datasets. Validation of the novel prediction tool revealed a C-statistic of 0.762 (95% CI 0.754 to 0.769) compared with the seventh TNM staging model, C-statistic 0.683 (95% CI 0.677 to 0.689), (p prediction model for gastric cancer in the American patient population. Its superior prediction of the 5-year survival of gastric cancer patients in a large Western cohort strongly supports its global applicability. Importantly, this model allows for accurate prognosis for an increasing number of gastric cancer patients worldwide, including those who received inadequate lymphadenectomy or underwent a noncurative resection. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.
A Novel Prognostic Score, Based on Preoperative Nutritional Status, Predicts Outcomes of Patients after Curative Resection for Gastric Cancer.

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Liu, Xuechao; Qiu, Haibo; Liu, Jianjun; Chen, Shangxiang; Xu, Dazhi; Li, Wei; Zhan, Youqing; Li, Yuanfang; Chen, Yingbo; Zhou, Zhiwei; Sun, Xiaowei

2016-01-01

PURPOSE: We aimed to determine whether preoperative nutritional status (PNS) was a valuable predictor of outcome in patients with gastric cancer (GC). METHODS: We retrospectively evaluated 1320 patients with GC undergoing curative resection. The PNS score was constructed based on four objective and easily measurable criteria: prognostic nutritional index (PNI) score 1, serum albumin nutritional-based prognostic score, is independently associated with OS in GC. Prospective studies are needed to validate its clinical utility.
Predicting the Survival of Gastric Cancer Patients Using

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Korhani Kangi, Azam; Bahrampour, Abbas

2018-02-26

Introduction and purpose: In recent years the use of neural networks without any premises for investigation of prognosis in analyzing survival data has increased. Artificial neural networks (ANN) use small processors with a continuous network to solve problems inspired by the human brain. Bayesian neural networks (BNN) constitute a neural-based approach to modeling and non-linearization of complex issues using special algorithms and statistical methods. Gastric cancer incidence is the first and third ranking for men and women in Iran, respectively. The aim of the present study was to assess the value of an artificial neural network and a Bayesian neural network for modeling and predicting of probability of gastric cancer patient death. Materials and Methods: In this study, we used information on 339 patients aged from 20 to 90 years old with positive gastric cancer, referred to Afzalipoor and Shahid Bahonar Hospitals in Kerman City from 2001 to 2015. The three layers perceptron neural network (ANN) and the Bayesian neural network (BNN) were used for predicting the probability of mortality using the available data. To investigate differences between the models, sensitivity, specificity, accuracy and the area under receiver operating characteristic curves (AUROCs) were generated. Results: In this study, the sensitivity and specificity of the artificial neural network and Bayesian neural network models were 0.882, 0.903 and 0.954, 0.909, respectively. Prediction accuracy and the area under curve ROC for the two models were 0.891, 0.944 and 0.935, 0.961. The age at diagnosis of gastric cancer was most important for predicting survival, followed by tumor grade, morphology, gender, smoking history, opium consumption, receiving chemotherapy, presence of metastasis, tumor stage, receiving radiotherapy, and being resident in a village. Conclusion: The findings of the present study indicated that the Bayesian neural network is preferable to an artificial neural network for
Achieving optimal delivery of follow-up care for prostate cancer survivors: improving patient outcomes

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Hudson SV

2015-03-01

Full Text Available Shawna V Hudson,1 Denalee M O’Malley,2 Suzanne M Miller3 1Department of Family Medicine and Community Health, Rutgers Robert Wood Johnson Medical School, Somerset, 2Rutgers School of Social Work, New Brunswick, NJ, 3Cancer Prevention and Control Program, Fox Chase Cancer Center/Temple University Health System, Philadelphia, PA, USA Background: Prostate cancer is the most commonly diagnosed cancer in men in the US, and the second most prevalent cancer in men worldwide. High incidence and survival rates for prostate cancer have resulted in a large and growing population of long-term prostate cancer survivors. Long-term follow-up guidelines have only recently been developed to inform approaches to this phase of care for the prostate cancer population. Methods: A PubMed search of English literature through August 2014 was performed. Articles were retrieved and reviewed to confirm their relevance. Patient-reported measures that were used in studies of long-term prostate cancer survivors (ie, at least 2 years posttreatment were reviewed and included in the review. Results: A total of 343 abstracts were initially identified from the database search. After abstract review, 105 full-text articles were reviewed of which seven met inclusion criteria. An additional 22 articles were identified from the references of the included articles, and 29 were retained. From the 29 articles, 68 patient-reported outcome measures were identified. The majority (75% were multi-item scales that had been previously validated in existing literature. We identified four main areas of assessment: 1 physical health; 2 quality of life – general, physical, and psychosocial; 3 health promotion – physical activity, diet, and tobacco cessation; and 4 care quality outcomes. Conclusion: There are a number of well-validated measures that assess patient-reported outcomes that document key aspects of long-term follow-up with respect to patient symptoms and quality of life. However
SU-E-T-170: Characterization of the Location, Extent, and Proximity to Critical Structures of Target Volumes Provides Detail for Improved Outcome Predictions Among Pancreatic Cancer Patients

International Nuclear Information System (INIS)

Cheng, Z; Moore, J; Rosati, L; Mian, O; Narang, A; Herman, J; McNutt, T

2015-01-01

Purpose: In radiotherapy, size, location and proximity of the target to critical structures influence treatment decisions. It has been shown that proximity of the target predicts dosimetric sparing of critical structures. In addition to dosimetry, precise location of disease has further implications such as tumor invasion, or proximity to major arteries that inhibit surgery. Knowledge of which patients can be converted to surgical candidates by radiation may have high impact on future treat/no-treat decisions. We propose a method to improve our characterization of the location of pancreatic cancer and treatment volume extent with respect to nearby arteries with the goal of developing features to improve clinical predictions and decisions. Methods: Oncospace is a local learning health system that systematically captures clinical outcomes and all aspects of radiotherapy treatment plans, including overlap volume histograms (OVH) – a measure of spatial relationships between two structures. Minimum and maximum distances of PTV and OARs based on OVH, PTV volume, anatomic location by ICD-9 code, and surgical outcome were queried. Normalized distance to center from the left and right kidney was calculated to indicate tumor location and laterality. Distance to critical arteries (celiac, superior mesenteric, common hepatic) is validated by surgical status (borderline resectable, locally advanced converted to resectable). Results: There were 205 pancreas stereotactic body radiotherapy patients treated from 2009–2015 queried. Location/laterality of tumor based on kidney OVH show strong trends between location by OVH and by ICD-9. Compared to the locally advanced group, the borderline resectable group showed larger geometrical distance from critical arteries (p=0.03). Conclusion: Our platform enabled analysis of shape/size-location relationships. These data suggest that PTV volume and attention to distance between PTVs and surrounding OARs and major arteries may be

SU-E-T-170: Characterization of the Location, Extent, and Proximity to Critical Structures of Target Volumes Provides Detail for Improved Outcome Predictions Among Pancreatic Cancer Patients

Energy Technology Data Exchange (ETDEWEB)

Cheng, Z; Moore, J; Rosati, L; Mian, O; Narang, A; Herman, J; McNutt, T [Johns Hopkins University, Baltimore, MD (United States)

2015-06-15

Purpose: In radiotherapy, size, location and proximity of the target to critical structures influence treatment decisions. It has been shown that proximity of the target predicts dosimetric sparing of critical structures. In addition to dosimetry, precise location of disease has further implications such as tumor invasion, or proximity to major arteries that inhibit surgery. Knowledge of which patients can be converted to surgical candidates by radiation may have high impact on future treat/no-treat decisions. We propose a method to improve our characterization of the location of pancreatic cancer and treatment volume extent with respect to nearby arteries with the goal of developing features to improve clinical predictions and decisions. Methods: Oncospace is a local learning health system that systematically captures clinical outcomes and all aspects of radiotherapy treatment plans, including overlap volume histograms (OVH) – a measure of spatial relationships between two structures. Minimum and maximum distances of PTV and OARs based on OVH, PTV volume, anatomic location by ICD-9 code, and surgical outcome were queried. Normalized distance to center from the left and right kidney was calculated to indicate tumor location and laterality. Distance to critical arteries (celiac, superior mesenteric, common hepatic) is validated by surgical status (borderline resectable, locally advanced converted to resectable). Results: There were 205 pancreas stereotactic body radiotherapy patients treated from 2009–2015 queried. Location/laterality of tumor based on kidney OVH show strong trends between location by OVH and by ICD-9. Compared to the locally advanced group, the borderline resectable group showed larger geometrical distance from critical arteries (p=0.03). Conclusion: Our platform enabled analysis of shape/size-location relationships. These data suggest that PTV volume and attention to distance between PTVs and surrounding OARs and major arteries may be
Analysing data from patient-reported outcome and quality of life endpoints for cancer clinical trials

DEFF Research Database (Denmark)

Bottomley, Andrew; Pe, Madeline; Sloan, Jeff

2016-01-01

Measures of health-related quality of life (HRQOL) and other patient-reported outcomes generate important data in cancer randomised trials to assist in assessing the risks and benefits of cancer therapies and fostering patient-centred cancer care. However, the various ways these measures are anal......Measures of health-related quality of life (HRQOL) and other patient-reported outcomes generate important data in cancer randomised trials to assist in assessing the risks and benefits of cancer therapies and fostering patient-centred cancer care. However, the various ways these measures...... are analysed and interpreted make it difficult to compare results across trials, and hinders the application of research findings to inform publications, product labelling, clinical guidelines, and health policy. To address these problems, the Setting International Standards in Analyzing Patient......-Reported Outcomes and Quality of Life Endpoints Data (SISAQOL) initiative has been established. This consortium, directed by the European Organisation for Research and Treatment of Cancer (EORTC), was convened to provide recommendations on how to standardise the analysis of HRQOL and other patient-reported outcomes...
Applications of Machine Learning in Cancer Prediction and Prognosis

Directory of Open Access Journals (Sweden)

Joseph A. Cruz

2006-01-01

Full Text Available Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25% improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.
Regional brain morphometry predicts memory rehabilitation outcome after traumatic brain injury

Directory of Open Access Journals (Sweden)

Gary E Strangman

2010-10-01

Full Text Available Cognitive deficits following traumatic brain injury (TBI commonly include difficulties with memory, attention, and executive dysfunction. These deficits are amenable to cognitive rehabilitation, but optimally selecting rehabilitation programs for individual patients remains a challenge. Recent methods for quantifying regional brain morphometry allow for automated quantification of tissue volumes in numerous distinct brain structures. We hypothesized that such quantitative structural information could help identify individuals more or less likely to benefit from memory rehabilitation. Fifty individuals with TBI of all severities who reported having memory difficulties first underwent structural MRI scanning. They then participated in a 12 session memory rehabilitation program emphasizing internal memory strategies (I-MEMS. Primary outcome measures (HVLT, RBMT were collected at the time of the MRI scan, immediately following therapy, and again at one month post-therapy. Regional brain volumes were used to predict outcome, adjusting for standard predictors (e.g., injury severity, age, education, pretest scores. We identified several brain regions that provided significant predictions of rehabilitation outcome, including the volume of the hippocampus, the lateral prefrontal cortex, the thalamus, and several subregions of the cingulate cortex. The prediction range of regional brain volumes were in some cases nearly equal in magnitude to prediction ranges provided by pretest scores on the outcome variable. We conclude that specific cerebral networks including these regions may contribute to learning during I-MEMS rehabilitation, and suggest that morphometric measures may provide substantial predictive value for rehabilitation outcome in other cognitive interventions as well.
The Functional Diffusion Map: An Imaging Biomarker for the Early Prediction of Cancer Treatment Outcome

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Bradford A. Moffat

2006-04-01

Full Text Available Functional diffusion map (fDM has been recently reported as an early and quantitative biomarker of clinical brain tumor treatment outcome. This MRI approach spatially maps and quantifies treatment-induced changes in tumor water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. This current study was designed to evaluate the capability of fDM for preclinical evaluation of dose escalation studies and to determine if these changes were correlated with outcome measures (cell kill and overall survival. Serial T2-weighted and diffusion MRI were carried out on rodents with orthotopically implanted 9L brain tumors receiving three doses of 1,3-bis(2-chloroethyl-1-nitrosourea (6.65, 13.3, and 26.6 mg/kg, i.p.. All images were coregistered to baseline T2-weighted images for fDM analysis. Analysis of tumor fDM data on day 4 posttreatment detected dosedependent changes in tumor diffusion values, which were also found to be spatially dependent. Histologic analysis of treated tumors confirmed spatial changes in cellularity as observed by fDM. Early changes in tumor diffusion values were found to be highly correlative with drug dose and independent biologic outcome measures (cell kill and survival. Therefore, the fDM imaging biomarker for early prediction of treatment efficacy can be used in the drug development process.
Predicting Brain Metastasis in Breast Cancer Patients: Stage Versus Biology.

Science.gov (United States)

Azim, Hamdy A; Abdel-Malek, Raafat; Kassem, Loay

2018-04-01

Brain metastasis (BM) is a life-threatening event in breast cancer patients. Identifying patients at a high risk for BM can help to adopt screening programs and test preventive interventions. We tried to identify the incidence of BM in different stages and subtypes of breast cancer. We reviewed the clinical records of 2193 consecutive breast cancer patients who presented between January 1999 and December 2010. We explored the incidence of BM in relation to standard clinicopathological factors, and determined the cumulative risk of BM according to the disease stage and phenotype. Of the 2193 included women, 160 (7.3%) developed BM at a median follow-up of 5.8 years. Age younger than 60 years (P = .015), larger tumors (P = .004), lymph node (LN) positivity (P < .001), high tumor grade (P = .012), and HER2 positivity (P < .001) were associated with higher incidence of BM in the whole population. In patients who presented with locoregional disease, 3 factors independently predicted BM: large tumors (hazard ratio [HR], 3.60; 95% confidence interval [CI], 1.54-8.38; P = .003), axillary LN metastasis (HR, 4.03; 95% CI, 1.91-8.52; P < .001), and HER2 positivity (HR, 1.89; 95% CI, 1.0-3.41; P = .049). A Brain Relapse Index was formulated using those 3 factors, with 5-year cumulative incidence of BM of 19.2% in those having the 2 or 3 risk factors versus 2.5% in those with no or 1 risk factor (P < .001). In metastatic patients, 3 factors were associated with higher risk of BM: HER2 positivity (P = .007), shorter relapse-free interval (P < .001), and lung metastasis (P < .001). Disease stage and biological subtypes predict the risk for BM and subsequent treatment outcome. Copyright © 2017 Elsevier Inc. All rights reserved.
Chronic Kidney Disease – Where Next? Predicting Outcomes and Planning Care Pathways

Directory of Open Access Journals (Sweden)

Angharad Marks

2014-07-01

Full Text Available With the introduction of the National Kidney Foundation Kidney Disease Outcomes Quality Initiative chronic kidney disease (CKD guidelines, CKD has been identified as common, particularly in the elderly. The outcomes for those with CKD can be poor: mortality, initiation of renal replacement therapy, and progressive deterioration in kidney function, with its associated complications. In young people with CKD, the risk of poor outcome is high and the social cost substantial, but the actual number of patients affected is relatively small. In the elderly, the risk of poor outcome is substantially lower, but due to the high prevalence of CKD the actual number of poor outcomes attributable to CKD is higher. Predicting which patients are at greatest risk, and being able to tailor care appropriately, has significant potential benefits. Risk prediction models in CKD are being developed and show promise but thus far have limitations. In this review we describe the pathway for developing and evaluating risk prediction tools, and consider what models we have for CKD prediction and where next.
Long-term psychosocial outcomes among bereaved siblings of children with cancer.

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Rosenberg, Abby R; Postier, Andrea; Osenga, Kaci; Kreicbergs, Ulrika; Neville, Bridget; Dussel, Veronica; Wolfe, Joanne

2015-01-01

The death of a child from cancer affects the entire family. Little is known about the long-term psychosocial outcomes of bereaved siblings. To describe 1) the prevalence of risky health behaviors, psychological distress, and social support among bereaved siblings and 2) potentially modifiable factors associated with poor outcomes. Bereaved siblings were eligible for this dual-center, cross-sectional, survey-based study if they were 16 years or older and their parents had enrolled in one of three prior studies about caring for children with cancer at the end of life. Linear regression models identified associations between personal perspectives before, during, and after the family's cancer experience and outcomes (health behaviors, psychological distress, and social support). Fifty-eight siblings completed surveys (62% response rate). They were approximately 12 years bereaved, with a mean age of 26 years at the time of the survey (SD 7.8). Anxiety, depression, and illicit substance use increased during the year after their brother/sister's death but then returned to baseline. Siblings who reported dissatisfaction with communication, poor preparation for death, missed opportunities to say goodbye, and/or a perceived negative impact of the cancer experience on relationships tended to have higher distress and lower social support scores (P siblings reported that their loss still affected them; half stated that the experience impacted current educational and career goals. How siblings experience the death of a child with cancer may impact their long-term psychosocial well-being. Sibling-directed communication and concurrent supportive care during the cancer experience and the year after the sibling death may mitigate poor long-term outcomes. Copyright © 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.
Identification and targeting of a TACE-dependent autocrine loopwhich predicts poor prognosis in breast cancer

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Kenny, Paraic A.; Bissell, Mina J.

2005-06-15

The ability to proliferate independently of signals from other cell types is a fundamental characteristic of tumor cells. Using a 3D culture model of human breast cancer progression, we have delineated a protease-dependent autocrine loop which provides an oncogenic stimulus in the absence of proto-oncogene mutation. Inhibition of this protease, TACE/ADAM17, reverts the malignant phenotype by preventing mobilization of two crucial growth factors, Amphiregulin and TGF{alpha}. We show further that the efficacy of EGFR inhibitors is overcome by physiological levels of growth factors and that successful EGFR inhibition is dependent on reducing ligand bioavailability. Using existing patient outcome data, we demonstrate a strong correlation between TACE and TGF{alpha} expression in human breast cancers that is predictive of poor prognosis.
Improving outcomes in lung cancer: the value of the multidisciplinary health care team

Directory of Open Access Journals (Sweden)

Denton E

2016-03-01

Full Text Available Eve Denton,1 Matthew Conron2 1Allergy, Immunology and Respiratory Department, Alfred Hospital, 2Department of Respiratory and Sleep Medicine, St Vincent's Hospital, Melbourne, VIC, Australia Abstract: Lung cancer is a major worldwide health burden, with high disease-related morbidity and mortality. Unlike other major cancers, there has been little improvement in lung cancer outcomes over the past few decades, and survival remains disturbingly low. Multidisciplinary care is the cornerstone of lung cancer treatment in the developed world, despite a relative lack of evidence that this model of care improves outcomes. In this article, the available literature concerning the impact of multidisciplinary care on key measures of lung cancer outcomes is reviewed. This includes the limited observational data supporting improved survival with multidisciplinary care. The impact of multidisciplinary care on other benchmark measures of quality lung cancer treatment is also examined, including staging accuracy, access to diagnostic investigations, improvements in clinical decision making, better utilization of radiotherapy and palliative care services, and improved quality of life for patients. Health service research suggests that multidisciplinary care improves care coordination, leading to a better patient experience, and reduces variation in care, a problem in lung cancer management that has been identified worldwide. Furthermore, evidence suggests that the multidisciplinary model of care overcomes barriers to treatment, promotes standardized treatment through adherence to guidelines, and allows audit of clinical services and for these reasons is more likely to provide quality care for lung cancer patients. While there is strengthening evidence suggesting that the multidisciplinary model of care contributes to improvements in lung cancer outcomes, more quality studies are needed. Keywords: lung cancer, multidisciplinary care, mortality, tumor board
Modern Radiation Therapy and Cardiac Outcomes in Breast Cancer

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Boero, Isabel J.; Paravati, Anthony J.; Triplett, Daniel P.; Hwang, Lindsay; Matsuno, Rayna K.; Gillespie, Erin F.; Yashar, Catheryn M.; Moiseenko, Vitali; Einck, John P.; Mell, Loren K. [Department of Radiation Medicine and Applied Sciences, Moores Cancer Center, University of California, San Diego, La Jolla, California (United States); Parikh, Sahil A. [University Hospitals Case Medical Center, Harrington Heart and Vascular Institute, and Case Western Reserve University School of Medicine, Cleveland, Ohio (United States); Murphy, James D., E-mail: j2murphy@ucsd.edu [Department of Radiation Medicine and Applied Sciences, Moores Cancer Center, University of California, San Diego, La Jolla, California (United States)

2016-03-15

Purpose: Adjuvant radiation therapy, which has proven benefit against breast cancer, has historically been associated with an increased incidence of ischemic heart disease. Modern techniques have reduced this risk, but a detailed evaluation has not recently been conducted. The present study evaluated the effect of current radiation practices on ischemia-related cardiac events and procedures in a population-based study of older women with nonmetastatic breast cancer. Methods and Materials: A total of 29,102 patients diagnosed from 2000 to 2009 were identified from the Surveillance, Epidemiology, and End Results–Medicare database. Medicare claims were used to identify the radiation therapy and cardiac outcomes. Competing risk models were used to assess the effect of radiation on these outcomes. Results: Patients with left-sided breast cancer had a small increase in their risk of percutaneous coronary intervention (PCI) after radiation therapy—the 10-year cumulative incidence for these patients was 5.5% (95% confidence interval [CI] 4.9%-6.2%) and 4.5% (95% CI 4.0%-5.0%) for right-sided patients. This risk was limited to women with previous cardiac disease. For patients who underwent PCI, those with left-sided breast cancer had a significantly increased risk of cardiac mortality with a subdistribution hazard ratio of 2.02 (95% CI 1.23-3.34). No other outcome, including cardiac mortality for the entire cohort, showed a significant relationship with tumor laterality. Conclusions: For women with a history of cardiac disease, those with left-sided breast cancer who underwent radiation therapy had increased rates of PCI and a survival decrement if treated with PCI. The results of the present study could help cardiologists and radiation oncologists better stratify patients who need more aggressive cardioprotective techniques.
Modern Radiation Therapy and Cardiac Outcomes in Breast Cancer

International Nuclear Information System (INIS)

Boero, Isabel J.; Paravati, Anthony J.; Triplett, Daniel P.; Hwang, Lindsay; Matsuno, Rayna K.; Gillespie, Erin F.; Yashar, Catheryn M.; Moiseenko, Vitali; Einck, John P.; Mell, Loren K.; Parikh, Sahil A.; Murphy, James D.

2016-01-01

Purpose: Adjuvant radiation therapy, which has proven benefit against breast cancer, has historically been associated with an increased incidence of ischemic heart disease. Modern techniques have reduced this risk, but a detailed evaluation has not recently been conducted. The present study evaluated the effect of current radiation practices on ischemia-related cardiac events and procedures in a population-based study of older women with nonmetastatic breast cancer. Methods and Materials: A total of 29,102 patients diagnosed from 2000 to 2009 were identified from the Surveillance, Epidemiology, and End Results–Medicare database. Medicare claims were used to identify the radiation therapy and cardiac outcomes. Competing risk models were used to assess the effect of radiation on these outcomes. Results: Patients with left-sided breast cancer had a small increase in their risk of percutaneous coronary intervention (PCI) after radiation therapy—the 10-year cumulative incidence for these patients was 5.5% (95% confidence interval [CI] 4.9%-6.2%) and 4.5% (95% CI 4.0%-5.0%) for right-sided patients. This risk was limited to women with previous cardiac disease. For patients who underwent PCI, those with left-sided breast cancer had a significantly increased risk of cardiac mortality with a subdistribution hazard ratio of 2.02 (95% CI 1.23-3.34). No other outcome, including cardiac mortality for the entire cohort, showed a significant relationship with tumor laterality. Conclusions: For women with a history of cardiac disease, those with left-sided breast cancer who underwent radiation therapy had increased rates of PCI and a survival decrement if treated with PCI. The results of the present study could help cardiologists and radiation oncologists better stratify patients who need more aggressive cardioprotective techniques.
The effect of age on the outcome of esophageal cancer surgery

International Nuclear Information System (INIS)

Alibakhshi, Abbas; Aminian Ali; Mirsharifi, Rasoul; Jahangiri, Yosra; Dashti, Habibollah; Karimian Faramarz

2009-01-01

Surgery is still the best way for treatment of esophageal cancer. The increase in life expectancy and the rising incidence of esophageal tumors have led to a great number of elderly candidates for complex surgery. The purpose of this study was to evaluate the effects of advanced age (70 years or more) on the surgical outcome of esophagectomy for esophageal cancer at a single high-volume center. Between January 2000 and April 2006, 480 cases with esophageal cancer underwent esophagectomy in the referral cancer institute. One hundred sixty-five patients in the elderly group (70 years old or more) were compared with 315 patients in the younger group ( 0.05). With increased experience and care, the outcomes of esophagectomy in elderly patients are comparable to young patients. Advanced age alone is not a contraindication for esophagectomy. (author)
Predicting outcome from coma : man-in-the-barrel syndrome as potential pitfall

NARCIS (Netherlands)

Elting, JW; Haaxma, R; De Keyser, J; Sulter, G.

The Glasgow coma scale motor score is often used in predicting outcome after hypoxic ischemic coma. Judicious care should be exerted when using this variable in predicting outcome in patients with coma following hypotension since borderzone infarction can obscure the clinical picture. We describe a
Radical prostatectomy and positive surgical margins: tumor volume and Gleason score predicts cancer outcome

International Nuclear Information System (INIS)

La Roca, Ricardo L.R. Felts de; Fonseca, Francisco Paula da; Cunha, Isabela Werneck da; Bezerra, Stephania Martins

2013-01-01

Introduction: positive surgical margins (PSMs) are common adverse factors to predict the outcome of a patient submitted to radical prostatectomy (PR). However, not all of these men will follow with biochemical (BCR) or clinical (CR) recurrence. Relationship between PSMs with these recurrent events has to be correlated with other clinicopathological findings in order to recognize more aggressive tumors in order to recommend complementary treatment to these selected patients. Materials and methods: we retrospectively reviewed the outcome of 228 patients submitted to open retropubic RP between March 1991 and June 2008, where 161 had and 67 did not have PSMs. Minimum follow-up time was considered 2 years after surgery. BCR was considered when PSA ≥ 0.2 ng/ml. CR was determined when clinical evidence of tumor appeared. Chi-square test was used to correlate clinical and pathologic variables with PSMs. The estimated 5-year risk of BCR and CR in presence of PSMs was determined using the Kaplan-Meier method and compared to log-rank tests. Results: from the total of 228 patients, 161 (71%) had PSMs, while 67 (29%) had negative surgical margins (NSMs). Prostatic circumferential margin was the most common (43.4%) site. Univariate analysis showed statistically significant (p < 0.001) associations between the presence of PSMs and BCR, but not with CR (p = 0.06). Among 161 patients with PSMs, 61 (37.8%) presented BCR, while 100 (62.8%) did not. Predicting progression-free survival for 5 years, BCR was correlated with pathological stage; Gleason score; pre-treatment PSA; tumor volume in specimen; capsular and perineural invasion; presence and number of PSMs. RC correlated only with angiolymphatic invasion and Gleason score. Considering univariate analyses the clinicopathological factors predicting BCR for 5 years, results statistically significant links with prostate weight; pre-treatment PSA; Gleason score; pathological stage; tumor volume; PSMs; capsular and perineural
Radical prostatectomy and positive surgical margins: tumor volume and Gleason score predicts cancer outcome

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La Roca, Ricardo L.R. Felts de, E-mail: Ricardo@delarocaurologia.com.br [Hospital do Cancer A.C. Camargo, Sao Paulo, SP (Brazil); Fonseca, Francisco Paula da, E-mail: fpf@uol.com.br [Hospital do Cancer A.C. Camargo, Sao Paulo, SP (Brazil). Divisao de Urologia. Dept. de Cirurgia Pelvica; Cunha, Isabela Werneck da; Bezerra, Stephania Martins, E-mail: iwerneck@gmail.com, E-mail: stephaniab@gmail.com [Hospital do Cancer A.C. Camargo, Sao Paulo, SP (Brazil). Dept. de Patologia

2013-07-01

Introduction: positive surgical margins (PSMs) are common adverse factors to predict the outcome of a patient submitted to radical prostatectomy (PR). However, not all of these men will follow with biochemical (BCR) or clinical (CR) recurrence. Relationship between PSMs with these recurrent events has to be correlated with other clinicopathological findings in order to recognize more aggressive tumors in order to recommend complementary treatment to these selected patients. Materials and methods: we retrospectively reviewed the outcome of 228 patients submitted to open retropubic RP between March 1991 and June 2008, where 161 had and 67 did not have PSMs. Minimum follow-up time was considered 2 years after surgery. BCR was considered when PSA {>=} 0.2 ng/ml. CR was determined when clinical evidence of tumor appeared. Chi-square test was used to correlate clinical and pathologic variables with PSMs. The estimated 5-year risk of BCR and CR in presence of PSMs was determined using the Kaplan-Meier method and compared to log-rank tests. Results: from the total of 228 patients, 161 (71%) had PSMs, while 67 (29%) had negative surgical margins (NSMs). Prostatic circumferential margin was the most common (43.4%) site. Univariate analysis showed statistically significant (p < 0.001) associations between the presence of PSMs and BCR, but not with CR (p = 0.06). Among 161 patients with PSMs, 61 (37.8%) presented BCR, while 100 (62.8%) did not. Predicting progression-free survival for 5 years, BCR was correlated with pathological stage; Gleason score; pre-treatment PSA; tumor volume in specimen; capsular and perineural invasion; presence and number of PSMs. RC correlated only with angiolymphatic invasion and Gleason score. Considering univariate analyses the clinicopathological factors predicting BCR for 5 years, results statistically significant links with prostate weight; pre-treatment PSA; Gleason score; pathological stage; tumor volume; PSMs; capsular and perineural
Breast Cancer Patients' Depression Prediction by Machine Learning Approach.

Science.gov (United States)

Cvetković, Jovana

2017-09-14

One of the most common cancer in females is breasts cancer. This cancer can has high impact on the women including health and social dimensions. One of the most common social dimension is depression caused by breast cancer. Depression can impairs life quality. Depression is one of the symptom among the breast cancer patients. One of the solution is to eliminate the depression in breast cancer patients is by treatments but these treatments can has different unpredictable impacts on the patients. Therefore it is suitable to develop algorithm in order to predict the depression range.
Breast cancer data analysis for survivability studies and prediction.

Science.gov (United States)

Shukla, Nagesh; Hagenbuchner, Markus; Win, Khin Than; Yang, Jack

2018-03-01

Breast cancer is the most common cancer affecting females worldwide. Breast cancer survivability prediction is challenging and a complex research task. Existing approaches engage statistical methods or supervised machine learning to assess/predict the survival prospects of patients. The main objectives of this paper is to develop a robust data analytical model which can assist in (i) a better understanding of breast cancer survivability in presence of missing data, (ii) providing better insights into factors associated with patient survivability, and (iii) establishing cohorts of patients that share similar properties. Unsupervised data mining methods viz. the self-organising map (SOM) and density-based spatial clustering of applications with noise (DBSCAN) is used to create patient cohort clusters. These clusters, with associated patterns, were used to train multilayer perceptron (MLP) model for improved patient survivability analysis. A large dataset available from SEER program is used in this study to identify patterns associated with the survivability of breast cancer patients. Information gain was computed for the purpose of variable selection. All of these methods are data-driven and require little (if any) input from users or experts. SOM consolidated patients into cohorts of patients with similar properties. From this, DBSCAN identified and extracted nine cohorts (clusters). It is found that patients in each of the nine clusters have different survivability time. The separation of patients into clusters improved the overall survival prediction accuracy based on MLP and revealed intricate conditions that affect the accuracy of a prediction. A new, entirely data driven approach based on unsupervised learning methods improves understanding and helps identify patterns associated with the survivability of patient. The results of the analysis can be used to segment the historical patient data into clusters or subsets, which share common variable values and
Life after endometrial cancer: A systematic review of patient-reported outcomes.

Science.gov (United States)

Shisler, Robert; Sinnott, Jennifer A; Wang, Vivian; Hebert, Courtney; Salani, Ritu; Felix, Ashley S

2018-02-01

Women with endometrial cancer (EC) are the second largest population of female cancer survivors in the United States. However, the outcomes of EC survivors, from the patient perspective, are not well-understood. Therefore, we conducted a systematic review of patient-reported outcomes (PROs) following an EC diagnosis. We searched MEDLINE, EMBASE, Scopus, CINAHL, and reference lists to identify published observational studies that examined PROs among women with EC. Reviewers independently reviewed eligible full-text study articles and conducted data extraction. We qualitatively summarized included articles according to exposures [e.g. body mass index (BMI), treatment, etc.] or specific PROs (e.g. sexual function). Of 1722 unique studies, 102 full-text articles were reviewed, of which a total of 27 studies fulfilled the inclusion criteria. The most commonly used PRO questionnaires were the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) (n=9), Short Form 36 Questionnaire (SF-36, n=8), the Functional Assessment of Cancer Therapy-General (FACT-G, n=5), and the Female Sexual Function Index (FSFI, n=4). Obesity was associated with lower quality of life (QOL) and physical functioning. Treatment type affected several outcomes. Laparoscopy generally resulted in better QOL outcomes than laparotomy. Likewise, vaginal brachytherapy was associated with better outcomes compared to external beam radiation. Sexual function outcomes were dependent on age, time since diagnosis, and having consulted a physician before engaging in sexual activities. In addition, a physical activity intervention was associated with improved sexual interest but not sexual function. Our review provides insight into the experience of EC survivors from the patient perspective. Factors that contribute to QOL, such as pain, fatigue, emotional and social functioning, should be monitored following an EC diagnosis. Copyright © 2017 Elsevier Inc
RUNX1 and RUNX3 protect against YAP-mediated EMT, stem-ness and shorter survival outcomes in breast cancer

Science.gov (United States)

Kulkarni, Madhura; Tan, Tuan Zea; Syed Sulaiman, Nurfarhanah Bte; Lamar, John M.; Bansal, Prashali; Cui, Jianzhou; Qiao, Yiting; Ito, Yoshiaki

2018-01-01

Hippo pathway target, YAP has emerged as an important player in solid tumor progression. Here, we identify RUNX1 and RUNX3 as novel negative regulators of oncogenic function of YAP in the context of breast cancer. RUNX proteins are one of the first transcription factors identified to interact with YAP. RUNX1 or RUNX3 expression abrogates YAP-mediated pro-tumorigenic properties of mammary epithelial cell lines in an interaction dependent manner. RUNX1 and RUNX3 inhibit YAP-mediated migration and stem-ness properties of mammary epithelial cell lines by co-regulating YAP-mediated gene expression. Analysis of whole genome expression profiles of breast cancer samples revealed significant co-relation between YAP–RUNX1/RUNX3 expression levels and survival outcomes of breast cancer patients. High RUNX1/RUNX3 expression proved protective towards YAP-dependent patient survival outcomes. High YAP in breast cancer patients’ expression profiles co-related with EMT and stem-ness gene signature enrichment. High RUNX1/RUNX3 expression along with high YAP reflected lower enrichment of EMT and stem-ness signatures. This antagonistic activity of RUNX1 and RUNX3 towards oncogenic function of YAP identified in mammary epithelial cells as well as in breast cancer expression profiles gives a novel mechanistic insight into oncogene–tumor suppressor interplay in the context of breast cancer progression. The novel interplay between YAP, RUNX1 and RUNX3 and its significance in breast cancer progression can serve as a prognostic tool to predict cancer recurrence. PMID:29581836

The EPOS-CC Score: An Integration of Independent, Tumor- and Patient-Associated Risk Factors to Predict 5-years Overall Survival Following Colorectal Cancer Surgery.

Science.gov (United States)

Haga, Yoshio; Ikejiri, Koji; Wada, Yasuo; Ikenaga, Masakazu; Koike, Shoichiro; Nakamura, Seiji; Koseki, Masato

2015-06-01

Surgical audit is an essential task for the estimation of postoperative outcome and comparison of quality of care. Previous studies on surgical audits focused on short-term outcomes, such as postoperative mortality. We propose a surgical audit evaluating long-term outcome following colorectal cancer surgery. The predictive model for this audit is designated as 'Estimation of Postoperative Overall Survival for Colorectal Cancer (EPOS-CC)'. Thirty-one tumor-related and physiological variables were prospectively collected in 889 patients undergoing elective resection for colorectal cancer between April 2005 and April 2007 in 16 Japanese hospitals. Postoperative overall survival was assessed over a 5-years period. The EPOS-CC score was established by selecting significant variables in a uni- and multivariate analysis and allocating a risk-adjusted multiplication factor to each variable using Cox regression analysis. For validation, the EPOS-CC score was compared to the predictive power of UICC stage. Inter-hospital variability of the observed-to-estimated 5-years survival was assessed to estimate quality of care. Among the 889 patients, 804 (90%) completed the 5-years follow-up. Univariate analysis displayed a significant correlation with 5-years survival for 14 physiological and nine tumor-related variables (p model for the prediction of survival. Risk-adjusted multiplication factors between 1.5 (distant metastasis) and 0.16 (serum sodium level) were accorded to the different variables. The predictive power of EPOS-CC was superior to the one of UICC stage; area under the curve 0.87, 95% CI 0.85-0.90 for EPOS-CC, and 0.80, 0.76-0.83 for UICC stage, p < 0.001. Quality of care did not differ between hospitals. The EPOS-CC score including the independent variables age, performance status, serum sodium level, TNM stage, and lymphatic invasion is superior to the UICC stage in the prediction of 5-years overall survival. This higher accuracy might be explained by the
Developing a risk prediction model for the functional outcome after hip arthroscopy.

Science.gov (United States)

Stephan, Patrick; Röling, Maarten A; Mathijssen, Nina M C; Hannink, Gerjon; Bloem, Rolf M

2018-04-19

Hip arthroscopic treatment is not equally beneficial for every patient undergoing this procedure. Therefore, the purpose of this study was to develop a clinical prediction model for functional outcome after surgery based on preoperative factors. Prospective data was collected on a cohort of 205 patients having undergone hip arthroscopy between 2011 and 2015. Demographic and clinical variables and patient reported outcome (PRO) scores were collected, and considered as potential predictors. Successful outcome was defined as either a Hip Outcome Score (HOS)-ADL score of over 80% or improvement of 23%, defined by the minimal clinical important difference, 1 year after surgery. The prediction model was developed using backward logistic regression. Regression coefficients were converted into an easy to use prediction rule. The analysis included 203 patients, of which 74% had a successful outcome. Female gender (OR: 0.37 (95% CI 0.17-0.83); p = 0.02), pincer impingement (OR: 0.47 (95% CI 0.21-1.09); p = 0.08), labral tear (OR: 0.46 (95% CI 0.20-1.06); p = 0.07), HOS-ADL score (IQR OR: 2.01 (95% CI 0.99-4.08); p = 0.05), WHOQOL physical (IQR OR: 0.43 (95% CI 0.22-0.87); p = 0.02) and WHOQOL psychological (IQR OR: 2.40 (95% CI 1.38-4.18); p = prediction model of successful functional outcome 1 year after hip arthroscopy. The model's discriminating accuracy turned out to be fair, as 71% (95% CI: 64-80%) of the patients were classified correctly. The developed prediction model can predict the functional outcome of patients that are considered for a hip arthroscopic intervention, containing six easy accessible preoperative risk factors. The model can be further improved trough external validation and/or adding additional potential predictors.
Do Patient Characteristics Predict Outcome of Psychodynamic Psychotherapy for Social Anxiety Disorder?

Directory of Open Access Journals (Sweden)

Jörg Wiltink

Full Text Available Little is known about patient characteristics as predictors for outcome in manualized short term psychodynamic psychotherapy (PDT. No study has addressed which patient variables predict outcome of PDT for social anxiety disorder.In the largest multicenter trial on psychotherapy of social anxiety (SA to date comparing cognitive therapy, PDT and wait list condition N = 230 patients were assigned to receive PDT, of which N = 166 completed treatment. Treatment outcome was assessed based on diverse parameters such as endstate functioning, remission, response, and drop-out. The relationship between patient characteristics (demographic variables, mental co-morbidity, personality, interpersonal problems and outcome was analysed using logistic and linear regressions.Pre-treatment SA predicted up to 39 percent of variance of outcome. Only few additional baseline characteristics predicted better treatment outcome (namely, lower comorbidity and interpersonal problems with a limited proportion of incremental variance (5.5 to 10 percent, while, e.g., shame, self-esteem or harm avoidance did not.We argue that the central importance of pre-treatment symptom severity for predicting outcomes should advocate alternative treatment strategies (e.g. longer treatments, combination of psychotherapy and medication in those who are most disturbed. Given the relatively small amount of variance explained by the other patient characteristics, process variables and patient-therapist interaction should additionally be taken into account in future research.Controlled-trials.com/ISRCTN53517394.
An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation.

Science.gov (United States)

Candido Dos Reis, Francisco J; Wishart, Gordon C; Dicks, Ed M; Greenberg, David; Rashbass, Jem; Schmidt, Marjanka K; van den Broek, Alexandra J; Ellis, Ian O; Green, Andrew; Rakha, Emad; Maishman, Tom; Eccles, Diana M; Pharoah, Paul D P

2017-05-22

PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age
Protein-Based Urine Test Predicts Kidney Transplant Outcomes

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... News Releases News Release Thursday, August 22, 2013 Protein-based urine test predicts kidney transplant outcomes NIH- ... supporting development of noninvasive tests. Levels of a protein in the urine of kidney transplant recipients can ...
The REDUCE metagram: a comprehensive prediction tool for determining the utility of dutasteride chemoprevention in men at risk for prostate cancer

Directory of Open Access Journals (Sweden)

Carvell eNguyen

2012-10-01

Full Text Available Introduction: 5-alpha reductase inhibitors can reduce the risk of prostate cancer but can be associated with significant side effects. A library of nomograms which predict the risk of clinical endpoints relevant to dutasteride treatment may help determine if chemoprevention is suited to the individual patient. Methods: Data from the REDUCE trial was used to identify predictive factors for nine endpoints relevant to dutasteride treatment. Using the treatment and placebo groups from the biopsy cohort, Cox proportional hazards and competing risks regression models were used to build 18 nomograms, whose predictive ability was measured by concordance index and calibration plots. Results: A total of 18 nomograms assessing the risks of cancer, high-grade cancer, high grade prostatic intraepithelial neoplasia (HGPIN, atypical small acinar proliferation (ASAP, erectile dysfunction (ED, acute urinary retention (AUR, gynecomastia, urinary tract infection (UTI and BPH-related surgery either on or off dutasteride were created. The nomograms for cancer, high grade cancer, ED, AUR, and BPH-related surgery demonstrated good discrimination and calibration while those for gynecomastia, UTI, HGPIN, and ASAP predicted no better than random chance. Conclusions: To aid patients in determining whether the benefits of dutasteride use outweigh the risks, we have developed a comprehensive metagram that can generate individualized risks of 9 outcomes relevant to men considering chemoprevention. Better models based on more predictive markers are needed for some of the endpoints but the current metagram demonstrates potential as a tool for patient counseling and decision making that is accessible, intuitive, and clinically relevant.
The REDUCE metagram: a comprehensive prediction tool for determining the utility of dutasteride chemoprevention in men at risk for prostate cancer

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Carvell T.; Isariyawongse, Brandon [Department of Urology, Glickman Urological and Kidney Institute, Cleveland Clinic Foundation, Cleveland, OH (United States); Yu, Changhong; Kattan, Michael W., E-mail: kattanm@ccf.org [Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH (United States)

2012-10-11

Introduction: 5-alpha reductase inhibitors can reduce the risk of prostate cancer (PCa) but can be associated with significant side effects. A library of nomograms which predict the risk of clinical endpoints relevant to dutasteride treatment may help determine if chemoprevention is suited to the individual patient. Methods: Data from the REDUCE trial was used to identify predictive factors for 9 endpoints relevant to dutasteride treatment. Using the treatment and placebo groups from the biopsy cohort, Cox proportional hazards (PH) and competing risks regression (CRR) models were used to build 18 nomograms, whose predictive ability was measured by concordance index (CI) and calibration plots. Results: A total of 18 nomograms assessing the risks of cancer, high grade cancer, high grade prostatic intraepithelial neoplasia (HGPIN), atypical small acinar proliferation (ASAP), erectile dysfunction (ED), acute urinary retention (AUR), gynecomastia, urinary tract infection (UTI) and BPH-related surgery either on or off dutasteride were created. The nomograms for cancer, high grade cancer, ED, AUR, and BPH-related surgery demonstrated good discrimination and calibration while those for gynecomastia, UTI, HGPIN, and ASAP predicted no better than random chance. Conclusions: To aid patients in determining whether the benefits of dutasteride use outweigh the risks, we have developed a comprehensive metagram that can generate individualized risks of 9 outcomes relevant to men considering chemoprevention. Better models based on more predictive markers are needed for some of the endpoints but the current metagram demonstrates potential as a tool for patient counseling and decision-making that is accessible, intuitive, and clinically relevant.
The REDUCE metagram: a comprehensive prediction tool for determining the utility of dutasteride chemoprevention in men at risk for prostate cancer

International Nuclear Information System (INIS)

Nguyen, Carvell T.; Isariyawongse, Brandon; Yu, Changhong; Kattan, Michael W.

2012-01-01

Introduction: 5-alpha reductase inhibitors can reduce the risk of prostate cancer (PCa) but can be associated with significant side effects. A library of nomograms which predict the risk of clinical endpoints relevant to dutasteride treatment may help determine if chemoprevention is suited to the individual patient. Methods: Data from the REDUCE trial was used to identify predictive factors for 9 endpoints relevant to dutasteride treatment. Using the treatment and placebo groups from the biopsy cohort, Cox proportional hazards (PH) and competing risks regression (CRR) models were used to build 18 nomograms, whose predictive ability was measured by concordance index (CI) and calibration plots. Results: A total of 18 nomograms assessing the risks of cancer, high grade cancer, high grade prostatic intraepithelial neoplasia (HGPIN), atypical small acinar proliferation (ASAP), erectile dysfunction (ED), acute urinary retention (AUR), gynecomastia, urinary tract infection (UTI) and BPH-related surgery either on or off dutasteride were created. The nomograms for cancer, high grade cancer, ED, AUR, and BPH-related surgery demonstrated good discrimination and calibration while those for gynecomastia, UTI, HGPIN, and ASAP predicted no better than random chance. Conclusions: To aid patients in determining whether the benefits of dutasteride use outweigh the risks, we have developed a comprehensive metagram that can generate individualized risks of 9 outcomes relevant to men considering chemoprevention. Better models based on more predictive markers are needed for some of the endpoints but the current metagram demonstrates potential as a tool for patient counseling and decision-making that is accessible, intuitive, and clinically relevant.
Prostatectomy-based validation of combined urine and plasma test for predicting high grade prostate cancer.

Science.gov (United States)

Albitar, Maher; Ma, Wanlong; Lund, Lars; Shahbaba, Babak; Uchio, Edward; Feddersen, Søren; Moylan, Donald; Wojno, Kirk; Shore, Neal

2018-03-01

Distinguishing between low- and high-grade prostate cancers (PCa) is important, but biopsy may underestimate the actual grade of cancer. We have previously shown that urine/plasma-based prostate-specific biomarkers can predict high grade PCa. Our objective was to determine the accuracy of a test using cell-free RNA levels of biomarkers in predicting prostatectomy results. This multicenter community-based prospective study was conducted using urine/blood samples collected from 306 patients. All recruited patients were treatment-naïve, without metastases, and had been biopsied, designated a Gleason Score (GS) based on biopsy, and assigned to prostatectomy prior to participation in the study. The primary outcome measure was the urine/plasma test accuracy in predicting high grade PCa on prostatectomy compared with biopsy findings. Sensitivity and specificity were calculated using standard formulas, while comparisons between groups were performed using the Wilcoxon Rank Sum, Kruskal-Wallis, Chi-Square, and Fisher's exact test. GS as assigned by standard 10-12 core biopsies was 3 + 3 in 90 (29.4%), 3 + 4 in 122 (39.8%), 4 + 3 in 50 (16.3%), and > 4 + 3 in 44 (14.4%) patients. The urine/plasma assay confirmed a previous validation and was highly accurate in predicting the presence of high-grade PCa (Gleason ≥3 + 4) with sensitivity between 88% and 95% as verified by prostatectomy findings. GS was upgraded after prostatectomy in 27% of patients and downgraded in 12% of patients. This plasma/urine biomarker test accurately predicts high grade cancer as determined by prostatectomy with a sensitivity at 92-97%, while the sensitivity of core biopsies was 78%. © 2018 Wiley Periodicals, Inc.
Diffusion-weighted magnetic resonance imaging for prediction of insignificant prostate cancer in potential candidates for active surveillance

International Nuclear Information System (INIS)

Kim, Tae Heon; Jeong, Jae Yong; Lee, Sin Woo; Sung, Hyun Hwan; Jeon, Hwang Gyun; Jeong, Byong Chang; Seo, Seong Il; Lee, Hyun Moo; Choi, Han Yong; Jeon, Seong Soo; Kim, Chan Kyo; Park, Byung Kwan

2015-01-01

To investigate whether the apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (DW-MRI) could help improve the prediction of insignificant prostate cancer in candidates for active surveillance (AS). Enrolled in this retrospective study were 287 AS candidates who underwent DW-MRI before radical prostatectomy. Patients were stratified into two groups; Group A consisted of patients with no visible tumour or a suspected tumour ADC value > 0.830 x 10 -3 mm 2 /sec and Group B consisted of patients with a suspected tumour ADC value < 0.830 x 10 -3 mm 2 /sec. We compared pathological outcomes in each group. Group A had 243 (84.7 %) patients and Group B had 44 (15.3 %) patients. The proportion of organ-confined Gleason ≤ 6 disease and insignificant prostate cancer was significantly higher in Group A than Group B (61.3 % vs. 38.6 %, p = 0.005 and 47.7 % vs. 25.0 %, p = 0.005, respectively). On multivariate analysis, a high ADC value was the independent predictor of organ-confined Gleason ≤ 6 disease and insignificant prostate cancer (odds ratio = 2.43, p = 0.011 and odds ratio = 2.74, p = 0.009, respectively). Tumour ADC values may be a useful marker for predicting insignificant prostate cancer in candidates for AS. (orig.)
Neonatal Pulmonary MRI of Bronchopulmonary Dysplasia Predicts Short-term Clinical Outcomes.

Science.gov (United States)

Higano, Nara S; Spielberg, David R; Fleck, Robert J; Schapiro, Andrew H; Walkup, Laura L; Hahn, Andrew D; Tkach, Jean A; Kingma, Paul S; Merhar, Stephanie L; Fain, Sean B; Woods, Jason C

2018-05-23

Bronchopulmonary dysplasia (BPD) is a serious neonatal pulmonary condition associated with premature birth, but the underlying parenchymal disease and trajectory are poorly characterized. The current NICHD/NHLBI definition of BPD severity is based on degree of prematurity and extent of oxygen requirement. However, no clear link exists between initial diagnosis and clinical outcomes. We hypothesized that magnetic resonance imaging (MRI) of structural parenchymal abnormalities will correlate with NICHD-defined BPD disease severity and predict short-term respiratory outcomes. Forty-two neonates (20 severe BPD, 6 moderate, 7 mild, 9 non-BPD controls; 40±3 weeks post-menstrual age) underwent quiet-breathing structural pulmonary MRI (ultrashort echo-time and gradient echo) in a NICU-sited, neonatal-sized 1.5T scanner, without sedation or respiratory support unless already clinically prescribed. Disease severity was scored independently by two radiologists. Mean scores were compared to clinical severity and short-term respiratory outcomes. Outcomes were predicted using univariate and multivariable models including clinical data and scores. MRI scores significantly correlated with severities and predicted respiratory support at NICU discharge (P<0.0001). In multivariable models, MRI scores were by far the strongest predictor of respiratory support duration over clinical data, including birth weight and gestational age. Notably, NICHD severity level was not predictive of discharge support. Quiet-breathing neonatal pulmonary MRI can independently assess structural abnormalities of BPD, describe disease severity, and predict short-term outcomes more accurately than any individual standard clinical measure. Importantly, this non-ionizing technique can be implemented to phenotype disease and has potential to serially assess efficacy of individualized therapies.
Diet Quality Scores and Prediction of All-Cause, Cardiovascular and Cancer Mortality in a Pan-European Cohort Study.

Directory of Open Access Journals (Sweden)

Camille Lassale

Full Text Available Scores of overall diet quality have received increasing attention in relation to disease aetiology; however, their value in risk prediction has been little examined. The objective was to assess and compare the association and predictive performance of 10 diet quality scores on 10-year risk of all-cause, CVD and cancer mortality in 451,256 healthy participants to the European Prospective Investigation into Cancer and Nutrition, followed-up for a median of 12.8y. All dietary scores studied showed significant inverse associations with all outcomes. The range of HRs (95% CI in the top vs. lowest quartile of dietary scores in a composite model including non-invasive factors (age, sex, smoking, body mass index, education, physical activity and study centre was 0.75 (0.72-0.79 to 0.88 (0.84-0.92 for all-cause, 0.76 (0.69-0.83 to 0.84 (0.76-0.92 for CVD and 0.78 (0.73-0.83 to 0.91 (0.85-0.97 for cancer mortality. Models with dietary scores alone showed low discrimination, but composite models also including age, sex and other non-invasive factors showed good discrimination and calibration, which varied little between different diet scores examined. Mean C-statistic of full models was 0.73, 0.80 and 0.71 for all-cause, CVD and cancer mortality. Dietary scores have poor predictive performance for 10-year mortality risk when used in isolation but display good predictive ability in combination with other non-invasive common risk factors.
Prognostic factors in patients with advanced cancer: use of the patient-generated subjective global assessment in survival prediction.

Science.gov (United States)

Martin, Lisa; Watanabe, Sharon; Fainsinger, Robin; Lau, Francis; Ghosh, Sunita; Quan, Hue; Atkins, Marlis; Fassbender, Konrad; Downing, G Michael; Baracos, Vickie

2010-10-01

To determine whether elements of a standard nutritional screening assessment are independently prognostic of survival in patients with advanced cancer. A prospective nested cohort of patients with metastatic cancer were accrued from different units of a Regional Palliative Care Program. Patients completed a nutritional screen on admission. Data included age, sex, cancer site, height, weight history, dietary intake, 13 nutrition impact symptoms, and patient- and physician-reported performance status (PS). Univariate and multivariate survival analyses were conducted. Concordance statistics (c-statistics) were used to test the predictive accuracy of models based on training and validation sets; a c-statistic of 0.5 indicates the model predicts the outcome as well as chance; perfect prediction has a c-statistic of 1.0. A training set of patients in palliative home care (n = 1,164) was used to identify prognostic variables. Primary disease site, PS, short-term weight change (either gain or loss), dietary intake, and dysphagia predicted survival in multivariate analysis (P statistics between predicted and observed responses for survival in the training set (0.90) and validation set (0.88; n = 603). The addition of weight change, dietary intake, and dysphagia did not further improve the c-statistic of the model. The c-statistic was also not altered by substituting physician-rated palliative PS for patient-reported PS. We demonstrate a high probability of concordance between predicted and observed survival for patients in distinct palliative care settings (home care, tertiary inpatient, ambulatory outpatient) based on patient-reported information.
Socio-economic status plays important roles in childhood cancer treatment outcome in Indonesia.

Science.gov (United States)

Mostert, Saskia; Gunawan, Stefanus; Wolters, Emma; van de Ven, Peter; Sitaresmi, Mei; Dongen, Josephine van; Veerman, Anjo; Mantik, Max; Kaspers, Gertjan

2012-01-01

The influence of parental socio-economic status on childhood cancer treatment outcome in low-income countries has not been sufficiently investigated. Our study examined this influence and explored parental experiences during cancer treatment of their children in an Indonesian academic hospital. Medical charts of 145 children diagnosed with cancer between 1999 and 2009 were reviewed retrospectively. From October 2011 until January 2012, 40 caretakers were interviewed using semi-structured questionnaires. Of all patients, 48% abandoned treatment, 34% experienced death, 9% had progressive/ relapsed disease, and 9% overall event-free survival. Prosperous patients had better treatment outcome than poor patients (Pfate or God (55%). Causes of cancer were thought to be destiny (35%) or God's punishment (23%). Alternative treatment could (18%) or might (50%) cure cancer. Most parents (95%) would like more information about cancer and treatment. More contact with doctors was desired (98%). Income decreased during treatment (55%). Parents lost employment (48% fathers, 10% mothers), most of whom stated this loss was caused by their child's cancer (84% fathers, 100% mothers). Loss of income led to financial difficulties (63%) and debts (55%). Treatment abandonment was most important reason for treatment failure. Treatment outcome was determined by parental socio-economic status. Childhood cancer survival could improve if financial constraints and provision of information and guidance are better addressed.
Impact of Thin-Section Computed Tomography-Determined Combined Pulmonary Fibrosis and Emphysema on Outcomes Among Patients With Resected Lung Cancer.

Science.gov (United States)

Hashimoto, Naozumi; Iwano, Shingo; Kawaguchi, Koji; Fukui, Takayuki; Fukumoto, Koichi; Nakamura, Shota; Mori, Shunsuke; Sakamoto, Koji; Wakai, Kenji; Yokoi, Kohei; Hasegawa, Yoshinori

2016-08-01

There is only limited information on the clinical impact of combined pulmonary fibrosis and emphysema (CPFE) on postoperative and survival outcomes among patients with resected lung cancer. In a retrospective analysis, data were reviewed from 685 patients with resected lung cancer between 2006 and 2011. The clinical impact of thin-section computed tomography (TSCT)-determined emphysema, fibrosis, and CPFE on postoperative and survival outcomes was evaluated. The emphysema group comprised 32.4% of the study population, the fibrosis group 2.8%, and the CPFE group 8.3%. The CPFE group had a more advanced pathologic stage and higher prevalence of squamous cell carcinoma as compared with the normal group without emphysema or fibrosis findings on TSCT. The incidence of postoperative complications was significantly higher in the CPFE group. Overall, the 30-day mortality in the CPFE group was 5.3%. Cancer recurrence at pathologic stage I and death due to either cancer or other causes were significantly higher in the CPFE group. Survival curves indicated that a finding of CPFE was associated with worse overall survival for patients with any stage disease. Multivariate analysis suggested that pathologic stage and CPFE were independent factors associated with worse overall survival. The adjusted hazard ratio of overall survival for the CPFE group versus the normal group was 2.990 (95% confidence interval: 1.801 to 4.962). Among patients with resected lung cancer, the presence of TSCT-determined CPFE might predict worse postoperative and survival outcomes. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
Proteins Annexin A2 and PSA in Prostate Cancer Biopsies Do Not Predict Biochemical Failure.

Science.gov (United States)

Lamb, David S; Sondhauss, Sven; Dunne, Jonathan C; Woods, Lisa; Delahunt, Brett; Ferguson, Peter; Murray, Judith; Nacey, John N; Denham, James W; Jordan, T William

2017-12-01

We previously reported the use of mass spectrometry and western blotting to identify proteins from tumour regions of formalin-fixed paraffin-embedded biopsies from 16 men who presented with apparently localized prostate cancer, and found that annexin A2 (ANXA2) appeared to be a better predictor of subsequent biochemical failure than prostate-specific antigen (PSA). In this follow-up study, ANXA2 and PSA were measured using western blotting of proteins extracted from biopsies from 37 men from a subsequent prostate cancer trial. No significant differences in ANXA2 and PSA levels were observed between men with and without biochemical failure. The statistical effect sizes were small, d=0.116 for ANXA2, and 0.266 for PSA. ANXA2 and PSA proteins measured from biopsy tumour regions are unlikely to be good biomarkers for prediction of the clinical outcome of prostate cancer presenting with apparently localized disease. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
Neonatal Sleep-Wake Analyses Predict 18-month Neurodevelopmental Outcomes.

Science.gov (United States)

Shellhaas, Renée A; Burns, Joseph W; Hassan, Fauziya; Carlson, Martha D; Barks, John D E; Chervin, Ronald D

2017-11-01

The neurological examination of critically ill neonates is largely limited to reflexive behavior. The exam often ignores sleep-wake physiology that may reflect brain integrity and influence long-term outcomes. We assessed whether polysomnography and concurrent cerebral near-infrared spectroscopy (NIRS) might improve prediction of 18-month neurodevelopmental outcomes. Term newborns with suspected seizures underwent standardized neurologic examinations to generate Thompson scores and had 12-hour bedside polysomnography with concurrent cerebral NIRS. For each infant, the distribution of sleep-wake stages and electroencephalogram delta power were computed. NIRS-derived fractional tissue oxygen extraction (FTOE) was calculated across sleep-wake stages. At age 18-22 months, surviving participants were evaluated with Bayley Scales of Infant Development (Bayley-III), 3rd edition. Twenty-nine participants completed Bayley-III. Increased newborn time in quiet sleep predicted worse 18-month cognitive and motor scores (robust regression models, adjusted r2 = 0.22, p = .007, and 0.27, .004, respectively). Decreased 0.5-2 Hz electroencephalograph (EEG) power during quiet sleep predicted worse 18-month language and motor scores (adjusted r2 = 0.25, p = .0005, and 0.33, .001, respectively). Predictive values remained significant after adjustment for neonatal Thompson scores or exposure to phenobarbital. Similarly, an attenuated difference in FTOE, between neonatal wakefulness and quiet sleep, predicted worse 18-month cognitive, language, and motor scores in adjusted analyses (each p sleep-as quantified by increased time in quiet sleep, lower electroencephalogram delta power during that stage, and muted differences in FTOE between quiet sleep and wakefulness-may improve prediction of adverse long-term outcomes for newborns with neurological dysfunction. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved
Low plasma bicarbonate predicts poor outcome of cerebral malaria ...

African Journals Online (AJOL)

Malaria remains a major cause of morbidity and mortality in many sub Saharan countries and cerebral malaria is widely recognised as one of its most fatal forms. We studied the predictive value of routine biochemical laboratory indices in predicting the outcome of cerebral malaria in 50 Nigerian children ages 9 months to 6 ...
Body Composition in Relation to Clinical Outcomes in Renal Cell Cancer

NARCIS (Netherlands)

Vrieling, Alina; Kampman, Ellen; Knijnenburg, Nathalja C.; Mulders, Peter F.; Sedelaar, J.P.M.; Baracos, Vickie E.; Kiemeney, Lambertus A.

2016-01-01

Context: Several studies suggest that body composition (ie, body proportions of muscle and fat defined by computed tomography) is associated with clinical outcomes of several cancer types, including renal cell cancer (RCC). Objective: To conduct a systematic review and meta-analysis of the evidence
Nutritional predictors for postoperative short-term and long-term outcomes of patients with gastric cancer.

Science.gov (United States)

Kanda, Mitsuro; Mizuno, Akira; Tanaka, Chie; Kobayashi, Daisuke; Fujiwara, Michitaka; Iwata, Naoki; Hayashi, Masamichi; Yamada, Suguru; Nakayama, Goro; Fujii, Tsutomu; Sugimoto, Hiroyuki; Koike, Masahiko; Takami, Hideki; Niwa, Yukiko; Murotani, Kenta; Kodera, Yasuhiro

2016-06-01

Evidence indicates that impaired immunocompetence and nutritional status adversely affect short-term and long-term outcomes of patients with cancer. We aimed to evaluate the clinical significance of preoperative immunocompetence and nutritional status according to Onodera's prognostic nutrition index (PNI) among patients who underwent curative gastrectomy for gastric cancer (GC).This study included 260 patients with stage II/III GC who underwent R0 resection. The predictive values of preoperative nutritional status for postoperative outcome (morbidity and prognosis) were evaluated. Onodera's PNI was calculated as follows: 10 × serum albumin (g/dL) + 0.005 × lymphocyte count (per mm).The mean preoperative PNI was 47.8. The area under the curve for predicting complications was greater for PNI compared with the serum albumin concentration or lymphocyte count. Multivariate analysis identified preoperative PNI < 47 as an independent predictor of postoperative morbidity. Moreover, patients in the PNI < 47 group experienced significantly shorter overall and disease-free survival compared with those in the PNI ≥ 47 group, notably because of a higher prevalence of hematogenous metastasis as the initial recurrence. Subgroup analysis according to disease stage and postoperative adjuvant treatment revealed that the prognostic significance of PNI was more apparent in patients with stage II GC and in those who received adjuvant chemotherapy.Preoperative PNI is easy and inexpensive to determine, and our findings indicate that PNI served as a significant predictor of postoperative morbidity, prognosis, and recurrence patterns of patients with stage II/III GC.

The impact of predictive genetic testing for hereditary nonpolyposis colorectal cancer: three years after testing.

Science.gov (United States)

Collins, Veronica R; Meiser, Bettina; Ukoumunne, Obioha C; Gaff, Clara; St John, D James; Halliday, Jane L

2007-05-01

To fully assess predictive genetic testing programs, it is important to assess outcomes over periods of time longer than the 1-year follow-up reported in the literature. We conducted a 3-year study of individuals who received predictive genetic test results for previously identified familial mutations in Australian Familial Cancer Clinics. Questionnaires were sent before attendance at the familial cancer clinic and 2 weeks, 4 months, 1 year, and 3 years after receiving test results. Psychological measures were included each time, and preventive behaviors were assessed at baseline and 1 and 3 years. Psychological measures were adjusted for age, gender, and baseline score. The study included 19 carriers and 54 non-carriers. We previously reported an increase in mean cancer-specific distress in carriers at 2 weeks with a return to baseline levels by 12 months. This level was maintained until 3 years. Non-carriers showed sustained decreases after testing with a significantly lower level at 3 years compared with baseline (P depression and anxiety scores did not differ between carriers and non-carriers and, at 3 years, were similar to baseline. All carriers and 7% of non-carriers had had a colonoscopy by 3 years, and 69% of 13 female carriers had undergone gynecological screening in the previous 2 years. Prophylactic surgery was rare. This report of long-term data indicates appropriate screening and improved psychological measures for non-carriers with no evidence of undue psychological distress in carriers of hereditary nonpolyposis colorectal cancer mutations.
A deep learning-based multi-model ensemble method for cancer prediction.

Science.gov (United States)

Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

2018-01-01

Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.
The influence of hospital volume on long-term oncological outcome after rectal cancer surgery

NARCIS (Netherlands)

Jonker, Frederik H. W.; Hagemans, Jan A. W.; Burger, Jacobus W. A.; Verhoef, Cornelis; Borstlap, Wernard A. A.; Tanis, Pieter J.; Aalbers, A.; Acherman, Y.; Algie, G. D.; Alting von Geusau, B.; Amelung, F.; Aukema, T. S.; Bakker, I. S.; Bartels, S. A.; Basha, S.; Bastiaansen, A. J. N. M.; Belgers, E.; Bemelman, W. A.; Bleeker, W.; Blok, J.; Bosker, R. J. I.; Bosmans, J. W.; Boute, M. C.; Bouvy, N. D.; Bouwman, H.; Brandt-Kerkhof, A.; Brinkman, D. J.; Bruin, S.; Bruns, E. R. J.; Burbach, J. P. M.; Clermonts, S.; Coene, P. P. L. O.; Compaan, C.; Consten, E. C. J.; Darbyshire, T.; de Mik, S. M. L.; de Graaf, E. J. R.; de Groot, I.; de Vos Tot Nederveen Cappel, R. J. L.; de Wilt, J. H. W.; van der Wolde, J.; den Boer, F. C.; Dekker, J. W. T.; Demirkiran, A.; van Duijvendijk, P.; Marres, C. C.; Musters, G. D.; van Rossem, C. C.; Schreuder, A. M.; Swank, H. A.

2017-01-01

The association between hospital volume and outcome in rectal cancer surgery is still subject of debate. The purpose of this study was to assess the impact of hospital volume on outcomes of rectal cancer surgery in the Netherlands in 2011. In this collaborative research with a cross-sectional study
[Gastroschisis: Prenatal ultrasonography and obstetrical criteria for predicting neonatal outcome].

Science.gov (United States)

Ducellier, G; Moussy, P; Sahmoune, L; Bonneau, S; Alanio, E; Bory, J-P

2016-09-01

Prenatal diagnosis of complex laparoschisis is difficult and yet it is associated with a significantly increased morbidity and mortality. The aim of the study was to define ultrasonographic factor and obstetrical criteria to predicting adverse neonatal outcome. Retrospective cohort study over 10 years, of 35 gastroschisis cases in CHU of Reims (France). The primary outcome was the neonatal death due to gastroschisis. The sonographic markers was bowel dilatation intra- or extra-abdominale, amniotic fluid, intra-uterin growth. The obstetrical criteria was fetal vitality, fetal heart rate, type of delivery, the weight and the term of birth. There were 28 live births, 16 children with favorable outcome, 8 children with adverse perinatal outcome and 4 deaths. There were any sonographic criteria to predicting adverse neonatal outcome. Only the birth weight less than 2000g was associated with an increase gastrointestinal complications (P=0.049). The type of the delivery was not associated with an adverse prenatal outcome. The birth weight less than 2000g seems to be associate with an increase gastrointestinal complications. It is important to fight against prematurity in case of gastroschisis. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
Beyond the bench and the bedside: economic and health systems dimensions of global childhood cancer outcomes.

Science.gov (United States)

Denburg, Avram E; Knaul, Felicia M; Atun, Rifat; Frazier, Lindsay A; Barr, Ronald D

2014-03-01

Globally, the number of new cases of childhood cancer continues to rise, with a widening gulf in outcomes across countries, despite the availability of effective cure options for many pediatric cancers. Economic forces and health system realities are deeply embedded in the foundation of disparities in global childhood cancer outcomes. A truly global effort to close the childhood cancer divide therefore requires systemic solutions. Analysis of the economic and health system dimensions of childhood cancer outcomes is essential to progress in childhood cancer survival around the globe. The conceptual power of this approach is significant. It provides insight into how and where pediatric oncology entwines with broader political and economic conditions, and highlights the mutual benefit derived from systems-oriented solutions. © 2013 Wiley Periodicals, Inc.
Are Fusion Transcripts in Relapsed/Metastatic Head and Neck Cancer Patients Predictive of Response to Anti-EGFR Therapies?

Directory of Open Access Journals (Sweden)

Paolo Bossi

2017-01-01

Full Text Available Prediction of benefit from combined chemotherapy and the antiepidermal growth factor receptor cetuximab is a not yet solved question in head and neck squamous cell carcinoma (HNSCC. In a selected series of 14 long progression-free survival (PFS and 26 short PFS patients by whole gene and microRNA expression analysis, we developed a model potentially predictive of cetuximab sensitivity. To better decipher the “omics” profile of our patients, we detected transcript fusions by RNA-seq through a Pan-Cancer panel targeting 1385 cancer genes. Twenty-seven different fusion transcripts, involving mRNA and long noncoding RNA (lncRNA, were identified. The majority of fusions (81% were intrachromosomal, and 24 patients (60% harbor at least one of them. The presence/absence of fusions and the presence of more than one fusion were not related to outcome, while the lncRNA-containing fusions resulted enriched in long PFS patients (P=0.0027. The CD274-PDCD1LG2 fusion was present in 7/14 short PFS patients harboring fusions and was absent in long PFS patients (P=0.0188. Among the short PFS patients, those harboring this fusion had the worst outcome (P=0.0172 and increased K-RAS activation (P=0.00147. The associations between HNSCC patient’s outcome following cetuximab treatment and lncRNA-containing fusions or the CD274-PDCD1LG2 fusion deserve validation in prospective clinical trials.
Applications of Machine learning in Prediction of Breast Cancer Incidence and Mortality

International Nuclear Information System (INIS)

Helal, N.; Sarwat, E.

2012-01-01

Breast cancer is one of the leading causes of cancer deaths for the female population in both developed and developing countries. In this work we have used the baseline descriptive data about the incidence (new cancer cases) of in situ breast cancer among Wisconsin females. The documented data were from the most recent 12-years period for which data are available. Wiscons in cancer incidence and mortality (deaths due to cancer) that occurred were also considered in this work. Artificial Neural network (ANN) have been successfully applied to problems in the prediction of the number of new cancer cases and mortality. Using artificial intelligence (AI) in this study, the numbers of new cancer cases and mortality that may occur are predicted.
Predictive value of the official cancer alarm symptoms in general practice

DEFF Research Database (Denmark)

Krasnik Huggenberger, Ivan; Andersen, John Sahl

2015-01-01

Introduction: The objective of this study was to investigate the evidence for positive predictive value (PPV) of alarm symptoms and combinations of symptoms for colorectal cancer, breast cancer, prostate cancer and lung cancer in general practice. Methods: This study is based on a literature search...
Impact of Immigration Status on Cancer Outcomes in Ontario, Canada.

Science.gov (United States)

Cheung, Matthew C; Earle, Craig C; Fischer, Hadas D; Camacho, Ximena; Liu, Ning; Saskin, Refik; Shah, Baiju R; Austin, Peter C; Singh, Simron

2017-07-01

Prior studies have documented inferior health outcomes in vulnerable populations, including racial minorities and those with disadvantaged socioeconomic status. The impact of immigration on cancer-related outcomes is less clear. Administrative databases were linked to create a cohort of incident cancer cases (colorectal, lung, prostate, head and neck, breast, and hematologic malignancies) from 2000 to 2012 in Ontario, Canada. Cancer patients who immigrated to Canada (from 1985 onward) were compared with those who were Canadian born (or immigrated before 1985). Patients were followed from diagnosis until death (cancer-specific or all-cause). Cox proportional hazards models were estimated to determine the impact of immigration on mortality after adjusting for explanatory variables. Additional adjusted models studied the relationship of time since immigration and cancer-specific and overall mortality. From 2000 to 2012, 11,485 cancer cases were diagnosed in recent immigrants (0 to 10 years in Canada), 17,844 cases in nonrecent immigrants (11 to 25 years), and 416,118 cases in nonimmigrants. After adjustment, the hazard of mortality was lower for recent immigrants (hazard ratio [HR], 0.843; 95% CI, 0.814 to 0.873) and nonrecent immigrants (HR, 0.902; 95% CI, 0.876 to 0.928) compared with nonimmigrants. Cancer-specific mortality was also lower for recent immigrants (HR, 0.857; 95% CI, 0.823 to 0.893) and nonrecent immigrants (HR, 0.907; 95% CI, 0.875 to 0.94). Among immigrants, each year from the original landing was associated with increased mortality (HR, 1.004; 95% CI, 1.000 to 1.009) and a trend to increased cancer-specific mortality (HR, 1.005; 95% CI, 0.999 to 1.010). Immigrants demonstrate a healthy immigrant effect, with lower cancer-specific mortality compared with Canadian-born individuals. This benefit seems to diminish over time, as the survival of immigrants from common cancers potentially converges with the Canadian norm.
An algorithm to discover gene signatures with predictive potential

Directory of Open Access Journals (Sweden)

Hallett Robin M

2010-09-01

Full Text Available Abstract Background The advent of global gene expression profiling has generated unprecedented insight into our molecular understanding of cancer, including breast cancer. For example, human breast cancer patients display significant diversity in terms of their survival, recurrence, metastasis as well as response to treatment. These patient outcomes can be predicted by the transcriptional programs of their individual breast tumors. Predictive gene signatures allow us to correctly classify human breast tumors into various risk groups as well as to more accurately target therapy to ensure more durable cancer treatment. Results Here we present a novel algorithm to generate gene signatures with predictive potential. The method first classifies the expression intensity for each gene as determined by global gene expression profiling as low, average or high. The matrix containing the classified data for each gene is then used to score the expression of each gene based its individual ability to predict the patient characteristic of interest. Finally, all examined genes are ranked based on their predictive ability and the most highly ranked genes are included in the master gene signature, which is then ready for use as a predictor. This method was used to accurately predict the survival outcomes in a cohort of human breast cancer patients. Conclusions We confirmed the capacity of our algorithm to generate gene signatures with bona fide predictive ability. The simplicity of our algorithm will enable biological researchers to quickly generate valuable gene signatures without specialized software or extensive bioinformatics training.
The role of p53 in radiation therapy outcomes for favorable-to-intermediate-risk prostate cancer

International Nuclear Information System (INIS)

Ritter, Mark A.; Gilchrist, Kennedy W.; Voytovich, Marta; Chappell, Richard J.; Verhoven, Bret M.

2002-01-01

Purpose: Some prostate cancers may have molecular alterations that render them less responsive to radiation therapy; identification of these alterations before treatment might allow improved treatment optimization. This study investigated whether p53, a potential molecular determinant, could predict long-term radiation therapy outcome in a restricted group of relatively favorable-risk prostate cancer patients treated uniformly with irradiation alone. Methods and Materials: This study included 53 patients previously treated with radiotherapy for favorable-to-intermediate-risk prostate cancer. These patients were selected for relatively low pretreatment PSAs (≤21 ng/mL) and Gleason scores (≤7) to decrease the likelihood of nonlocalized disease, because disease localization was necessary to examine the efficacy of localized radiation therapy. The status of p53 was immunohistochemically assessed in paraffin-embedded pretreatment biopsy specimens, along with appropriate controls. This marker was selected based upon a usable mutation prevalence in early-stage prostate cancer and its potential linkage with radiation response via cell cycle, DNA repair, and cell death pathways. Correlation between p53 mutation and clinical outcome was analyzed in univariate and multivariate fashion and included conventional prognosticators, such as stage, grade, and PSA. Freedom from biochemical failure was determined using American Society for Therapeutic Radiology and Oncology criteria. Limitations of prior studies were potentially avoided by requiring adequate posttreatment follow-up (median follow-up in nonfailing patients of 5.1 years), as well as pretreatment PSA and Gleason scores that suggested localized disease, and uniformity of treatment. Results: The total group of 53 favorable-to-intermediate-risk patients demonstrated an actuarial biochemical failure rate of 35% at 5 years. Forty percent of all specimens had a greater than 10% labeling index for p53 mutation, and
Patient experiences and outcomes following facial skin cancer surgery: A qualitative study.

Science.gov (United States)

Lee, Erica H; Klassen, Anne F; Lawson, Jessica L; Cano, Stefan J; Scott, Amie M; Pusic, Andrea L

2016-08-01

Early melanoma and non-melanoma skin cancer of the facial area are primarily treated with surgery. Little is known about the outcomes of treatment for facial skin cancer patients. The objective of the study was to identify concerns about aesthetics, procedures and health from the patients' perspective after facial skin surgery. Semi-structured in-depth interviews were conducted with 15 participants. Line-by-line coding was used to establish categories and develop themes. We identified five major themes on the impact of skin cancer surgery: appearance-related concerns; psychological (e.g., fear of new cancers or recurrence); social (e.g. impact on social activities and interaction); physical (e.g. pain and swelling) concerns and satisfaction with the experience of care (e.g., satisfaction with surgeon). The priority of participants was the removal of the facial skin cancer, as this reduced their overall worry. The aesthetic outcome was secondary but important, as it had important implications on the participants' social and psychological functioning. The participants' experience with the care provided by the surgeon and staff also contributed to their satisfaction with their treatment. This conceptual framework provides the basis for the development of a new patient-reported outcome instrument. © 2015 The Australasian College of Dermatologists.
Outcome of cervix uteri cancer patients: Clinical treatment results and toxicity profile in a retrospective study from Saudi Arabia.

Science.gov (United States)

El Sayed, Mohamed E; Bahadur, Yasir A; Hassouna, Ashraf H; Fawzy, Ehab E; Nasr, Azza M; Sadiq, Bakr B; Dada, Reyad; Sait, Khalid H; Anfinan, Nisrin M

2017-10-01

This study evaluated the survival outcome, pattern of failure and prognostic factors in cervix uteri cancer patients. We reviewed the data of 60 patients with stages IB-IVA cancer who were treated between January 2004 and December 2010. Most patients (n = 50; 83%) had squamous cell carcinoma. Stage IIB was the most common presentation (n = 41; 68%). Forty-seven patients (78%) received Cisplatin concurrent with radiotherapy (CRT). The 2- and 4-year overall survival (OS) was 82% and 79%, respectively. Prolongation of the overall treatment time (OAT) for greater than 56 days, advanced stage and pretreatment hemoglobin (Hb) levels (cervix uteri cancer patients and the prognostic factors are comparable to those of previous reports. Orthogonal brachytherapy planning and vaginal infiltration negatively predicted relapse. © 2016 John Wiley & Sons Australia, Ltd.
The predictive accuracy of PREDICT: a personalized decision-making tool for Southeast Asian women with breast cancer.

Science.gov (United States)

Wong, Hoong-Seam; Subramaniam, Shridevi; Alias, Zarifah; Taib, Nur Aishah; Ho, Gwo-Fuang; Ng, Char-Hong; Yip, Cheng-Har; Verkooijen, Helena M; Hartman, Mikael; Bhoo-Pathy, Nirmala

2015-02-01

Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480 patients who underwent complete surgical treatment for stages I to III breast cancer from 1998 to 2006 were identified from the prospective breast cancer registry of University Malaya Medical Centre, Kuala Lumpur, Malaysia. Calibration was evaluated by comparing the model-predicted overall survival (OS) with patients' actual OS. Model discrimination was tested using receiver-operating characteristic (ROC) analysis. Median age at diagnosis was 50 years. The median tumor size at presentation was 3 cm and 54% of patients had lymph node-negative disease. About 55% of women had estrogen receptor-positive breast cancer. Overall, the model-predicted 5 and 10-year OS was 86.3% and 77.5%, respectively, whereas the observed 5 and 10-year OS was 87.6% (difference: -1.3%) and 74.2% (difference: 3.3%), respectively; P values for goodness-of-fit test were 0.18 and 0.12, respectively. The program was accurate in most subgroups of patients, but significantly overestimated survival in patients aged discrimination; areas under ROC curve were 0.78 (95% confidence interval [CI]: 0.74-0.81) and 0.73 (95% CI: 0.68-0.78) for 5 and 10-year OS, respectively. Based on its accurate performance in this study, PREDICT may be clinically useful in prognosticating women with breast cancer and personalizing breast cancer treatment in resource-limited settings.
Utilisation and outcomes of cervical cancer prevention services ...

African Journals Online (AJOL)

The proportion of women undergoing cervical cancer screening after HIV diagnosis at primary health clinics, demographic characteristics of women referred for colposcopy at a tertiary centre, and outcomes of therapy for precancerous lesions of the cervix. Results. The proportion of women undergoing at least one Pap ...
Predicting the Outcome of NBA Playoffs Based on the Maximum Entropy Principle

OpenAIRE

Ge Cheng; Zhenyu Zhang; Moses Ntanda Kyebambe; Nasser Kimbugwe

2016-01-01

Predicting the outcome of National Basketball Association (NBA) matches poses a challenging problem of interest to the research community as well as the general public. In this article, we formalize the problem of predicting NBA game results as a classification problem and apply the principle of Maximum Entropy to construct an NBA Maximum Entropy (NBAME) model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs using the model. Our results reveal that...
Clinicopathologic Characteristics and Treatment Outcomes of Penile Cancer

Science.gov (United States)

Nam, Jong Kil; Lee, Dong Hoon; Park, Sung Woo; Kam, Sung Chul; Lee, Ki Soo; Kim, Tae Hyo; Kim, Taek Sang; Oh, Cheol Kyu; Park, Hyun Jun

2017-01-01

Purpose The aim of this study was to assess the clinicopathologic characteristics of penile cancer, including patterns of therapy, oncologic results, and survival. Materials and Methods Between January 2005 and July 2015, 71 patients at 6 institutions who had undergone penectomy or penile biopsy were enrolled. Their medical records were reviewed to identify the mode of therapy, pathology reports, and cancer-specific survival (CSS) rate. Results Clinicopathologic and outcome information was available for 52 male patients (mean age, 64.3 years; mean follow-up, 61.4 months). At presentation, 17 patients were node-positive, and 4 had metastatic disease. Management was partial penectomy in 34 patients, total penectomy in 12 patients, and chemotherapy or radiotherapy in 6 patients. The pathology reports were squamous cell carcinoma in 50 patients and other types of carcinoma in the remaining 2 patients. Kaplan-Meier survival analysis showed a 5-year CSS rate of 84.0%. In univariate and multivariate analyses, the American Joint Committee on Cancer (AJCC) stage and pathologic grade were associated with survival. Conclusions Partial penectomy was the most common treatment of penile lesions. The oncologic outcomes were good, with a 5-year CSS of 84.0%. The AJCC stage and pathologic grade were independent prognostic factors for survival. PMID:28459145
Outcomes of cancer surgery after inhalational and intravenous anesthesia

DEFF Research Database (Denmark)

Soltanizadeh, Sinor; Degett, Thea H; Gögenur, Ismail

2017-01-01

Perioperative factors are probably essential for different oncological outcomes. This systematic review investigates the literature concerning overall mortality and postoperative complications after cancer surgery with inhalational (INHA) and intravenous anesthesia (TIVA). A search was conducted...
Comparing 2 Whiplash Grading Systems to Predict Clinical Outcomes.

Science.gov (United States)

Croft, Arthur C; Bagherian, Alireza; Mickelsen, Patrick K; Wagner, Stephen

2016-06-01

Two whiplash severity grading systems have been developed: Quebec Task Force on Whiplash-Associated Disorders (QTF-WAD) and the Croft grading system. The majority of clinical studies to date have used the modified grading system published by the QTF-WAD in 1995 and have demonstrated some ability to predict outcome. But most studies include only injuries of lower severity (grades 1 and 2), preventing a broader interpretation. The purpose of this study was assess the ability of these grading systems to predict clinical outcome within the context of a broader injury spectrum. This study evaluated both grading systems for their ability to predict the bivalent outcome, recovery, within a sample of 118 whiplash patients who were part of a previous case-control designed study. Of these, 36% (controls) had recovered, and 64% (cases) had not recovered. The discrete bivariate distribution between recovery status and whiplash grade was analyzed using the 2-tailed cross-tabulation statistics. Applying the criteria of the original 1993 Croft grading system, the subset comprised 1 grade 1 injury, 32 grade 2 injuries, 53 grade 3 injuries, and 32 grade 4 injuries. Applying the criteria of the modified (QTF-WAD) grading system, there were 1 grade 1 injury, 89 grade 2 injuries, and 28 grade 3 injuries. Both whiplash grading systems correlated negatively with recovery; that is, higher severity grades predicted a lower probability of recovery, and statistically significant correlations were observed in both, but the Croft grading system substantially outperformed the QTF-WAD system on this measure. The Croft grading system for whiplash injury severity showed a better predictive measure for recovery status from whiplash injuries as compared with the QTF-WAD grading system.
Development and Validation of a Prediction Model to Estimate Individual Risk of Pancreatic Cancer.

Science.gov (United States)

Yu, Ami; Woo, Sang Myung; Joo, Jungnam; Yang, Hye-Ryung; Lee, Woo Jin; Park, Sang-Jae; Nam, Byung-Ho

2016-01-01

There is no reliable screening tool to identify people with high risk of developing pancreatic cancer even though pancreatic cancer represents the fifth-leading cause of cancer-related death in Korea. The goal of this study was to develop an individualized risk prediction model that can be used to screen for asymptomatic pancreatic cancer in Korean men and women. Gender-specific risk prediction models for pancreatic cancer were developed using the Cox proportional hazards model based on an 8-year follow-up of a cohort study of 1,289,933 men and 557,701 women in Korea who had biennial examinations in 1996-1997. The performance of the models was evaluated with respect to their discrimination and calibration ability based on the C-statistic and Hosmer-Lemeshow type χ2 statistic. A total of 1,634 (0.13%) men and 561 (0.10%) women were newly diagnosed with pancreatic cancer. Age, height, BMI, fasting glucose, urine glucose, smoking, and age at smoking initiation were included in the risk prediction model for men. Height, BMI, fasting glucose, urine glucose, smoking, and drinking habit were included in the risk prediction model for women. Smoking was the most significant risk factor for developing pancreatic cancer in both men and women. The risk prediction model exhibited good discrimination and calibration ability, and in external validation it had excellent prediction ability. Gender-specific risk prediction models for pancreatic cancer were developed and validated for the first time. The prediction models will be a useful tool for detecting high-risk individuals who may benefit from increased surveillance for pancreatic cancer.

Comparison of TMS and DTT for predicting motor outcome in intracerebral hemorrhage.

Science.gov (United States)

Jang, Sung Ho; Ahn, Sang Ho; Sakong, Joon; Byun, Woo Mok; Choi, Byung Yun; Chang, Chul Hoon; Bai, Daiseg; Son, Su Min

2010-03-15

TMS (transcranial magnetic stimulation) and DTT (diffusion tensor tractography) have different advantages in evaluating stroke patients. TMS has good clinical accessibility and economical benefit. On the contrary, DTT has a unique advantage to visualize neural tracts three-dimensionally although it requires an expensive and large MRI machine. Many studies have demonstrated that TMS and DTT have predictive values for motor outcome in stroke patients. However, there has been no study on the comparison of these two evaluation tools. In the current study, we compared the abilities of TMS and DTT to predict upper motor outcome in patients with ICH (intracerebral hemorrhage). Fifty-three consecutive patients with severe motor weakness were evaluated by TMS and DTT at the early stage (7-28 days) of ICH. Modified Brunnstrom classification (MBC) and the motricity index of upper extremity (UMI) were evaluated at onset and 6 months after onset. Patients with the presence of a motor evoked potential (MEP) in TMS or a preserved corticospinal tract (CST) in DTT showed better motor outcomes than those without (p=0.000). TMS showed higher positive predictive value than DTT. In contrast, DTT showed higher negative predictive value than TMS. TMS and DTT had different advantages in predicting motor outcome, and this result could be a reference to predict final neurological deficit at the early stage of ICH.
Looking for students'personal characteristics predicting study outcome

NARCIS (Netherlands)

Bergen, T.C.M.; Bragt, van C.A.C.; Bakx, A.W.E.A.; Croon, M.A.

2011-01-01

Abstract The central goal of this study is to clarify to what degree former education and students’ personal characteristics (the ‘Big Five personality characteristics’, personal orientations on learning and students’ study approach) may predict study outcome (required credits and study
Looking for students' personal characteristics predicting study outcome.

NARCIS (Netherlands)

Dr. A. Bakx; Theo Bergen; Dr. Cyrille A.C. Van Bragt; Marcel Croon

2011-01-01

Abstract The central goal of this study is to clarify to what degree former education and students' personal characteristics (the 'Big Five personality characteristics', personal orientations on learning and students' study approach) may predict study outcome (required credits and study
Extensions of the Rosner-Colditz breast cancer prediction model to include older women and type-specific predicted risk.

Science.gov (United States)

Glynn, Robert J; Colditz, Graham A; Tamimi, Rulla M; Chen, Wendy Y; Hankinson, Susan E; Willett, Walter W; Rosner, Bernard

2017-08-01

A breast cancer risk prediction rule previously developed by Rosner and Colditz has reasonable predictive ability. We developed a re-fitted version of this model, based on more than twice as many cases now including women up to age 85, and further extended it to a model that distinguished risk factor prediction of tumors with different estrogen/progesterone receptor status. We compared the calibration and discriminatory ability of the original, the re-fitted, and the type-specific models. Evaluation used data from the Nurses' Health Study during the period 1980-2008, when 4384 incident invasive breast cancers occurred over 1.5 million person-years. Model development used two-thirds of study subjects and validation used one-third. Predicted risks in the validation sample from the original and re-fitted models were highly correlated (ρ = 0.93), but several parameters, notably those related to use of menopausal hormone therapy and age, had different estimates. The re-fitted model was well-calibrated and had an overall C-statistic of 0.65. The extended, type-specific model identified several risk factors with varying associations with occurrence of tumors of different receptor status. However, this extended model relative to the prediction of any breast cancer did not meaningfully reclassify women who developed breast cancer to higher risk categories, nor women remaining cancer free to lower risk categories. The re-fitted Rosner-Colditz model has applicability to risk prediction in women up to age 85, and its discrimination is not improved by consideration of varying associations across tumor subtypes.
Expression changes in the stroma of prostate cancer predict subsequent relapse.

Directory of Open Access Journals (Sweden)

Zhenyu Jia

Full Text Available Biomarkers are needed to address overtreatment that occurs for the majority of prostate cancer patients that would not die of the disease but receive radical treatment. A possible barrier to biomarker discovery may be the polyclonal/multifocal nature of prostate tumors as well as cell-type heterogeneity between patient samples. Tumor-adjacent stroma (tumor microenvironment is less affected by genetic alteration and might therefore yield more consistent biomarkers in response to tumor aggressiveness. To this end we compared Affymetrix gene expression profiles in stroma near tumor and identified a set of 115 probe sets for which the expression levels were significantly correlated with time-to-relapse. We also compared patients that chemically relapsed shortly after prostatectomy (<1 year, and patients that did not relapse in the first four years after prostatectomy. We identified 131 differentially expressed microarray probe sets between these two categories. 19 probe sets (15 genes overlapped between the two gene lists with p<0.0001. We developed a PAM-based classifier by training on samples containing stroma near tumor: 9 rapid relapse patient samples and 9 indolent patient samples. We then tested the classifier on 47 different samples, containing 90% or more stroma. The classifier predicted the risk status of patients with an average accuracy of 87%. This is the first general tumor microenvironment-based prognostic classifier. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for predicting outcomes for patients.
Quantifying predictive capability of electronic health records for the most harmful breast cancer

Science.gov (United States)

Wu, Yirong; Fan, Jun; Peissig, Peggy; Berg, Richard; Tafti, Ahmad Pahlavan; Yin, Jie; Yuan, Ming; Page, David; Cox, Jennifer; Burnside, Elizabeth S.

2018-03-01

Improved prediction of the "most harmful" breast cancers that cause the most substantive morbidity and mortality would enable physicians to target more intense screening and preventive measures at those women who have the highest risk; however, such prediction models for the "most harmful" breast cancers have rarely been developed. Electronic health records (EHRs) represent an underused data source that has great research and clinical potential. Our goal was to quantify the value of EHR variables in the "most harmful" breast cancer risk prediction. We identified 794 subjects who had breast cancer with primary non-benign tumors with their earliest diagnosis on or after 1/1/2004 from an existing personalized medicine data repository, including 395 "most harmful" breast cancer cases and 399 "least harmful" breast cancer cases. For these subjects, we collected EHR data comprised of 6 components: demographics, diagnoses, symptoms, procedures, medications, and laboratory results. We developed two regularized prediction models, Ridge Logistic Regression (Ridge-LR) and Lasso Logistic Regression (Lasso-LR), to predict the "most harmful" breast cancer one year in advance. The area under the ROC curve (AUC) was used to assess model performance. We observed that the AUCs of Ridge-LR and Lasso-LR models were 0.818 and 0.839 respectively. For both the Ridge-LR and LassoLR models, the predictive performance of the whole EHR variables was significantly higher than that of each individual component (pbreast cancer, providing the possibility to personalize care for those women at the highest risk in clinical practice.
Radiological characteristics, histological features and clinical outcomes of lung cancer patients with coexistent idiopathic pulmonary fibrosis.

Science.gov (United States)

Khan, K A; Kennedy, M P; Moore, E; Crush, L; Prendeville, S; Maher, M M; Burke, L; Henry, M T

2015-02-01

Despite advances in diagnosis and management, the outcomes for both lung cancer and idiopathic pulmonary fibrosis (IPF) are still unfavourable. The pathophysiology and outcomes for patients with concomitant lung cancer and IPF remains unclear. A retrospective analysis was performed of all patients presenting with concomitant IPF and lung cancer to our centre over a 3-year period. Patients with connective tissue disease, asbestos exposure, sarcoidosis, previous thoracic radiation, radiological evidence of fibrosis but no histological confirmation of lung cancer, or the use of medications known to cause pulmonary fibrosis were excluded. We describe clinical, radiological and pathological characteristics of this group. We also report the response to standardized lung cancer therapy in this cohort. Of 637 lung cancer patients, 34 were identified with concomitant IPF (5.3 %) and all were smokers. 85 % had non-small cell lung cancer, 41 % were squamous cell cancers. The majority of tumours were located in the lower lobes, peripheral and present in an area of honeycombing. Despite the fact that approximately 2/3rds of the patients had localised or locally advanced lung cancer, the outcome of therapy for lung cancer was extremely poor regardless of tumour stage or severity of IPF. At our centre, 1/20 patients with lung cancer have concomitant IPF. The majority of these tumours are small in size, peripheral in location and squamous cell carcinoma; in an area of honey combing. The outcome for concomitant lung cancer and IPF regardless of stage or therapy is poor.
The expression level of HJURP has an independent prognostic impact and predicts the sensitivity to radiotherapy in breast cancer

International Nuclear Information System (INIS)

Hu, Zhi; Huang, Ge; Sadanandam, Anguraj; Gu, Shenda; Lenburg, Marc E.; Pai, Melody; Bayani, Nora; Blakely, Eleanor A.; Gray, Joe W.; Mao, Jian-Hua

2010-01-01

HJURP (Holliday Junction Recognition Protein) is a newly discovered gene reported to function at centromeres and to interact with CENPA. However its role in tumor development remains largely unknown. The goal of this study was to investigate the clinical significance of HJURP in breast cancer and its correlation with radiotherapeutic outcome. We measured HJURP expression level in human breast cancer cell lines and primary breast cancers by Western blot and/or by Affymetrix Microarray; and determined its associations with clinical variables using standard statistical methods. Validation was performed with the use of published microarray data. We assessed cell growth and apoptosis of breast cancer cells after radiation using high-content image analysis. HJURP was expressed at higher level in breast cancer than in normal breast tissue. HJURP mRNA levels were significantly associated with estrogen receptor (ER), progesterone receptor (PR), Scarff-Bloom-Richardson (SBR) grade, age and Ki67 proliferation indices, but not with pathologic stage, ERBB2, tumor size, or lymph node status. Higher HJURP mRNA levels significantly decreased disease-free and overall survival. HJURP mRNA levels predicted the prognosis better than Ki67 proliferation indices. In a multivariate Cox proportional-hazard regression, including clinical variables as covariates, HJURP mRNA levels remained an independent prognostic factor for disease-free and overall survival. In addition HJURP mRNA levels were an independent prognostic factor over molecular subtypes (normal like, luminal, Erbb2 and basal). Poor clinical outcomes among patients with high HJURP expression were validated in five additional breast cancer cohorts. Furthermore, the patients with high HJURP levels were much more sensitive to radiotherapy. In vitro studies in breast cancer cell lines showed that cells with high HJURP levels were more sensitive to radiation treatment and had a higher rate of apoptosis than those with low levels
The expression level of HJURP has an independent prognostic impact and predicts the sensitivity to radiotherapy in breast cancer

Energy Technology Data Exchange (ETDEWEB)

Hu, Zhi; Huang, Ge; Sadanandam, Anguraj; Gu, Shenda; Lenburg, Marc E; Pai, Melody; Bayani, Nora; Blakely, Eleanor A; Gray, Joe W; Mao, Jian-Hua

2010-06-25

Introduction: HJURP (Holliday Junction Recognition Protein) is a newly discovered gene reported to function at centromeres and to interact with CENPA. However its role in tumor development remains largely unknown. The goal of this study was to investigate the clinical significance of HJURP in breast cancer and its correlation with radiotherapeutic outcome. Methods: We measured HJURP expression level in human breast cancer cell lines and primary breast cancers by Western blot and/or by Affymetrix Microarray; and determined its associations with clinical variables using standard statistical methods. Validation was performed with the use of published microarray data. We assessed cell growth and apoptosis of breast cancer cells after radiation using high-content image analysis. Results: HJURP was expressed at higher level in breast cancer than in normal breast tissue. HJURP mRNA levels were significantly associated with estrogen receptor (ER), progesterone receptor (PR), Scarff-Bloom-Richardson (SBR) grade, age and Ki67 proliferation indices, but not with pathologic stage, ERBB2, tumor size, or lymph node status. Higher HJURP mRNA levels significantly decreased disease-free and overall survival. HJURP mRNA levels predicted the prognosis better than Ki67 proliferation indices. In a multivariate Cox proportional-hazard regression, including clinical variables as covariates, HJURP mRNA levels remained an independent prognostic factor for disease-free and overall survival. In addition HJURP mRNA levels were an independent prognostic factor over molecular subtypes (normal like, luminal, Erbb2 and basal). Poor clinical outcomes among patients with high HJURP expression werevalidated in five additional breast cancer cohorts. Furthermore, the patients with high HJURP levels were much more sensitive to radiotherapy. In vitro studies in breast cancer cell lines showed that cells with high HJURP levels were more sensitive to radiation treatment and had a higher rate of apoptosis
The relation of CT-determined tumor parameters and local and regional outcome of tonsillar cancer after definitive radiation treatment

International Nuclear Information System (INIS)

Hermans, Robert; Op de beeck, Katya; Bogaert, Walter van den; Rijnders, Alexis; Staelens, Lorenzo; Feron, Michel; Bellon, Erwin

2001-01-01

Purpose: To investigate the value of CT-derived tumor parameters as predictor of local and regional outcome of tonsillar squamous cell carcinoma treated by definitive radiation therapy. Methods and Materials: The pretreatment CT studies of 112 patients with tonsillar squamous cell carcinoma were reviewed. After redigitizing the films, primary and nodal tumor volume was calculated with the summation-of-areas technique. The nodal CT aspect was graded using a 3-point scale (homogenous, inhomogeneous, and necrotic). Mean follow-up time was 33 months. Actuarial statistical analysis of local and regional outcome was done for each of the covariates; multivariate analysis was performed using Cox's proportional hazards model. Results: In the actuarial analysis, CT-determined primary tumor volume was significantly correlated with local recurrence rate (p<0.05) when all patients were considered, but primary tumor volume did not predict local control within the T2, T3, and T4 category. CT-determined nodal volume was significantly related to regional outcome (p<0.01), but nodal density was not. Total tumor volume was not significantly related to locoregional outcome (p=0.1). In the multivariate analysis, the T and N categories were the independent predictors of local and regional outcomes, respectively. Conclusion: Compared to other head-and-neck sites, primary and nodal tumor volume have only marginal predictive value regarding local and regional outcome after radiation therapy in tonsillar cancer
Predictive value of cognition for different domains of outcome in recent-onset schizophrenia.

Science.gov (United States)

Holthausen, Esther A E; Wiersma, Durk; Cahn, Wiepke; Kahn, René S; Dingemans, Peter M; Schene, Aart H; van den Bosch, Robert J

2007-01-15

The aim of this study was to see whether and how cognition predicts outcome in recent-onset schizophrenia in a large range of domains such as course of illness, self-care, interpersonal functioning, vocational functioning and need for care. At inclusion, 115 recent-onset patients were tested on a cognitive battery and 103 patients participated in the follow-up 2 years after inclusion. Differences in outcome between cognitively normal and cognitively impaired patients were also analysed. Cognitive measures at inclusion did not predict number of relapses, activities of daily living and interpersonal functioning. Time in psychosis or in full remission, as well as need for care, were partly predicted by specific cognitive measures. Although statistically significant, the predictive value of cognition with regard to clinical outcome was limited. There was a significant difference between patients with and without cognitive deficits in competitive employment status and vocational functioning. The predictive value of cognition for different social outcome domains varies. It seems that cognition most strongly predicts work performance, where having a cognitive deficit, regardless of the nature of the deficit, acts as a rate-limiting factor.
Sarcopenia predicts 1-year mortality in elderly patients undergoing curative gastrectomy for gastric cancer: a prospective study.

Science.gov (United States)

Huang, Dong-Dong; Chen, Xiao-Xi; Chen, Xi-Yi; Wang, Su-Lin; Shen, Xian; Chen, Xiao-Lei; Yu, Zhen; Zhuang, Cheng-Le

2016-11-01

One-year mortality is vital for elderly oncologic patients undergoing surgery. Recent studies have demonstrated that sarcopenia can predict outcomes after major abdominal surgeries, but the association of sarcopenia and 1-year mortality has never been investigated in a prospective study. We conducted a prospective study of elderly patients (≥65 years) who underwent curative gastrectomy for gastric cancer from July 2014 to July 2015. Sarcopenia was determined by the measurements of muscle mass, handgrip strength, and gait speed. Univariate and multivariate analyses were used to identify the risk factors associated with 1-year mortality. A total of 173 patients were included, in which 52 (30.1 %) patients were identified as having sarcopenia. Twenty-four (13.9 %) patients died within 1 year of surgery. Multivariate analysis showed that sarcopenia was an independent risk factor for 1-year mortality. Area under the receiver operating characteristic curve demonstrated an increased predictive power for 1-year mortality with the inclusion of sarcopenia, from 0.835 to 0.868. Solely low muscle mass was not predictive of 1-year mortality in the multivariate analysis. Sarcopenia is predictive of 1-year mortality in elderly patients undergoing gastric cancer surgery. The measurement of muscle function is important for sarcopenia as a preoperative assessment tool.
Prognostic outcomes in advanced breast cancer: the metastasis-free interval is important.

Science.gov (United States)

Shen, Tiansheng; Gao, Cheng; Zhang, Kui; Siegal, Gene P; Wei, Shi

2017-12-01

Metastatic breast cancer is a heterogeneous disease with a diverse clinical course. There have been limited studies regarding prognostic outcomes in patients with de novo metastatic breast cancer versus those with metastatic recurrence, with controversial observations. In this study, we sought to examine the difference in survival outcomes among patients with advanced breast cancer stratified based on metastasis-free interval (MFI) and to further explore the role of systemic therapy in these patient groups. Of 569 consecutive patients with stage IV breast cancer between 1998 and 2013, 201 had de novo metastatic disease (metastasis at diagnosis) and 368 developed metastatic recurrence, including 168 with an MFI≤24 months and 200 with an MFI>24 months. In the 492 patients who received systemic therapy, de novo metastasis was an independent favorable prognostic factor for overall survival after metastasis when compared with metastatic recurrence irrespective of MFI. Compared with the patients with metastatic recurrence with an MFI≤24 months, those with an MFI>24 months had a superior survival outcome, although it did not reach statistical significance by multivariate analysis. In contrast, de novo metastatic breast cancer was associated with a worse prognosis when compared with recurring metastasis in the patients who did not receive systemic treatment. These findings provide more insight into the natural history of advanced breast cancer, thus necessitating further investigation into the molecular mechanism of drug resistance. Copyright © 2017 Elsevier Inc. All rights reserved.
Prognostic and predictive factors in colorectal cancer.

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Bolocan, A; Ion, D; Ciocan, D N; Paduraru, D N

2012-01-01

Colorectal cancer (CRC) is an important public health problem; it is a leading cause of cancer mortality in the industrialized world, second to lung cancer: each year there are nearly one million new cases of CRC diagnosed worldwide and half a million deaths (1). This review aims to summarise the most important currently available markers for CRC that provide prognostic or predictive information. Amongst others, it covers serum markers such as CEA and CA19-9, markers expressed by tumour tissues, such as thymidylate synthase, and also the expression/loss of expression of certain oncogenes and tumour suppressor genes such as K-ras and p53. The prognostic value of genomic instability, angiogenesis and proliferative indices, such as the apoptotic index, are discussed. The advent of new therapies created the pathway for a personalized approach of the patient. This will take into consideration the complex genetic mechanisms involved in tumorigenesis, besides the classical clinical and pathological stagings. The growing number of therapeutic agents and known molecular targets in oncology lead to a compulsory study of the clinical use of biomarkers with role in improving response and survival, as well as in reducing toxicity and establishing economic stability. The potential predictive and prognostic biomarkers which have arisen from the study of the genetic basis of colorectal cancer and their therapeutical significance are discussed. RevistaChirurgia.
Quantifying the Cumulative Impact of Differences in Care on Prostate Cancer Outcomes

National Research Council Canada - National Science Library

Fesinmeyer, Megan

2007-01-01

... of the disparity in prostate cancer outcomes. This work involves first examining how care patterns are correlated throughout all phases of cancer care within racial groups in order to gain a fuller understanding of how racial differences across...
Predicting the Outcome of NBA Playoffs Based on the Maximum Entropy Principle

Directory of Open Access Journals (Sweden)

Ge Cheng

2016-12-01

Full Text Available Predicting the outcome of National Basketball Association (NBA matches poses a challenging problem of interest to the research community as well as the general public. In this article, we formalize the problem of predicting NBA game results as a classification problem and apply the principle of Maximum Entropy to construct an NBA Maximum Entropy (NBAME model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs using the model. Our results reveal that the model is able to predict the winning team with 74.4% accuracy, outperforming other classical machine learning algorithms that could only afford a maximum prediction accuracy of 70.6% in the experiments that we performed.
The mediating roles of cancer-related rumination in the relationship between dispositional hope and psychological outcomes among childhood cancer survivors.

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Yuen, Ada N Y; Ho, Samuel M Y; Chan, Calais K Y

2014-04-01

This study aimed to examine the effects of dispositional hope on psychopathology as well as self-perceived positive change in childhood cancer survivors through the potential mediation of cancer-related ruminations. A cross-sectional design was used, and a group of childhood cancer survivors (N = 89; mean age = 23.2 years; age range = 17.2-31.3 years) were studied. Dispositional hope level was measured by the Hope Scale; positive and negative cancer-related ruminations were assessed by the Chinese Cancer-related Rumination Scale; depression symptoms were measured by Beck Depression Inventory; and anxiety symptoms were measured by Beck Anxiety Inventory. Positive adjustment outcome of posttraumatic growth (PTG) was assessed by the Chinese Post-traumatic Growth Inventory. Multiple regressions were used to analyze the relationship between dispositional hope and the outcome variables of PTG, anxiety and depression and the potential mediators of positive and negative cancer-related rumination. Dispositional hope was positively related to PTG, and the correlation was specifically mediated by positive cancer-related rumination. Dispositional hope also correlated with lower levels of depression and anxiety, specifically mediated by negative cancer-related rumination. The present finding supported hope as a significant positive factor for childhood cancer survivors, which was associated with PTG and better psychological adjustment. The findings may inform development of therapeutic intervention programs aimed at increasing childhood cancer patients' hope levels, which may be correlated with more positive cancer-related thoughts and better adjustment. The present study, which examined survivors diagnosed at young age, may enrich existing studies on the effect of onset age and adjustment outcomes. Copyright © 2013 John Wiley & Sons, Ltd.
Nanotechnology Strategies To Advance Outcomes in Clinical Cancer Care.

Science.gov (United States)

Hartshorn, Christopher M; Bradbury, Michelle S; Lanza, Gregory M; Nel, Andre E; Rao, Jianghong; Wang, Andrew Z; Wiesner, Ulrich B; Yang, Lily; Grodzinski, Piotr

2018-01-23

Ongoing research into the application of nanotechnology for cancer treatment and diagnosis has demonstrated its advantages within contemporary oncology as well as its intrinsic limitations. The National Cancer Institute publishes the Cancer Nanotechnology Plan every 5 years since 2005. The most recent iteration helped codify the ongoing basic and translational efforts of the field and displayed its breadth with several evolving areas. From merely a technological perspective, this field has seen tremendous growth and success. However, an incomplete understanding of human cancer biology persists relative to the application of nanoscale materials within contemporary oncology. As such, this review presents several evolving areas in cancer nanotechnology in order to identify key clinical and biological challenges that need to be addressed to improve patient outcomes. From this clinical perspective, a sampling of the nano-enabled solutions attempting to overcome barriers faced by traditional therapeutics and diagnostics in the clinical setting are discussed. Finally, a strategic outlook of the future is discussed to highlight the need for next-generation cancer nanotechnology tools designed to address critical gaps in clinical cancer care.
Nutritional Care of Gastric Cancer Patients with Clinical Outcomes and Complications: A Review.

Science.gov (United States)

Choi, Wook Jin; Kim, Jeongseon

2016-04-01

The incidence and mortality of gastric cancer have been steadily decreased over the past few decades. However, gastric cancer is still one of the leading causes of cancer deaths across many regions of the world, particularly in Asian countries. In previous studies, nutrition has been considered one of significant risk factors in gastric cancer patients. Especially, malnourished patients are at greater risk of adverse clinical outcomes (e.g., longer hospital stay) and higher incidence of complications (e.g., wound/infectious complications) compared to well-nourished patients. Malnutrition is commonly found in advanced gastric cancer patients due to poor absorption of essential nutrients after surgery. Therefore, nutritional support protocols, such as early oral and enternal feeding, have been proposed in many studies, to improve unfavorable clinical outcomes and to reduce complications due to delayed application of oral nutritional support or parental feeding. Also, the supplied with enternal immune-enriched diet had more benefits in improving clinical outcomes and fewer complications compared to a group supplied with control formula. Using nutritional screening tools, such as nutritional risk index (NRI) and nutritional risk screening (NRS 2002), malnourished patients showed higher incidence of complications and lower survival rates than non-malnourished patients. However, a long-term nutritional intervention, such as nutritional counseling, was not effective in the patients. Therefore, early assessment of nutritional status in patients using a proper nutritional screening tool is suggested to prevent malnutrition and adverse health outcomes. Further studies with numerous ethnic groups may provide stronger scientific evidences in association between nutritional care and recovery from surgery in patients with gastric cancer.
Is the AIMS65 score useful in predicting outcomes in peptic ulcer bleeding?

Science.gov (United States)

Jung, Sung Hoon; Oh, Jung Hwan; Lee, Hye Yeon; Jeong, Joon Won; Go, Se Eun; You, Chan Ran; Jeon, Eun Jung; Choi, Sang Wook

2014-02-21

To evaluate the applicability of AIMS65 scores in predicting outcomes of peptic ulcer bleeding. This was a retrospective study in a single center between January 2006 and December 2011. We enrolled 522 patients with upper gastrointestinal haemorrhage who visited the emergency room. High-risk patients were regarded as those who had re-bleeding within 30 d from the first endoscopy as well as those who died within 30 d of visiting the Emergency room. A total of 149 patients with peptic ulcer bleeding were analysed, and the AIMS65 score was used to retrospectively predict the high-risk patients. A total of 149 patients with peptic ulcer bleeding were analysed. The poor outcome group comprised 28 patients [male: 23 (82.1%) vs female: 5 (10.7%)] while the good outcome group included 121 patients [male: 93 (76.9%) vs female: 28 (23.1%)]. The mean age in each group was not significantly different. The mean serum albumin levels in the poor outcome group were slightly lower than those in the good outcome group (P = 0.072). For the prediction of poor outcome, the AIMS65 score had a sensitivity of 35.5% (95%CI: 27.0-44.8) and a specificity of 82.1% (95%CI: 63.1-93.9) at a score of 0. The AIMS65 score was insufficient for predicting outcomes in peptic ulcer bleeding (area under curve = 0.571; 95%CI: 0.49-0.65). The AIMS65 score may therefore not be suitable for predicting clinical outcomes in peptic ulcer bleeding. Low albumin levels may be a risk factor associated with high mortality in peptic ulcer bleeding.

Prediction of surgical outcome in compressive cervical myelopathy: A novel clinicoradiological prognostic score

Directory of Open Access Journals (Sweden)

Rishi Anil Aggarwal

2016-01-01

Full Text Available Context: Preoperative severity of myelopathy, age, and duration of symptoms have been shown to be highly predictive of the outcome in compressive cervical myelopathy (CCM. The role of radiological parameters is still controversial. Aims: Define the prognostic factors in CCM and formulate a prognostic score to predict the outcome following surgery in CCM. Settings and Design: Retrospective. Materials and Methods: This study included 78 consecutive patients with CCM treated surgically. The modified Japanese Orthopaedic Association (mJOA scale was used to quantify severity of myelopathy at admission and at 12-month follow-up. The outcome was defined as "good" if the patient had mJOA score ≥16 and "poor" if the score was <16. Age, sex, duration of symptoms, comorbidities, intrinsic hand muscle wasting (IHMW, diagnosis, surgical technique, Torg ratio, instability on dynamic radiographs, and magnetic resonance imaging (MRI signal intensity changes were assessed. Statistics: Statistical Package for the Social Sciences (SPSS (version 20.0 was used for statistical analysis. The association was assessed amongst variables using logistic regression analysis. Parameters having a statistically significant correlation with the outcome were included in formulating a prognostic score. Results: Severity of myelopathy, IHMW, age, duration, diabetes, and instability on radiographs were predictive of the outcome with a P value <0.01. Genders, diagnosis, surgical procedure, Torg ratio, and intensity changes on MRI were not significantly related to the outcome. A 8-point scoring system was devised incorporating the significant clinicoradiological parameters, and it was found that nearly all patients (97.82% with a score below 5 had good outcome and all patients (100% with a score above 5 had poor outcome. The outcome is difficult to predict with a score of 5. Conclusions: Clinical parameters are better predictors of the outcome as compared to radiological findings
Supervised deep learning embeddings for the prediction of cervical cancer diagnosis

Directory of Open Access Journals (Sweden)

Kelwin Fernandes

2018-05-01

Full Text Available Cervical cancer remains a significant cause of mortality all around the world, even if it can be prevented and cured by removing affected tissues in early stages. Providing universal and efficient access to cervical screening programs is a challenge that requires identifying vulnerable individuals in the population, among other steps. In this work, we present a computationally automated strategy for predicting the outcome of the patient biopsy, given risk patterns from individual medical records. We propose a machine learning technique that allows a joint and fully supervised optimization of dimensionality reduction and classification models. We also build a model able to highlight relevant properties in the low dimensional space, to ease the classification of patients. We instantiated the proposed approach with deep learning architectures, and achieved accurate prediction results (top area under the curve AUC = 0.6875 which outperform previously developed methods, such as denoising autoencoders. Additionally, we explored some clinical findings from the embedding spaces, and we validated them through the medical literature, making them reliable for physicians and biomedical researchers.
Pneumonectomy for lung cancer: contemporary national early morbidity and mortality outcomes.

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Thomas, Pascal A; Berbis, Julie; Baste, Jean-Marc; Le Pimpec-Barthes, Françoise; Tronc, François; Falcoz, Pierre-Emmanuel; Dahan, Marcel; Loundou, Anderson

2015-01-01

The study objective was to determine contemporary early outcomes associated with pneumonectomy for lung cancer and to identify their predictors using a nationally representative general thoracic surgery database (EPITHOR). After discarding inconsistent files, a group of 4498 patients who underwent elective pneumonectomy for primary lung cancer between 2003 and 2013 was selected. Logistic regression analysis was performed on variables for mortality and major adverse events. Then, a propensity score analysis was adjusted for imbalances in baseline characteristics between patients with or without neoadjuvant treatment. Operative mortality was 7.8%. Surgical, cardiovascular, pulmonary, and infectious complications rates were 14.9%, 14.1%, 11.5%, and 2.7%, respectively. None of these complications were predicted by the performance of a neoadjuvant therapy. Operative mortality analysis, adjusted for the propensity scores, identified age greater than 65 years (odds ratio [OR], 2.1; 95% confidence interval [CI], 1.5-2.9; P < .001), underweight body mass index category (OR, 2.2; 95% CI, 1.2-4.0; P = .009), American Society of Anesthesiologists score of 3 or greater (OR, 2.310; 95% CI, 1.615-3.304; P < .001), right laterality of the procedure (OR, 1.8; 95% CI, 1.1-2.4; P = .011), performance of an extended pneumonectomy (OR, 1.5; 95% CI, 1.1-2.1; P = .018), and absence of systematic lymphadenectomy (OR, 2.9; 95% CI, 1.1-7.8; P = .027) as risk predictors. Induction therapy (OR, 0.63; 95% CI, 0.5-0.9; P = .005) and overweight body mass index category (OR, 0.60; 95% CI, 0.4-0.9; P = .033) were protective factors. Several risk factors for major adverse early outcomes after pneumonectomy for cancer were identified. Overweight patients and those who received induction therapy had paradoxically lower adjusted risks of mortality. Copyright © 2015 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.
Comparative study of oncologic outcomes for laparoscopic vs. open surgery in transverse colon cancer.

Science.gov (United States)

Kim, Woo Ram; Baek, Se Jin; Kim, Chang Woo; Jang, Hyun A; Cho, Min Soo; Bae, Sung Uk; Hur, Hyuk; Min, Byung Soh; Baik, Seung Hyuk; Lee, Kang Young; Kim, Nam Kyu; Sohn, Seung Kuk

2014-01-01

Laparoscopic resection for transverse colon cancer is a technically challenging procedure that has been excluded from various large randomized controlled trials of which the long-term outcomes still need to be verified. The purpose of this study was to evaluate long-term oncologic outcomes for transverse colon cancer patients undergoing laparoscopic colectomy (LAC) or open colectomy (OC). This retrospective review included patients with transverse colon cancer who received a colectomy between January 2006 and December 2010. Short-term and five-year oncologic outcomes were compared between these groups. A total of 131 patients were analyzed in the final study (LAC, 84 patients; OC, 47 patients). There were no significant differences in age, gender, body mass index, tumor location, operative procedure, or blood loss between groups, but the mean operative time in LAC was significantly longer (LAC, 246.8 minutes vs. OC, 213.8 minutes; P = 0.03). Hospital stay was much shorter for LAC than OC (9.1 days vs. 14.5 days, P transverse colon cancer is feasible and safe with comparable short- and long-term outcomes.
Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

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Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

2015-02-01

Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have
Cancer outcomes for Aboriginal and Torres Strait Islander Australians in rural and remote areas.

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Diaz, Abbey; Whop, Lisa J; Valery, Patricia C; Moore, Suzanne P; Cunningham, Joan; Garvey, Gail; Condon, John R

2015-02-01

To examine the association between residential remoteness and stage of cancer at diagnosis, treatment uptake, and survival within the Australian Indigenous population. Systematic review and matched retrospective cohort study. Australia. Systematic review: published papers that included a comparison of cancer stage at diagnosis, treatment uptake, mortality and/or survival for Indigenous people across remoteness categories were identified (n = 181). Fifteen papers (13 studies) were included in the review. Original analyses: new analyses were conducted using data from the Queensland Indigenous Cancer Study (QICS) comparing cancer stage at diagnosis, treatment uptake, and survival for Indigenous cancer patients living in rural/remote areas (n = 627, 66%) and urban areas (n = 329, 34%). Systematic review: Papers were included if there were related to stage of disease at diagnosis, treatment, mortality and survival of cancer. Restrictions were not placed on the outcome measures reported (e.g. standardised mortality ratios versus crude mortality rates). Original analyses: Odds ratios (OR, 95%CI) were used to compare stage of disease and treatment uptake between the two remoteness groups. Treatment uptake (treated/not treated) was analysed using logistic regression analysis. Survival was analysed using Cox proportional hazards regression. The final multivariate models included stage of cancer at diagnosis and area-level socioeconomic status (SEIFA). Existing evidence of variation in cancer outcomes for Indigenous people in remote compared with metropolitan areas is limited. While no previous studies have reported on differences in cancer stage and treatment uptake by remoteness within the Indigenous population, the available evidence suggests Indigenous cancer patients are less likely to survive their cancer the further they live from urban centres. New analysis of QICS data indicates that Indigenous cancer patients in rural/remote Queensland were less likely to be
Predicting Chernobyl childhood thyroid cancers from incoming data

International Nuclear Information System (INIS)

Thomas, P.J.

1997-01-01

Data on childhood thyroid cancers contracted in Belarus, the Ukraine and Russia's Bryansk and Kaluga regions have been analysed under the working hypothesis that the excess cancers have been caused by iodine-131 from Chernobyl fallout. It is postulated that the variation in latency period between different individuals is most likely to conform to either a normal or a normal logarithmic distribution. Optimal values of the mean and geometric mean latency period, together with their associated standard deviations, have been found using Belarus data. Both resulting distributions predict significant incidence of childhood thyroid cancer much earlier than ten years after the accident, a length of time widely understood in the past to be the approximate minimum for the development of a radiation-induced, solid tumour. The two distributions incorporating these optimal values have been tested against independent data from the Ukraine and Russian and each distribution has passed the statistical tests to date. Predictions are given for the annual incidence of childhood thyroid cancer in each country and for the total number of excess cases over all years. Tolerances are assigned to the latter figure. (Author)
Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods.

Science.gov (United States)

Obrzut, Bogdan; Kusy, Maciej; Semczuk, Andrzej; Obrzut, Marzanna; Kluska, Jacek

2017-12-12

Computational intelligence methods, including non-linear classification algorithms, can be used in medical research and practice as a decision making tool. This study aimed to evaluate the usefulness of artificial intelligence models for 5-year overall survival prediction in patients with cervical cancer treated by radical hysterectomy. The data set was collected from 102 patients with cervical cancer FIGO stage IA2-IIB, that underwent primary surgical treatment. Twenty-three demographic, tumor-related parameters and selected perioperative data of each patient were collected. The simulations involved six computational intelligence methods: the probabilistic neural network (PNN), multilayer perceptron network, gene expression programming classifier, support vector machines algorithm, radial basis function neural network and k-Means algorithm. The prediction ability of the models was determined based on the accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve. The results of the computational intelligence methods were compared with the results of linear regression analysis as a reference model. The best results were obtained by the PNN model. This neural network provided very high prediction ability with an accuracy of 0.892 and sensitivity of 0.975. The area under the receiver operating characteristics curve of PNN was also high, 0.818. The outcomes obtained by other classifiers were markedly worse. The PNN model is an effective tool for predicting 5-year overall survival in cervical cancer patients treated with radical hysterectomy.
Adaptive Encoding of Outcome Prediction by Prefrontal Cortex Ensembles Supports Behavioral Flexibility.

Science.gov (United States)

Del Arco, Alberto; Park, Junchol; Wood, Jesse; Kim, Yunbok; Moghaddam, Bita

2017-08-30

The prefrontal cortex (PFC) is thought to play a critical role in behavioral flexibility by monitoring action-outcome contingencies. How PFC ensembles represent shifts in behavior in response to changes in these contingencies remains unclear. We recorded single-unit activity and local field potentials in the dorsomedial PFC (dmPFC) of male rats during a set-shifting task that required them to update their behavior, among competing options, in response to changes in action-outcome contingencies. As behavior was updated, a subset of PFC ensembles encoded the current trial outcome before the outcome was presented. This novel outcome-prediction encoding was absent in a control task, in which actions were rewarded pseudorandomly, indicating that PFC neurons are not merely providing an expectancy signal. In both control and set-shifting tasks, dmPFC neurons displayed postoutcome discrimination activity, indicating that these neurons also monitor whether a behavior is successful in generating rewards. Gamma-power oscillatory activity increased before the outcome in both tasks but did not differentiate between expected outcomes, suggesting that this measure is not related to set-shifting behavior but reflects expectation of an outcome after action execution. These results demonstrate that PFC neurons support flexible rule-based action selection by predicting outcomes that follow a particular action. SIGNIFICANCE STATEMENT Tracking action-outcome contingencies and modifying behavior when those contingencies change is critical to behavioral flexibility. We find that ensembles of dorsomedial prefrontal cortex neurons differentiate between expected outcomes when action-outcome contingencies change. This predictive mode of signaling may be used to promote a new response strategy at the service of behavioral flexibility. Copyright © 2017 the authors 0270-6474/17/378363-11$15.00/0.
Macrophage migration inhibitory factor induces epithelial to mesenchymal transition, enhances tumor aggressiveness and predicts clinical outcome in resected pancreatic ductal adenocarcinoma.

Science.gov (United States)

Funamizu, Naotake; Hu, Chaoxin; Lacy, Curtis; Schetter, Aaron; Zhang, Geng; He, Peijun; Gaedcke, Jochen; Ghadimi, Michael B; Ried, Thomas; Yfantis, Harris G; Lee, Dong H; Subleski, Jeffrey; Chan, Tim; Weiss, Jonathan M; Back, Timothy C; Yanaga, Katsuhiko; Hanna, Nader; Alexander, H Richard; Maitra, Anirban; Hussain, S Perwez

2013-02-15

MIF is a proinflammatory cytokine and is implicated in cancer. A higher MIF level is found in many human cancer and cancer-prone inflammatory diseases, including chronic pancreatitis and pancreatic cancer. We tested the hypothesis that MIF contributes to pancreatic cancer aggressiveness and predicts disease outcome in resected cases. Consistent with our hypothesis we found that an elevated MIF mRNA expression in tumors was significantly associated with poor outcome in resected cases. Multivariate Cox-regression analysis further showed that MIF is independently associated with patients' survival (HR = 2.26, 95% CI = 1.17-4.37, p = 0.015). Mechanistic analyses revealed that MIF overexpression decreased E-cadherin and increased vimentin mRNA and protein levels in pancreatic cancer cell lines, consistent with the features of epithelial-to-mesenchymal transition (EMT). Furthermore, MIF-overexpression significantly increased ZEB1/2 and decreased miR-200b expression, while shRNA-mediated inhibition of MIF increased E-cadherin and miR-200b expression, and reduced the expression of ZEB1/2 in Panc1 cells. Re-expression of miR-200b in MIF overexpressing cells restored the epithelial characteristics, as indicated by an increase in E-cadherin and decrease in ZEB1/2 and vimentin expression. A reduced sensitivity to the chemotherapeutic drug, gemcitabine, occurred in MIF-overexpressing cells. Indicative of an increased malignant potential, MIF over-expressing cells showed significant increase in their invasion ability in vitro, and tumor growth and metastasis in an orthotopic xenograft mouse model. These results support a role of MIF in disease aggressiveness, indicating its potential usefulness as a candidate target for designing improved treatment in pancreatic cancer. Copyright © 2012 UICC.
The Cambridge Prognostic Groups for improved prediction of disease mortality at diagnosis in primary non-metastatic prostate cancer: a validation study.

Science.gov (United States)

Gnanapragasam, V J; Bratt, O; Muir, K; Lee, L S; Huang, H H; Stattin, P; Lophatananon, A

2018-02-28

The purpose of this study is to validate a new five-tiered prognostic classification system to better discriminate cancer-specific mortality in men diagnosed with primary non-metastatic prostate cancer. We applied a recently described five-strata model, the Cambridge Prognostic Groups (CPGs 1-5), in two international cohorts and tested prognostic performance against the current standard three-strata classification of low-, intermediate- or high-risk disease. Diagnostic clinico-pathological data for men obtained from the Prostate Cancer data Base Sweden (PCBaSe) and the Singapore Health Study were used. The main outcome measure was prostate cancer mortality (PCM) stratified by age group and treatment modality. The PCBaSe cohort included 72,337 men, of whom 7162 died of prostate cancer. The CPG model successfully classified men with different risks of PCM with competing risk regression confirming significant intergroup distinction (p study of nearly 75,000 men confirms that the CPG five-tiered prognostic model has superior discrimination compared to the three-tiered model in predicting prostate cancer death across different age and treatment groups. Crucially, it identifies distinct sub-groups of men within the old intermediate-risk and high-risk criteria who have very different prognostic outcomes. We therefore propose adoption of the CPG model as a simple-to-use but more accurate prognostic stratification tool to help guide management for men with newly diagnosed prostate cancer.
Outcomes assessment in cancer: measures, methods, and applications

National Research Council Canada - National Science Library

Lipscomb, Joseph; Snyder, Claire; Gotay, Carolyn C

2005-01-01

... on individuals and populations. The findings and recommendations of the working group's 35 internationally recognized members are reported in Outcomes Assessment in Cancer, lucidly written and accessible to both researchers and policy makers in academia, government, and industry. This volume provides the most penetrating yet practical discussion to date of alte...
Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

Science.gov (United States)

Huang, Cai; Mezencev, Roman; McDonald, John F; Vannberg, Fredrik

2017-01-01

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.
Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

Directory of Open Access Journals (Sweden)

Cai Huang

Full Text Available Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM algorithm combined with a standard recursive feature elimination (RFE approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60. The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.
Predicting radiotherapy outcomes using statistical learning techniques

International Nuclear Information System (INIS)

El Naqa, Issam; Bradley, Jeffrey D; Deasy, Joseph O; Lindsay, Patricia E; Hope, Andrew J

2009-01-01

Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model
Fetal omphalocele ratios predict outcomes in prenatally diagnosed omphalocele.

Science.gov (United States)

Montero, Freddy J; Simpson, Lynn L; Brady, Paula C; Miller, Russell S

2011-09-01

The objective of the study was to evaluate whether ratios considering omphalocele diameter relative to fetal biometric measurements perform better than giant omphalocele designation at predicting inability to achieve neonatal primary surgical closure. Cases of fetal omphalocele that underwent evaluation between May 2003 and July 2010 were identified. Inclusion was restricted to live births with plan for postnatal repair. Omphalocele diameter upon antenatal ultrasound was compared with abdominal circumference, femur length, and head circumference, yielding the respective omphalocele (O)/abdominal circumference (AC), O/femur length (FL), and O/head circumference (HC) ratios. The absolute measurements were used to classify giant lesions. Omphalocele ratios and giant omphalocele designations were evaluated as predictors of inability to achieve primary repair. Among 25 included cases, staged or delayed closure occurred in 52%. With an optimal cutoff of 0.21 or greater, O/HC best predicted the primary outcome (sensitivity, 84.6%; specificity, 58.3%; odds ratio, 7.7). The O/HC of 0.21 or greater outperformed giant designations. The O/HC of 0.21 or greater best predicted staged or delayed omphalocele closure. Giant omphalocele designation, regardless of definition, poorly predicted outcome. Copyright © 2011 Mosby, Inc. All rights reserved.
Cancer prehabilitation: an opportunity to decrease treatment-related morbidity, increase cancer treatment options, and improve physical and psychological health outcomes.

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Silver, Julie K; Baima, Jennifer

2013-08-01

Cancer prehabilitation, a process on the continuum of care that occurs between the time of cancer diagnosis and the beginning of acute treatment, includes physical and psychological assessments that establish a baseline functional level, identifies impairments, and provides targeted interventions that improve a patient's health to reduce the incidence and the severity of current and future impairments. There is a growing body of scientific evidence that supports preparing newly diagnosed cancer patients for and optimizing their health before starting acute treatments. This is the first review of cancer prehabilitation, and the purpose was to describe early studies in the noncancer population and then the historical focus in cancer patients on aerobic conditioning and building strength and stamina through an appropriate exercise regimen. More recent research shows that opportunities exist to use other unimodal or multimodal prehabilitation interventions to decrease morbidity, improve physical and psychological health outcomes, increase the number of potential treatment options, decrease hospital readmissions, and reduce both direct and indirect healthcare costs attributed to cancer. Future research may demonstrate increased compliance with acute cancer treatment protocols and, therefore, improved survival outcomes. New studies suggest that a multimodal approach that incorporates both physical and psychological prehabilitation interventions may be more effective than a unimodal approach that addresses just one or the other. In an impairment-driven cancer rehabilitation model, identifying current and anticipating future impairments are the critical first steps in improving healthcare outcomes and decreasing costs. More research is urgently needed to evaluate the most effective prehabilitation interventions, and combinations thereof, for survivors of all types of cancer.
Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.

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Du, Juan; Yang, Fang; Zhang, Zhiqiang; Hu, Jingze; Xu, Qiang; Hu, Jianping; Zeng, Fanyong; Lu, Guangming; Liu, Xinfeng

2018-05-15

An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.
Integration and comparison of different genomic data for outcome prediction in cancer

OpenAIRE

Gomez Rueda, Hugo; Martínez Ledesma, Emmanuel; Martínez Torteya, Antonio; Palacios Corona, Rebeca; Treviño, Victor

2005-01-01

Background In cancer, large-scale technologies such as next-generation sequencing and microarrays have produced a wide number of genomic features such as DNA copy number alterations (CNA), mRNA expression (EXPR), microRNA expression (MIRNA), and DNA somatic mutations (MUT), among others. Several analyses of a specific type of these genomic data have generated many prognostic biomarkers in cancer. However, it is uncertain which of these data is more powerful and whether the best data-type is c...
Establishment of a 12-gene expression signature to predict colon cancer prognosis

Directory of Open Access Journals (Sweden)

Dalong Sun

2018-06-01

Full Text Available A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA. The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS: Kaplan Meier (KM Log Rank p = 0.0034; overall survival (OS: KM Log Rank p = 0.0336 in GSE17538. For patients with proficient mismatch repair system (pMMR in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS: KM Log Rank p = 0.022. Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003. After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01 and stage II & III (Log Rank p = 0.017 in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041. Among stage II/III pMMR patients

Predicting Community College Outcomes: Does High School CTE Participation Have a Significant Effect?

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Dietrich, Cecile; Lichtenberger, Eric; Kamalludeen, Rosemaliza

2016-01-01

This study explored the relative importance of participation in high school career and technical education (CTE) programs in predicting community college outcomes. A hierarchical generalized linear model (HGLM) was used to predict community college outcome attainment among a random sample of direct community college entrants. Results show that…
Quantitative prediction of oral cancer risk in patients with oral leukoplakia.

Science.gov (United States)

Liu, Yao; Li, Yicheng; Fu, Yue; Liu, Tong; Liu, Xiaoyong; Zhang, Xinyan; Fu, Jie; Guan, Xiaobing; Chen, Tong; Chen, Xiaoxin; Sun, Zheng

2017-07-11

Exfoliative cytology has been widely used for early diagnosis of oral squamous cell carcinoma. We have developed an oral cancer risk index using DNA index value to quantitatively assess cancer risk in patients with oral leukoplakia, but with limited success. In order to improve the performance of the risk index, we collected exfoliative cytology, histopathology, and clinical follow-up data from two independent cohorts of normal, leukoplakia and cancer subjects (training set and validation set). Peaks were defined on the basis of first derivatives with positives, and modern machine learning techniques were utilized to build statistical prediction models on the reconstructed data. Random forest was found to be the best model with high sensitivity (100%) and specificity (99.2%). Using the Peaks-Random Forest model, we constructed an index (OCRI2) as a quantitative measurement of cancer risk. Among 11 leukoplakia patients with an OCRI2 over 0.5, 4 (36.4%) developed cancer during follow-up (23 ± 20 months), whereas 3 (5.3%) of 57 leukoplakia patients with an OCRI2 less than 0.5 developed cancer (32 ± 31 months). OCRI2 is better than other methods in predicting oral squamous cell carcinoma during follow-up. In conclusion, we have developed an exfoliative cytology-based method for quantitative prediction of cancer risk in patients with oral leukoplakia.
Comparison of statistical and clinical predictions of functional outcome after ischemic stroke.

Directory of Open Access Journals (Sweden)

Douglas D Thompson

Full Text Available To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor's clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs.A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS. Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3 using five previously described CPMs. The specificity of a doctor's informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97 and similar to CPMs (range 0.94 to 0.96; however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49 and clinical prediction models (range 0.38 to 0.45 was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76 and CPMs (range 0.69 to 0.75. No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.
Predicting The Outcome of Marketing Negotiations: Role-Playing versus Unaided Opinions

OpenAIRE

JS Armstrong; Philip D. Hutcherson

2005-01-01

Role -playing and unaided opinions were used to forecast the outcome of three negotiations. Consistent with prior re search, role-playing yielded more accurate predictions. In two studies on marketing negotiations, the predictions based on role-playing were correct for 53% of the predictions while unaided opinions were correct for only 7% (p
Understanding reproducibility of human IVF traits to predict next IVF cycle outcome.

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Wu, Bin; Shi, Juanzi; Zhao, Wanqiu; Lu, Suzhen; Silva, Marta; Gelety, Timothy J

2014-10-01

Evaluating the failed IVF cycle often provides useful prognostic information. Before undergoing another attempt, patients experiencing an unsuccessful IVF cycle frequently request information about the probability of future success. Here, we introduced the concept of reproducibility and formulae to predict the next IVF cycle outcome. The experimental design was based on the retrospective review of IVF cycle data from 2006 to 2013 in two different IVF centers and statistical analysis. The reproducibility coefficients (r) of IVF traits including number of oocytes retrieved, oocyte maturity, fertilization, embryo quality and pregnancy were estimated using the interclass correlation coefficient between the repeated IVF cycle measurements for the same patient by variance component analysis. The formulae were designed to predict next IVF cycle outcome. The number of oocytes retrieved from patients and their fertilization rate had the highest reproducibility coefficients (r = 0.81 ~ 0.84), which indicated a very close correlation between the first retrieval cycle and subsequent IVF cycles. Oocyte maturity and number of top quality embryos had middle level reproducibility (r = 0.38 ~ 0.76) and pregnancy rate had a relative lower reproducibility (r = 0.23 ~ 0.27). Based on these parameters, the next outcome for these IVF traits might be accurately predicted by the designed formulae. The introduction of the concept of reproducibility to our human IVF program allows us to predict future IVF cycle outcomes. The traits of oocyte numbers retrieved, oocyte maturity, fertilization, and top quality embryos had higher or middle reproducibility, which provides a basis for accurate prediction of future IVF outcomes. Based on this prediction, physicians may counsel their patients or change patient's stimulation plans, and laboratory embryologists may improve their IVF techniques accordingly.
The standardized surgical approach improves outcome of gallbladder cancer

Directory of Open Access Journals (Sweden)

Igna Dorian

2007-05-01

Full Text Available Abstract Background The objective of this study was to examine the extent of surgical procedures, pathological findings, complications and outcome of patients treated in the last 12 years for gallbladder cancer. Methods The impact of a standardized more aggressive approach compared with historical controls of our center with an individual approach was examined. Of 53 patients, 21 underwent resection for cure and 32 for palliation. Results Overall hospital mortality was 9% and procedure related mortality was 4%. The standardized approach in UICC stage IIa, IIb and III led to a significantly improved outcome compared to patients with an individual approach (Median survival: 14 vs. 7 months, mean+/-SEM: 26+/-7 vs. 17+/-5 months, p = 0.014. The main differences between the standardized and the individual approach were anatomical vs. atypical liver resection, performance of systematic lymph dissection of the hepaticoduodenal ligament and the resection of the common bile duct. Conclusion Anatomical liver resection, proof for bile duct infiltration and, in case of tumor invasion, radical resection and lymph dissection of the hepaticoduodenal ligament are essential to improve outcome of locally advanced gallbladder cancer.
Prognostic and predictive values of EGFR overexpression and EGFR copy number alteration in HER2-positive breast cancer.

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Lee, H J; Seo, A N; Kim, E J; Jang, M H; Kim, Y J; Kim, J H; Kim, S-W; Ryu, H S; Park, I A; Im, S-A; Gong, G; Jung, K H; Kim, H J; Park, S Y

2015-01-06

Epidermal growth factor receptor (EGFR) is overexpressed in a subset of human epidermal growth factor receptor 2 (HER2)-positive breast cancers, and coexpression of HER2 and EGFR has been reported to be associated with poor clinical outcome. Moreover, interaction between HER2 and EGFR has been suggested to be a possible basis for trastuzumab resistance. We analysed the clinical significance of EGFR overexpression and EGFR gene copy number alterations in 242 HER2-positive primary breast cancers. In addition, we examined the correlations between EGFR overexpression, trastuzumab response and clinical outcome in 447 primary, and 112 metastatic HER2-positive breast cancer patients treated by trastuzumab. Of the 242 primary cases, the level of EGFR overexpression was 2+ in 12.7% and 3+ in 11.8%. High EGFR gene copy number was detected in 10.3%. Epidermal growth factor receptor overexpression was associated with hormone receptor negativity and high Ki-67 proliferation index. In survival analyses, EGFR overexpression, but not high EGFR copy number, was associated with poor disease-free survival in all patients, and in the subgroup not receiving adjuvant trastuzumab. In 447 HER2-positive primary breast cancer patients treated with adjuvant trastuzumab, EGFR overexpression was also an independent poor prognostic factor. However, EGFR overexpression was not associated with trastuzumab response, progression-free survival or overall survival in the metastatic setting. Epidermal growth factor receptor overexpression, but not high EGFR copy number, is a poor prognostic factor in HER2-positive primary breast cancer. Epidermal growth factor receptor overexpression is a predictive factor for trastuzumab response in HER2-positive primary breast cancer, but not in metastatic breast cancer.
Validation of the online prediction tool PREDICT v. 2.0 in the Dutch breast cancer population

NARCIS (Netherlands)

Maaren, M.C. van; Steenbeek, C.D. van; Pharoah, P.D.; Witteveen, A.; Sonke, G.S.; Strobbe, L.J.A.; Poortmans, P.; Siesling, S.

2017-01-01

BACKGROUND: PREDICT version 2.0 is increasingly used to estimate prognosis in breast cancer. This study aimed to validate this tool in specific prognostic subgroups in the Netherlands. METHODS: All operated women with non-metastatic primary invasive breast cancer, diagnosed in 2005, were selected
Validation of the online prediction tool PREDICT v. 2.0 in the Dutch breast cancer population

NARCIS (Netherlands)

van Maaren, M. C.; van Steenbeek, C. D.; Pharoah, P. D.P.; Witteveen, A.; Sonke, Gabe S.; Strobbe, L.J.A.; Poortmans, P.M.P.; Siesling, S.

2017-01-01

Background PREDICT version 2.0 is increasingly used to estimate prognosis in breast cancer. This study aimed to validate this tool in specific prognostic subgroups in the Netherlands. Methods All operated women with non-metastatic primary invasive breast cancer, diagnosed in 2005, were selected from
Profiles of Genomic Instability in High-Grade Serous Ovarian Cancer Predict Treatment Outcome

DEFF Research Database (Denmark)

Wang, Zhigang C.; Birkbak, Nicolai Juul; Culhane, Aedín C.

2012-01-01

Purpose: High-grade serous cancer (HGSC) is the most common cancer of the ovary and is characterized by chromosomal instability. Defects in homologous recombination repair (HRR) are associated with genomic instability in HGSC, and are exploited by therapy targeting DNA repair. Defective HRR cause...
Development of a Breast Cancer Risk Prediction Model for Women in Nigeria.

Science.gov (United States)

Wang, Shengfeng; Ogundiran, Temidayo O; Ademola, Adeyinka; Oluwasola, Olayiwola A; Adeoye, Adewunmi O; Sofoluwe, Adenike; Morhason-Bello, Imran; Odedina, Stella O; Agwai, Imaria; Adebamowo, Clement; Obajimi, Millicent; Ojengbede, Oladosu; Olopade, Olufunmilayo I; Huo, Dezheng

2018-04-20

Risk prediction models have been widely used to identify women at higher risk of breast cancer. We aim to develop a model for absolute breast cancer risk prediction for Nigerian women. A total of 1,811 breast cancer cases and 2,225 controls from the Nigerian Breast Cancer Study (NBCS, 1998~2015) were included. Subjects were randomly divided into the training and validation sets. Incorporating local incidence rates, multivariable logistic regressions were used to develop the model. The NBCS model included age, age at menarche, parity, duration of breast feeding, family history of breast cancer, height, body mass index, benign breast diseases and alcohol consumption. The model developed in the training set performed well in the validation set. The discriminating accuracy of the NBCS model (area under ROC curve [AUC]=0.703, 95% confidence interval [CI]: 0.687-0.719) was better than the Black Women's Health Study (BWHS) model (AUC=0.605, 95% CI: 0.586-0.624), Gail model for White population (AUC=0.551, 95% CI: 0.531-0.571), and Gail model for Black population (AUC=0.545, 95% CI: 0.525-0.565). Compared to the BWHS, two Gail models, the net reclassification improvement of the NBCS model were 8.26%, 13.45% and 14.19%, respectively. We have developed a breast cancer risk prediction model specific to women in Nigeria, which provides a promising and indispensable tool to identify women in need of breast cancer early detection in SSA populations. Our model is the first breast cancer risk prediction model in Africa. It can be used to identify women at high-risk for breast cancer screening. Copyright ©2018, American Association for Cancer Research.
Cognitive and social processes predicting partner psychological adaptation to early stage breast cancer.

Science.gov (United States)

Manne, Sharon; Ostroff, Jamie; Fox, Kevin; Grana, Generosa; Winkel, Gary

2009-02-01

The diagnosis and subsequent treatment for early stage breast cancer is stressful for partners. Little is known about the role of cognitive and social processes predicting the longitudinal course of partners' psychosocial adaptation. This study evaluated the role of cognitive and social processing in partner psychological adaptation to early stage breast cancer, evaluating both main and moderator effect models. Moderating effects for meaning making, acceptance, and positive reappraisal on the predictive association of searching for meaning, emotional processing, and emotional expression on partner psychological distress were examined. Partners of women diagnosed with early stage breast cancer were evaluated shortly after the ill partner's diagnosis (N=253), 9 (N=167), and 18 months (N=149) later. Partners completed measures of emotional expression, emotional processing, acceptance, meaning making, and general and cancer-specific distress at all time points. Lower satisfaction with partner support predicted greater global distress, and greater use of positive reappraisal was associated with greater distress. The predicted moderator effects for found meaning on the associations between the search for meaning and cancer-specific distress were found and similar moderating effects for positive reappraisal on the associations between emotional expression and global distress and for acceptance on the association between emotional processing and cancer-specific distress were found. Results indicate several cognitive-social processes directly predict partner distress. However, moderator effect models in which the effects of partners' processing depends upon whether these efforts result in changes in perceptions of the cancer experience may add to the understanding of partners' adaptation to cancer.
Tolerability and outcomes of radiotherapy or chemoradiotherapy for rectal cancer in elderly patients aged 70 years and older

International Nuclear Information System (INIS)

Cai, Xin; Wu, Hongbin; Peng, Junjie; Zhu, Ji; Cai, Sanjun; Cai, Gang; Zhang, Zhen

2013-01-01

To assess the safety and outcomes of radiotherapy (RT) or chemoradiotherapy (CRT) in elderly patients (≥70) with rectal cancer. Elderly patients aged 70 and older with rectal cancer, who were treated with RT or CRT at a single institution, were retrospectively analyzed. Performance status (KPS and ECOG score) and comorbidity (Charlson comorbidity index) were calculated, and their correlation with treatment toxicity and overall survival were studied. Risk factors for overall survival were investigated using univariate and multivariate survival analysis. A total of 126 patients with locally advanced disease, local recurrence or synchronous metastasis were included, with a 3-year OS rate of 48.1%. Scheduled dosage of radiation was delivered to 69% of patients. Grade 3 toxicities occurred more often in patients treated with CRT versus RT. The occurrence of grade 3 toxicities was not related to KPS score, ECOG score, number of comorbidities, and Charlson score. Multivariate analysis found that only age and Charlson score were independent prognostic factors for predicting patients’ 3-year OS. The 3-year OS rate was significantly higher in patients with Charlson score <4 vs Charlson score ≥4 (71.1% vs. 26.4%, P=0.0003). Although toxicities may be significant, elderly patients with rectal cancer of varied stages can be safely treated with RT or CRT with careful monitoring and frequent modification of treatment. Except for patients’ age, Charlson comorbidity index may be helpful in assessing patients’ outcomes in elderly patients with rectal cancer
Individual Prediction of Heart Failure Among Childhood Cancer Survivors

Science.gov (United States)

Chow, Eric J.; Chen, Yan; Kremer, Leontien C.; Breslow, Norman E.; Hudson, Melissa M.; Armstrong, Gregory T.; Border, William L.; Feijen, Elizabeth A.M.; Green, Daniel M.; Meacham, Lillian R.; Meeske, Kathleen A.; Mulrooney, Daniel A.; Ness, Kirsten K.; Oeffinger, Kevin C.; Sklar, Charles A.; Stovall, Marilyn; van der Pal, Helena J.; Weathers, Rita E.; Robison, Leslie L.; Yasui, Yutaka

2015-01-01

Purpose To create clinically useful models that incorporate readily available demographic and cancer treatment characteristics to predict individual risk of heart failure among 5-year survivors of childhood cancer. Patients and Methods Survivors in the Childhood Cancer Survivor Study (CCSS) free of significant cardiovascular disease 5 years after cancer diagnosis (n = 13,060) were observed through age 40 years for the development of heart failure (ie, requiring medications or heart transplantation or leading to death). Siblings (n = 4,023) established the baseline population risk. An additional 3,421 survivors from Emma Children's Hospital (Amsterdam, the Netherlands), the National Wilms Tumor Study, and the St Jude Lifetime Cohort Study were used to validate the CCSS prediction models. Results Heart failure occurred in 285 CCSS participants. Risk scores based on selected exposures (sex, age at cancer diagnosis, and anthracycline and chest radiotherapy doses) achieved an area under the curve of 0.74 and concordance statistic of 0.76 at or through age 40 years. Validation cohort estimates ranged from 0.68 to 0.82. Risk scores were collapsed to form statistically distinct low-, moderate-, and high-risk groups, corresponding to cumulative incidences of heart failure at age 40 years of 0.5% (95% CI, 0.2% to 0.8%), 2.4% (95% CI, 1.8% to 3.0%), and 11.7% (95% CI, 8.8% to 14.5%), respectively. In comparison, siblings had a cumulative incidence of 0.3% (95% CI, 0.1% to 0.5%). Conclusion Using information available to clinicians soon after completion of childhood cancer therapy, individual risk for subsequent heart failure can be predicted with reasonable accuracy and discrimination. These validated models provide a framework on which to base future screening strategies and interventions. PMID:25287823
Black Hole Sign Predicts Poor Outcome in Patients with Intracerebral Hemorrhage.

Science.gov (United States)

Li, Qi; Yang, Wen-Song; Chen, Sheng-Li; Lv, Fu-Rong; Lv, Fa-Jin; Hu, Xi; Zhu, Dan; Cao, Du; Wang, Xing-Chen; Li, Rui; Yuan, Liang; Qin, Xin-Yue; Xie, Peng

2018-01-01

In spontaneous intracerebral hemorrhage (ICH), black hole sign has been proposed as a promising imaging marker that predicts hematoma expansion in patients with ICH. The aim of our study was to investigate whether admission CT black hole sign predicts hematoma growth in patients with ICH. From July 2011 till February 2016, patients with spontaneous ICH who underwent baseline CT scan within 6 h of symptoms onset and follow-up CT scan were recruited into the study. The presence of black hole sign on admission non-enhanced CT was independently assessed by 2 readers. The functional outcome was assessed using the modified Rankin Scale (mRS) at 90 days. Univariate and multivariable logistic regression analyses were performed to assess the association between the presence of the black hole sign and functional outcome. A total of 225 patients (67.6% male, mean age 60.3 years) were included in our study. Black hole sign was identified in 32 of 225 (14.2%) patients on admission CT scan. The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, baseline ICH volume, admission Glasgow Coma Scale score, and presence of black hole sign on baseline CT independently predict poor functional outcome at 90 days. There are significantly more patients with a poor functional outcome (defined as mRS ≥4) among patients with black hole sign than those without (84.4 vs. 32.1%, p black hole sign independently predicts poor outcome in patients with ICH. Early identification of black hole sign is useful in prognostic stratification and may serve as a potential therapeutic target for anti-expansion clinical trials. © 2018 S. Karger AG, Basel.
Artificial Neural Network System to Predict the Postoperative Outcome of Percutaneous Nephrolithotomy.

Science.gov (United States)

Aminsharifi, Alireza; Irani, Dariush; Pooyesh, Shima; Parvin, Hamid; Dehghani, Sakineh; Yousofi, Khalilolah; Fazel, Ebrahim; Zibaie, Fatemeh

2017-05-01

To construct, train, and apply an artificial neural network (ANN) system for prediction of different outcome variables of percutaneous nephrolithotomy (PCNL). We calculated predictive accuracy, sensitivity, and precision for each outcome variable. During the study period, all adult patients who underwent PCNL at our institute were enrolled in the study. Preoperative and postoperative variables were recorded, and stone-free status was assessed perioperatively with computed tomography scans. MATLAB software was used to design and train the network in a feed forward back-propagation error adjustment scheme. Preoperative and postoperative data from 200 patients (training set) were used to analyze the effect and relative relevance of preoperative values on postoperative parameters. The validated adequately trained ANN was used to predict postoperative outcomes in the subsequent 254 adult patients (test set) whose preoperative values were serially fed into the system. To evaluate system accuracy in predicting each postoperative variable, predicted values were compared with actual outcomes. Two hundred fifty-four patients (155 [61%] males) were considered the test set. Mean stone burden was 6702.86 ± 381.6 mm 3 . Overall stone-free rate was 76.4%. Fifty-four out of 254 patients (21.3%) required ancillary procedures (shockwave lithotripsy 5.9%, transureteral lithotripsy 10.6%, and repeat PCNL 4.7%). The accuracy and sensitivity of the system in predicting different postoperative variables ranged from 81.0% to 98.2%. As a complex nonlinear mathematical model, our ANN system is an interconnected data mining tool, which prospectively analyzes and "learns" the relationships between variables. The accuracy and sensitivity of the system for predicting the stone-free rate, the need for blood transfusion, and post-PCNL ancillary procedures ranged from 81.0% to 98.2%.The stone burden and the stone morphometry were among the most significant preoperative characteristics that
Matched Cohort Analysis of Outcomes of Definitive Radiotherapy for Prostate Cancer in Human Immunodeficiency Virus-Positive Patients

International Nuclear Information System (INIS)

Kahn, Shannon; Jani, Ashesh; Edelman, Scott; Rossi, Peter; Godette, Karen; Landry, Jerome; Anderson, Cynthia

2012-01-01

Purpose: To compare the biochemical outcome and toxicity scores of men with human immunodeficiency virus (HIV) and prostate cancer with a matched control population with negative or unknown HIV status when treated with external-beam radiotherapy (EBRT). Methods and Materials: A single-institution database of men with prostate cancer treated with EBRT from 1999 to 2009 was reviewed. Thirteen men with HIV were identified and matched to 2 control patients according to age, race, T stage, prostate-specific antigen level, Gleason score, RT dose, intensity-modulated RT vs. three-dimensional conformal RT, and whole-pelvis vs. prostate-only RT, for a total of 39 cases. The median follow-up time was 39 months (range, 3–110 months). Results: The 4-year biochemical failure (BF)-free survival rate was 87% in the HIV-positive group vs. 89% in the controls (p = 0.94). Pre- and post-RT viral loads were found to be predictive of BF (p = 0.04 and p = 0.04, respectively). No men with HIV died, whereas 2 in the control group died of causes unrelated to prostate cancer. Acute and chronic genitourinary and gastrointestinal toxicity were less in the HIV-positive patients than in controls (p 3 . Conclusions: Our findings suggest that men with HIV treated with EBRT have a similar risk of BF; however, high viral loads may contribute to an increased risk. This analysis supports that HIV-positive men with prostate cancer can be treated with definitive EBRT with similar disease control and toxicity outcomes as in the general population.
miR-21 Expression in Cancer Cells may Not Predict Resistance to Adjuvant Trastuzumab in Primary Breast Cancer

DEFF Research Database (Denmark)

Nielsen, Boye Schnack; Balslev, Eva; Poulsen, Tim Svenstrup

2014-01-01

, predominantly in cancer cells, or in both stromal and cancer cells. There was no obvious difference between the HER2-positive and HER2-negative tumors in terms of the miR-21 expression patterns and intensities. To explore the possibility that miR-21 expression levels and/or cellular localization could predict...... expression patterns and intensities revealed no association between the miR-21 scores in the cancer cell population (p = 0.69) or the stromal cells population (p = 0.13) and recurrent disease after adjuvant trastuzumab. Thus, our findings show that elevated miR-21 expression does not predict resistance......Trastuzumab is established as standard care for patients with HER2-positive breast cancer both in the adjuvant and metastatic setting. However, 50% of the patients do not respond to the trastuzumab therapy, and therefore new predictive biomarkers are highly warranted. MicroRNAs (miRs) constitute...
Predictive efficacy of radioisotope voiding cystography for renal outcome

International Nuclear Information System (INIS)

Kim, Seok Ki; Lee, Dong Soo; Kim, Kwang Myeung; Choi, Whang; Chung, June Key; Lee, Myung Chul

2000-01-01

As vesicoureteral reflux (VUR) could lead to renal functional deterioration when combined with urinary tract infection, we need to decide whether operative anti-reflux treatment should be performed at the time of diagnosis of VUR. Predictive value of radioisotope voiding cystography (RIVCG) for renal outcome was tested. In 35 children (18 males, 17 females), radiologic voiding cystoure-thrography (VCU), RIVCG and DMSA scan were performed. Change in renal function was evaluated using the follow-up DMSA scan, ultrasonography, and clinical information. Discriminant analysis was performed using individual or integrated variables such as reflux amount and extent at each phase of voiding on RIVCG, in addition to age, gender and cortical defect on DMSA scan at the time of diagnosis. Discriminant function was composed and its performance was examined. Reflux extent at the filling phase and reflux amount and extent at postvoiding phase had a significant prognostic value. Total reflux amount was a composite variable to predict prognosis. Discriminant function composed of reflux extent at the filling phase and reflux amount and extent at postvoiding phase showed better positive predictive value and specificity than conventional reflux grading. RIVCG could predict renal outcome by disclosing characteristic reflux pattern during various voiding phases.=20
Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer.

Science.gov (United States)

Loeb, Stacy; Shin, Sanghyuk S; Broyles, Dennis L; Wei, John T; Sanda, Martin; Klee, George; Partin, Alan W; Sokoll, Lori; Chan, Daniel W; Bangma, Chris H; van Schaik, Ron H N; Slawin, Kevin M; Marks, Leonard S; Catalona, William J

2017-07-01

To examine the use of the Prostate Health Index (PHI) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study. The study population included 728 men, with prostate-specific antigen (PSA) levels of 2-10 ng/mL and a negative digital rectal examination, enrolled in a prospective, multi-site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [PCPT] and European Randomised Study of Screening for Prostate Cancer [ERSPC] risk calculators). We also designed and internally validated a new PHI-based multivariable predictive model, and created a nomogram. Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI, with an area under the curve of 0.746. The bootstrap-corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision-curve analysis. Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

Risk prediction model for colorectal cancer: National Health Insurance Corporation study, Korea.

Science.gov (United States)

Shin, Aesun; Joo, Jungnam; Yang, Hye-Ryung; Bak, Jeongin; Park, Yunjin; Kim, Jeongseon; Oh, Jae Hwan; Nam, Byung-Ho

2014-01-01

Incidence and mortality rates of colorectal cancer have been rapidly increasing in Korea during last few decades. Development of risk prediction models for colorectal cancer in Korean men and women is urgently needed to enhance its prevention and early detection. Gender specific five-year risk prediction models were developed for overall colorectal cancer, proximal colon cancer, distal colon cancer, colon cancer and rectal cancer. The model was developed using data from a population of 846,559 men and 479,449 women who participated in health examinations by the National Health Insurance Corporation. Examinees were 30-80 years old and free of cancer in the baseline years of 1996 and 1997. An independent population of 547,874 men and 415,875 women who participated in 1998 and 1999 examinations was used to validate the model. Model validation was done by evaluating its performance in terms of discrimination and calibration ability using the C-statistic and Hosmer-Lemeshow-type chi-square statistics. Age, body mass index, serum cholesterol, family history of cancer, and alcohol consumption were included in all models for men, whereas age, height, and meat intake frequency were included in all models for women. Models showed moderately good discrimination ability with C-statistics between 0.69 and 0.78. The C-statistics were generally higher in the models for men, whereas the calibration abilities were generally better in the models for women. Colorectal cancer risk prediction models were developed from large-scale, population-based data. Those models can be used for identifying high risk groups and developing preventive intervention strategies for colorectal cancer.
Pretreatment Quality of Life Predicts for Locoregional Control in Head and Neck Cancer Patients: A Radiation Therapy Oncology Group Analysis

International Nuclear Information System (INIS)

Siddiqui, Farzan; Pajak, Thomas F.; Watkins-Bruner, Deborah; Konski, Andre A.; Coyne, James C.; Gwede, Clement K.; Garden, Adam S.; Spencer, Sharon A.; Jones, Christopher; Movsas, Benjamin

2008-01-01

Purpose: To analyze the prospectively collected health-related quality-of-life (HRQOL) data from patients enrolled in two Radiation Therapy Oncology Group randomized Phase III head and neck cancer trials (90-03 and 91-11) to assess their value as an independent prognostic factor for locoregional control (LRC) and/or overall survival (OS). Methods and Materials: HRQOL questionnaires, using a validated instrument, the Functional Assessment of Cancer Therapy-Head and Neck (FACT-H and N), version 2, were completed by patients before the start of treatment. OS and LRC were the outcome measures analyzed using a multivariate Cox proportional hazard model. Results: Baseline FACT-H and N data were available for 1,093 patients and missing for 417 patients. No significant difference in outcome was found between the patients with and without baseline FACT-H and N data (p = 0.58). The median follow-up time was 27.2 months for all patients and 49 months for surviving patients. Multivariate analyses were performed for both OS and LRC. Beyond tumor and nodal stage, Karnofsky performance status, primary site, cigarette use, use of concurrent chemotherapy, and altered fractionation schedules, the FACT-H and N score was independently predictive of LRC (but not OS), with p = 0.0038. The functional well-being component of the FACT-H and N predicted most significantly for LRC (p = 0.0004). Conclusions: This study represents, to our knowledge, the largest analysis of HRQOL as a prognostic factor in locally advanced head and neck cancer patients. The results of this study have demonstrated the importance of baseline HRQOL as a significant and independent predictor of LRC in patients with locally advanced head and neck cancer
Concurrent chemoradiotherapy improves survival outcome in muscle-invasive bladder cancer

International Nuclear Information System (INIS)

Byun, Sang Jun; Kim, Jin Hee; Oh, Young Kee; Kim, Byung Hoon

2015-01-01

To evaluate survival rates and prognostic factors related to treatment outcomes after bladder preserving therapy including transurethral resection of bladder tumor, radiotherapy (RT) with or without concurrent chemotherapy in bladder cancer with a curative intent. We retrospectively studied 50 bladder cancer patients treated with bladder-preserving therapy at Keimyung University Dongsan Medical Center from January 1999 to December 2010. Age ranged from 46 to 89 years (median, 71.5 years). Bladder cancer was the American Joint Committee on Cancer (AJCC) stage II, III, and IV in 9, 27, and 14 patients, respectively. Thirty patients were treated with concurrent chemoradiotherapy (CCRT) and 20 patients with RT alone. Nine patients received chemotherapy prior to CCRT or RT alone. Radiation was delivered with a four-field box technique (median, 63 Gy; range, 48.6 to 70.2 Gy). The follow-up periods ranged from 2 to 169 months (median, 34 months). Thirty patients (60%) showed complete response and 13 (26%) a partial response. All patients could have their own bladder preserved. Five-year overall survival (OS) rate was 37.2%, and the 5-year disease-free survival (DFS) rate was 30.2%. In multivariate analysis, tumor grade and CCRT were statistically significant in OS. Tumor grade was a significant prognostic factor related to OS. CCRT is also considered to improve survival outcomes. Further multi-institutional studies are needed to elucidate the impact of RT in bladder cancer
Predicting opportunities to increase utilization of laparoscopy for colon cancer.

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Keller, Deborah S; Parikh, Niraj; Senagore, Anthony J

2017-04-01

Despite proven safety and efficacy, rates of minimally invasive approaches for colon cancer remain low in the USA. Given the known benefits, investigating the root causes of underutilization and methods to increase laparoscopy is warranted. Our goal was to develop a predictive model of factors impacting use of laparoscopic surgery for colon cancer. The Premier Hospital Database was reviewed for elective colorectal resections for colon cancer (2009-2014). Patients were identified by ICD-9-CM diagnosis code and then stratified into open or laparoscopic approaches by ICD-9-CM procedure codes. An adjusted multivariate logistic regression model identified variables predictive of use of laparoscopy for colon cancer. A total of 24,245 patients were included-12,523 (52 %) laparoscopic and 11,722 (48 %) open. General surgeons performed the majority of all procedures (77.99 % open, 71.60 % laparoscopic). Overall use of laparoscopy increased from 48.94 to 52.03 % over the study period (p colon cancer laparoscopically. Colorectal surgeons were 32 % more likely to approach a case laparoscopically than general surgeons (OR 1.315, 95 % CI [1.222, 1.415], p characteristics that can be identified preoperatively to predict who will undergo surgery for colon cancer using laparoscopy. However, additional patients may be eligible for laparoscopy based on patient-level characteristics. These results have implications for regionalization and increasing teaching of MIS. Recognizing and addressing these variables with training and recruiting could increase use of minimally invasive approaches, with the associated clinical and financial benefits.
Measuring body composition using the bioelectrical impedance method can predict the outcomes of gemcitabine-based chemotherapy in patients with pancreatobiliary tract cancer.

Science.gov (United States)

Muramatsu, Mami; Tsuchiya, Aya; Ohta, Seiko; Iijima, Yukie; Maruyama, Miyuki; Onodera, Yoshiko; Hagihara, Megumi; Nakaya, Naoki; Sato, Itaru; Omura, Kenji; Ueno, Soichiro; Nakajima, Hideo

2015-12-01

In order to examine the effect on body composition of anticancer drug treatments, the body composition rate in patients being treated with gemcitabine (GEM)-based chemotherapy was measured over time on an outpatient basis with a simple body composition monitor using the bioelectrical impedance (BI) method. The results revealed a significant reduction in the body fat rate (P=0.01) over the course of treatment in patients with pancreatobiliary tract cancer who became unable to continue GEM-based chemotherapy due to progressive disease or a decreased performance status. Meanwhile, no changes were observed in the body composition of control patients with urothelial carcinoma receiving GEM-based chemotherapy. In association with the adverse reactions to GEM and the hematotoxicity profile, a decreased white blood cell count was more likely to occur in body fat-dominant patients (mean fat rate, 25.8%; mean muscle rate, 26.2%), whereas a decreased blood platelet count was more likely to occur in skeletal muscle-dominant patients (mean fat rate, 23.3%; mean muscle rates, 28.7%). The correlation between body composition parameters and the relative dose intensity (RDI) associated with GEM administration was also analyzed. The results revealed a positive correlation between the RDI and basal metabolism amount (P=0.03); however, the RDI did not correlate with the body fat rate, skeletal muscle rate or body mass index (P=0.61, P=0.14 and P=0.20, respectively). In conclusion, the body composition rate measurement using the BI method over time may be useful for predicting the outcome of GEM-based chemotherapy and adverse events in patients with pancreatobiliary tract cancer. In particular, the present findings indicate that the changes in body fat rate may be helpful as an adjunct index for assessing potential continuation of chemotherapy and changes in physical conditions.
The Glasgow Prognostic Score Predicts Response to Chemotherapy in Patients with Metastatic Breast Cancer.

Science.gov (United States)

Wang, Dexing; Duan, Li; Tu, Zhiquan; Yan, Fei; Zhang, Cuicui; Li, Xu; Cao, Yuzhu; Wen, Hongsheng

2016-01-01

Breast cancer is one of the most common causes of cancer death in women worldwide. The Glasgow Prognostic Score (GPS), a cumulative prognostic score based on C-reactive protein and albumin, indicates the presence of a systemic inflammatory response. The GPS has been adopted as a powerful prognostic tool for patients with various types of malignant tumors, including breast cancer. The aim of this study was to assess the value of the GPS in predicting the response and toxicity in breast cancer patients treated with chemotherapy. Patients with metastatic breast cancers in a progressive stage for consideration of chemotherapy were eligible. The clinical characteristics and demographics were recorded. The GPS was calculated before the onset of chemotherapy. Data on the response to chemotherapy and progression-free survival (PFS) were also collected. Objective tumor responses were evaluated according to Response Evaluation Criteria in Solid Tumors (RECIST). Toxicities were graded according to National Cancer Institute Common Terminology Criteria for Adverse Events (NCI-CTC) version 3.0 throughout therapy. In total, 106 breast cancer patients were recruited. The GPS was associated with the response rate (p = 0.05), the clinical benefit rate (p = 0.03), and PFS (p = 0.005). The GPS was the only independent predictor of PFS (p = 0.005). The GPS was significantly associated with neutropenia, thrombocytopenia, anorexia, nausea and vomiting, fatigue, and mucositis (p = 0.05-0.001). Our data demonstrate that GPS assessment is associated with poor clinical outcomes and severe chemotherapy-related toxicities in patients with metastatic breast cancer who have undergone chemotherapy, without any specific indication regarding the type of chemotherapy applied. © 2016 S. Karger AG, Basel.
Clinical course and outcome of patients with high-level microsatellite instability cancers in a real-life setting: a retrospective analysis

Directory of Open Access Journals (Sweden)

Halpern N

2017-03-01

Full Text Available Naama Halpern,1 Yael Goldberg,2 Luna Kadouri,2 Morasha Duvdevani,2 Tamar Hamburger,2 Tamar Peretz,2 Ayala Hubert2 1Institute of Oncology, The Chaim Sheba Medical Center, Tel Hashomer, Israel; 2Sharett Institute of Oncology, Hadassah Medical Center, Hebrew University, Jerusalem, Israel Background: The prognostic and predictive significance of the high-level microsatellite instability (MSI-H phenotype in various malignancies is unclear. We describe the characteristics, clinical course, and outcomes of patients with MSI-H malignancies treated in a real-life hospital setting.Patients and methods: A retrospective analysis of MSI-H cancer patient files was conducted. We analyzed the genetic data, clinical characteristics, and oncological treatments, including chemotherapy and surgical interventions.Results: Clinical data of 73 MSI-H cancer patients were available. Mean age at diagnosis of first malignancy was 52.3 years. Eight patients (11% had more than four malignancies each. Most patients (76% had colorectal cancer (CRC. Seventeen patients (23% had only extracolonic malignancies. Eighteen women (36% had gynecological malignancy. Nine women (18% had breast cancer. Mean follow-up was 8.5 years. Five-year overall survival and disease-free survival of all MSI-H cancer patients from first malignancy were 86% and 74.6%, respectively. Five-year overall survival rates of stage 2, 3, and 4 MSI-H CRC patients were 89.5%, 58.4%, and 22.9%, respectively.Conclusion: Although the overall prognosis of MSI-H cancer patients is favorable, this advantage may not be maintained in advanced MSI-H CRC patients. Keywords: microsatellite instability, malignancy, treatment, outcome
Predictive factors of thyroid cancer in patients with Graves' disease.

Science.gov (United States)

Ren, Meng; Wu, Mu Chao; Shang, Chang Zhen; Wang, Xiao Yi; Zhang, Jing Lu; Cheng, Hua; Xu, Ming Tong; Yan, Li

2014-01-01

The best preoperative examination in Graves' disease with thyroid cancer still remains uncertain. The objectives of the present study were to investigate the prevalence of thyroid cancer in Graves' disease patients, and to identify the predictive factors and ultrasonographic features of thyroid cancer that may aid the preoperative diagnosis in Graves' disease. This retrospective study included 423 patients with Graves' disease who underwent surgical treatment from 2002 to 2012 at our institution. The clinical features and ultrasonographic findings of thyroid nodules were recorded. The diagnosis of thyroid cancer was determined according to the pathological results. Thyroid cancer was discovered in 58 of the 423 (13.7 %) surgically treated Graves' disease patients; 46 of those 58 patients had thyroid nodules, and the other 12 patients were diagnosed with incidentally discovered thyroid carcinomas without thyroid nodules. Among the 58 patients with thyroid cancer, papillary microcarcinomas were discovered in 50 patients, and multifocality and lymph node involvement were detected in the other 8 patients. Multivariate regression analysis showed younger age was the only significant factor predictive of metastatic thyroid cancer. Ultrasonographic findings of calcification and intranodular blood flow in thyroid nodules indicate that they are more likely to harbor thyroid cancers. Because the influencing factor of metastatic thyroid cancers in Graves' disease is young age, every suspicious nodule in Graves' disease patients should be evaluated and treated carefully, especially in younger patients because of the potential for metastasis.
Comparison of oncological outcomes of right-sided colon cancer versus left-sided colon cancer after curative resection: Which side is better outcome?

Science.gov (United States)

Lim, Dae Ro; Kuk, Jung Kul; Kim, Taehyung; Shin, Eung Jin

2017-10-01

There are embryological origins, anatomical, histological, genetic, and immunological differences between right-sided colon cancer (RCC) and left-sided colon cancer (LCC). Many studies have sought to determine the survival and prognosis according to tumor location. This study aimed to analyze outcomes between RCC and LCC. Between January 2000 and December 2012, data on 414 patients who underwent curative resection for RCC and LCC were retrieved from a retrospective database. Propensity score matching (1:1) was performed and RCC was identified in 207 and LCC in 207 patients. On average, RCC exhibited a more advanced N stage, increased tumor size, more frequently poorly differentiated tumors, more harvested lymph nodes, and more positivity of lymphovascular invasion than LCC. With a median follow-up of 66.7 months, the 5-year overall survival (OS) rates for RCC and LCC were 82.1% and 88.7%, respectively, (P cancers, the DFS rates were 61.1% (RCC) and 81.9% (LCC; P colon cancer is needed.
Equity and improvement in outcome of breast cancer in Denmark

DEFF Research Database (Denmark)

Andreasen, A H; Mouridsen, H T; Andersen, K W

1994-01-01

The trend in the prognosis for female breast cancer patients was investigated by comparing Kaplan-Meier survival curves of different patient cohorts diagnosed during the period 1948-87. The study is based on 71,448 patients from the Danish Cancer Registry. The cohorts were defined by age...... in other parts of Denmark. For patients diagnosed in 1978-87 the prognosis, however, reached an equal level in all parts of the country. Thus, it is reasonable to assume that the national programme introduced in 1977 by the Danish Breast Cancer Cooperative Group (DBCG) has played an important role...... and not only brought about therapeutic improvements in breast cancer treatment in Denmark, but also ensured equity in the outcome on a national scale....
Revisiting the Surveillance Epidemiology and End Results Cancer Registry and Medicare Health Outcomes Survey (SEER-MHOS) Linked Data Resource for Patient-Reported Outcomes Research in Older Adults with Cancer.

Science.gov (United States)

Kent, Erin E; Malinoff, Rochelle; Rozjabek, Heather M; Ambs, Anita; Clauser, Steven B; Topor, Marie A; Yuan, Gigi; Burroughs, James; Rodgers, Anne B; DeMichele, Kimberly

2016-01-01

Researchers and clinicians are increasingly recognizing the value of patient-reported outcome (PRO) data to better characterize people's health and experiences with illness and care. Considering the rising prevalence of cancer in adults aged 65 and older, PRO data are particularly relevant for older adults with cancer, who often require complex cancer care and have additional comorbid conditions. A data linkage between the Surveillance Epidemiology and End Results (SEER) cancer registry and the Medicare Health Outcomes Survey (MHOS) was created through a partnership between the National Cancer Institute and the Centers for Medicare and Medicaid Services that created the opportunity to examine PROs in Medicare Advantage enrollees with and without cancer. The December 2013 linkage of SEER-MHOS data included the linked data for 12 cohorts, bringing the number of individuals in the linked data set to 95,723 with cancer and 1,510,127 without. This article reviews the features of the resource and provides information on some descriptive characteristics of the individuals in the data set (health-related quality of life, body mass index, fall risk management, number of unhealthy days in the past month). Individuals without (n=258,108) and with (n=3,440) cancer (1,311 men with prostate cancer, 982 women with breast cancer, 689 with colorectal cancer, 458 with lung cancer) were included in the current descriptive analysis. Given increasing longevity, advances in effective therapies and earlier detection, and population growth, the number of individuals aged 65 and older with cancer is expected to reach more than 12 million by 2020. SEER-MHOS provides population-level, self-reported, cancer registry-linked data for person-centered surveillance research on this growing population. © 2016, Copyright the Authors Journal compilation © 2016, The American Geriatrics Society.
Gene expression alterations associated with outcome in aromatase inhibitor-treated ER+ early-stage breast cancer patients

DEFF Research Database (Denmark)

Gravgaard Thomsen, Karina Hedelund; Lyng, Maria Bibi; Elias, Daniel

2015-01-01

predictive of outcome of ER+ breast cancer patients treated with AIs are needed. Global gene expression analysis was performed on ER+ primary breast cancers from patients treated with adjuvant AI monotherapy; half experienced recurrence (median follow-up 6.7 years). Gene expression alterations were validated...... by qRT-PCR, and functional studies evaluating the effect of siRNA-mediated gene knockdown on cell growth were performed. Twenty-six genes, including TFF3, DACH1, RGS5, and GHR, were shown to exhibit altered expression in tumors from patients with recurrence versus non-recurrent (fold change ≥1.5, p ....05), and the gene expression alterations were confirmed using qRT-PCR. Ten of these 26 genes could be linked in a network associated with cellular proliferation, growth, and development. TFF3, which encodes for trefoil factor 3 and is an estrogen-responsive oncogene shown to play a functional role in tamoxifen...
Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker.

Directory of Open Access Journals (Sweden)

Heewon Park

Full Text Available The personal genomics era has attracted a large amount of attention for anti-cancer therapy by patient-specific analysis. Patient-specific analysis enables discovery of individual genomic characteristics for each patient, and thus we can effectively predict individual genetic risk of disease and perform personalized anti-cancer therapy. Although the existing methods for patient-specific analysis have successfully uncovered crucial biomarkers, their performance takes a sudden turn for the worst in the presence of outliers, since the methods are based on non-robust manners. In practice, clinical and genomic alterations datasets usually contain outliers from various sources (e.g., experiment error, coding error, etc. and the outliers may significantly affect the result of patient-specific analysis. We propose a robust methodology for patient-specific analysis in line with the NetwrokProfiler. In the proposed method, outliers in high dimensional gene expression levels and drug response datasets are simultaneously controlled by robust Mahalanobis distance in robust principal component space. Thus, we can effectively perform for predicting anti-cancer drug sensitivity and identifying sensitivity-specific biomarkers for individual patients. We observe through Monte Carlo simulations that the proposed robust method produces outstanding performances for predicting response variable in the presence of outliers. We also apply the proposed methodology to the Sanger dataset in order to uncover cancer biomarkers and predict anti-cancer drug sensitivity, and show the effectiveness of our method.
Validation of revised Epstein's criteria for insignificant prostate cancer prediction in a Greek subpopulation.

Science.gov (United States)

Chondros, Κ; Karpathakis, Ν; Heretis, Ι; Mavromanolakis, Ε; Chondros, N; Sofras, F; Mamoulakis, C

2015-01-01

Different treatment options for patients with prostate cancer (PCa) are applicable after stratifying patients according to various classification criteria. The purpose of our study is to evaluate the revised Epstein's criteria for insignificant PCa prediction in a Greek subpopulation. During a 4-year-period, 172 Cretan patients were submitted to radical retropubic prostatectomy in our institution. 23 out of them met the revised Epstein's criteria for the presence of clinically insignificant PCa (clinical stage T1c, prostate specific antigen density < 0.15 ng/ml/g, absence of Gleason pattern 4-5, <3 positive biopsy cores, presence of <50% tumor per core) during pre-treatment evaluation and were retrospectively included in the study. Post-surgery outcomes were evaluated including pathological stage, surgical margins and Gleason score upgrade. Organ confined disease and insignificant PCa were predicted with a 74% and 31% accuracy, respectively. These figures are remarkably lower than those derived from similar studies worldwide. Due to the high variation in the revised Epstein's criteria prediction accuracy observed worldwide, the development and implementation of novel tools/nomograms with a greater predictive accuracy is still warranted. Hippokratia 2015, 19 (1): 30-33.
Loss of secreted frizzled-related protein 4 correlates with an aggressive phenotype and predicts poor outcome in ovarian cancer patients.

Directory of Open Access Journals (Sweden)

Francis Jacob

Full Text Available BACKGROUND: Activation of the Wnt signaling pathway is implicated in aberrant cellular proliferation in various cancers. In 40% of endometrioid ovarian cancers, constitutive activation of the pathway is due to oncogenic mutations in β-catenin or other inactivating mutations in key negative regulators. Secreted frizzled-related protein 4 (SFRP4 has been proposed to have inhibitory activity through binding and sequestering Wnt ligands. METHODOLOGY/PRINCIPAL FINDINGS: We performed RT-qPCR and Western-blotting in primary cultures and ovarian cell lines for SFRP4 and its key downstream regulators activated β-catenin, β-catenin and GSK3β. SFRP4 was then examined by immunohistochemistry in a cohort of 721 patients and due to its proposed secretory function, in plasma, presenting the first ELISA for SFRP4. SFRP4 was most highly expressed in tubal epithelium and decreased with malignant transformation, both on RNA and on protein level, where it was even more profound in the membrane fraction (p<0.0001. SFRP4 was expressed on the protein level in all histotypes of ovarian cancer but was decreased from borderline tumors to cancers and with loss of cellular differentiation. Loss of membrane expression was an independent predictor of poor survival in ovarian cancer patients (p = 0.02 unadjusted; p = 0.089 adjusted, which increased the risk of a patient to die from this disease by the factor 1.8. CONCLUSIONS/SIGNIFICANCE: Our results support a role for SFRP4 as a tumor suppressor gene in ovarian cancers via inhibition of the Wnt signaling pathway. This has not only predictive implications but could also facilitate a therapeutic role using epigenetic targets.
Setting the vision: applied patient-reported outcomes and smart, connected digital healthcare systems to improve patient-centered outcomes prediction in critical illness.

Science.gov (United States)

Wysham, Nicholas G; Abernethy, Amy P; Cox, Christopher E

2014-10-01

Prediction models in critical illness are generally limited to short-term mortality and uncommonly include patient-centered outcomes. Current outcome prediction tools are also insensitive to individual context or evolution in healthcare practice, potentially limiting their value over time. Improved prognostication of patient-centered outcomes in critical illness could enhance decision-making quality in the ICU. Patient-reported outcomes have emerged as precise methodological measures of patient-centered variables and have been successfully employed using diverse platforms and technologies, enhancing the value of research in critical illness survivorship and in direct patient care. The learning health system is an emerging ideal characterized by integration of multiple data sources into a smart and interconnected health information technology infrastructure with the goal of rapidly optimizing patient care. We propose a vision of a smart, interconnected learning health system with integrated electronic patient-reported outcomes to optimize patient-centered care, including critical care outcome prediction. A learning health system infrastructure integrating electronic patient-reported outcomes may aid in the management of critical illness-associated conditions and yield tools to improve prognostication of patient-centered outcomes in critical illness.
Endosomal gene expression: a new indicator for prostate cancer patient prognosis?

LENUS (Irish Health Repository)

Johnson, Ian R D

2015-11-10

Prostate cancer continues to be a major cause of morbidity and mortality in men, but a method for accurate prognosis in these patients is yet to be developed. The recent discovery of altered endosomal biogenesis in prostate cancer has identified a fundamental change in the cell biology of this cancer, which holds great promise for the identification of novel biomarkers that can predict disease outcomes. Here we have identified significantly altered expression of endosomal genes in prostate cancer compared to non-malignant tissue in mRNA microarrays and confirmed these findings by qRT-PCR on fresh-frozen tissue. Importantly, we identified endosomal gene expression patterns that were predictive of patient outcomes. Two endosomal tri-gene signatures were identified from a previously published microarray cohort and had a significant capacity to stratify patient outcomes. The expression of APPL1, RAB5A, EEA1, PDCD6IP, NOX4 and SORT1 were altered in malignant patient tissue, when compared to indolent and normal prostate tissue. These findings support the initiation of a case-control study using larger cohorts of prostate tissue, with documented patient outcomes, to determine if different combinations of these new biomarkers can accurately predict disease status and clinical progression in prostate cancer patients.
Physical Activity, Biomarkers, and Disease Outcomes in Cancer Survivors: A Systematic Review

Science.gov (United States)

Friedenreich, Christine M.; Courneya, Kerry S.; Siddiqi, Sameer M.; McTiernan, Anne; Alfano, Catherine M.

2012-01-01

Background Cancer survivors often seek information about how lifestyle factors, such as physical activity, may influence their prognosis. We systematically reviewed studies that examined relationships between physical activity and mortality (cancer-specific and all-cause) and/or cancer biomarkers. Methods We identified 45 articles published from January 1950 to August 2011 through MEDLINE database searches that were related to physical activity, cancer survival, and biomarkers potentially relevant to cancer survival. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement to guide this review. Study characteristics, mortality outcomes, and biomarker-relevant and subgroup results were abstracted for each article that met the inclusion criteria (ie, research articles that included participants with a cancer diagnosis, mortality outcomes, and an assessment of physical activity). Results There was consistent evidence from 27 observational studies that physical activity is associated with reduced all-cause, breast cancer–specific, and colon cancer–specific mortality. There is currently insufficient evidence regarding the association between physical activity and mortality for survivors of other cancers. Randomized controlled trials of exercise that included biomarker endpoints suggest that exercise may result in beneficial changes in the circulating level of insulin, insulin-related pathways, inflammation, and, possibly, immunity; however, the evidence is still preliminary. Conclusions Future research directions identified include the need for more observational studies on additional types of cancer with larger sample sizes; the need to examine whether the association between physical activity and mortality varies by tumor, clinical, or risk factor characteristics; and the need for research on the biological mechanisms involved in the association between physical activity and survival after a cancer diagnosis. Future randomized
Proteomic biomarkers predicting lymph node involvement in serum of cervical cancer patients. Limitations of SELDI-TOF MS

Directory of Open Access Journals (Sweden)

Van Gorp Toon

2012-06-01

Full Text Available Abstract Background Lymph node status is not part of the staging system for cervical cancer, but provides important information for prognosis and treatment. We investigated whether lymph node status can be predicted with proteomic profiling. Material & methods Serum samples of 60 cervical cancer patients (FIGO I/II were obtained before primary treatment. Samples were run through a HPLC depletion column, eliminating the 14 most abundant proteins ubiquitously present in serum. Unbound fractions were concentrated with spin filters. Fractions were spotted onto CM10 and IMAC30 surfaces and analyzed with surface-enhanced laser desorption time of flight (SELDI-TOF mass spectrometry (MS. Unsupervised peak detection and peak clustering was performed using MASDA software. Leave-one-out (LOO validation for weighted Least Squares Support Vector Machines (LSSVM was used for prediction of lymph node involvement. Other outcomes were histological type, lymphvascular space involvement (LVSI and recurrent disease. Results LSSVM models were able to determine LN status with a LOO area under the receiver operating characteristics curve (AUC of 0.95, based on peaks with m/z values 2,698.9, 3,953.2, and 15,254.8. Furthermore, we were able to predict LVSI (AUC 0.81, to predict recurrence (AUC 0.92, and to differentiate between squamous carcinomas and adenocarcinomas (AUC 0.88, between squamous and adenosquamous carcinomas (AUC 0.85, and between adenocarcinomas and adenosquamous carcinomas (AUC 0.94. Conclusions Potential markers related with lymph node involvement were detected, and protein/peptide profiling support differentiation between various subtypes of cervical cancer. However, identification of the potential biomarkers was hampered by the technical limitations of SELDI-TOF MS.
Nomogram for predicting the probability of the positive outcome of ...

African Journals Online (AJOL)

F.A. Yeboah

Abstract. Introduction and objectives: Several existing models have been developed to predict positive prostate biopsy among men undergoing evaluation for prostate cancer (PCa). However, most of these models have come from industrialized countries. We therefore, developed a prostate disease nomogram model to ...

Role of Subdural Electrocorticography in Prediction of Long-Term Seizure Outcome in Epilepsy Surgery

Science.gov (United States)

Asano, Eishi; Juhasz, Csaba; Shah, Aashit; Sood, Sandeep; Chugani, Harry T.

2009-01-01

Since prediction of long-term seizure outcome using preoperative diagnostic modalities remains suboptimal in epilepsy surgery, we evaluated whether interictal spike frequency measures obtained from extraoperative subdural electrocorticography (ECoG) recording could predict long-term seizure outcome. This study included 61 young patients (age…
Patient feature based dosimetric Pareto front prediction in esophageal cancer radiotherapy.

Science.gov (United States)

Wang, Jiazhou; Jin, Xiance; Zhao, Kuaike; Peng, Jiayuan; Xie, Jiang; Chen, Junchao; Zhang, Zhen; Studenski, Matthew; Hu, Weigang

2015-02-01

To investigate the feasibility of the dosimetric Pareto front (PF) prediction based on patient's anatomic and dosimetric parameters for esophageal cancer patients. Eighty esophagus patients in the authors' institution were enrolled in this study. A total of 2928 intensity-modulated radiotherapy plans were obtained and used to generate PF for each patient. On average, each patient had 36.6 plans. The anatomic and dosimetric features were extracted from these plans. The mean lung dose (MLD), mean heart dose (MHD), spinal cord max dose, and PTV homogeneity index were recorded for each plan. Principal component analysis was used to extract overlap volume histogram (OVH) features between PTV and other organs at risk. The full dataset was separated into two parts; a training dataset and a validation dataset. The prediction outcomes were the MHD and MLD. The spearman's rank correlation coefficient was used to evaluate the correlation between the anatomical features and dosimetric features. The stepwise multiple regression method was used to fit the PF. The cross validation method was used to evaluate the model. With 1000 repetitions, the mean prediction error of the MHD was 469 cGy. The most correlated factor was the first principal components of the OVH between heart and PTV and the overlap between heart and PTV in Z-axis. The mean prediction error of the MLD was 284 cGy. The most correlated factors were the first principal components of the OVH between heart and PTV and the overlap between lung and PTV in Z-axis. It is feasible to use patients' anatomic and dosimetric features to generate a predicted Pareto front. Additional samples and further studies are required improve the prediction model.
Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

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Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

2016-02-19

Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.
The Predictive Accuracy of PREDICT : A Personalized Decision-Making Tool for Southeast Asian Women With Breast Cancer

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Wong, Hoong-Seam; Subramaniam, Shridevi; Alias, Zarifah; Taib, Nur Aishah; Ho, Gwo-Fuang; Ng, Char-Hong; Yip, Cheng-Har; Verkooijen, Helena M.; Hartman, Mikael; Bhoo Pathy, N

Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480
Predictive Accuracy of the PanCan Lung Cancer Risk Prediction Model -External Validation based on CT from the Danish Lung Cancer Screening Trial

DEFF Research Database (Denmark)

Winkler Wille, Mathilde M.; van Riel, Sarah J.; Saghir, Zaigham

2015-01-01

Objectives: Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. Methods: From...... the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were...... used to evaluate risk discrimination. Results: AUCs of 0.826–0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer...
Gene expression signature of normal cell-of-origin predicts ovarian tumor outcomes.

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Melissa A Merritt

Full Text Available The potential role of the cell-of-origin in determining the tumor phenotype has been raised, but not adequately examined. We hypothesized that distinct cells-of-origin may play a role in determining ovarian tumor phenotype and outcome. Here we describe a new cell culture medium for in vitro culture of paired normal human ovarian (OV and fallopian tube (FT epithelial cells from donors without cancer. While these cells have been cultured individually for short periods of time, to our knowledge this is the first long-term culture of both cell types from the same donors. Through analysis of the gene expression profiles of the cultured OV/FT cells we identified a normal cell-of-origin gene signature that classified primary ovarian cancers into OV-like and FT-like subgroups; this classification correlated with significant differences in clinical outcomes. The identification of a prognostically significant gene expression signature derived solely from normal untransformed cells is consistent with the hypothesis that the normal cell-of-origin may be a source of ovarian tumor heterogeneity and the associated differences in tumor outcome.
Improvements in 5-year outcomes of stage II/III rectal cancer relative to colon cancer.

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Renouf, Daniel J; Woods, Ryan; Speers, Caroline; Hay, John; Phang, P Terry; Fitzgerald, Catherine; Kennecke, Hagen

2013-12-01

Stage for stage, rectal cancer has historically been associated with inferior survival compared with colon cancer. Randomized trials of rectal cancer have generally demonstrated improvements in locoregional relapse but not survival. We compared therapy and outcomes of colon versus rectal cancer in 2 time cohorts to determine if relative improvements have occurred. Patients with resected stage II/III colorectal cancer referred to the British Columbia Cancer Agency in 1989/1990 and 2001/2002 were identified. The higher of clinical or pathologic stage was used for patients receiving preoperative chemoradiation. Disease-specific survival (DSS) and overall survival (OS) were compared for rectal and colon cancer between the 2 cohorts. Kaplan-Meier method was used for survival analysis. A total of 1427 patients were included, with 375 from 1989/1990 and 1052 from 2001/2002. Between 1989/1990 and 2001/2002 there were significant increases in the use of perioperative chemotherapy for both rectal and colon cancer (Prectal cancer. DSS significantly improved for rectal (Pcolon cancer (P=0.069). Five-year OS was significantly inferior for rectal versus colon cancer in 1989/1990 (46.1% vs. 57.2%, P=0.023) and was similar to that of colon cancer in 2001/2002 (63.7% vs. 66.2%, P=0.454). Advances in locoregional and systemic therapy significantly improved survival among patients with rectal cancer. DSS and OS are now similar between colon and rectal cancer for both stage II and III disease.
Preliminary study of tumor heterogeneity in imaging predicts two year survival in pancreatic cancer patients.

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Jayasree Chakraborty

Full Text Available Pancreatic ductal adenocarcinoma (PDAC is one of the most lethal cancers in the United States with a five-year survival rate of 7.2% for all stages. Although surgical resection is the only curative treatment, currently we are unable to differentiate between resectable patients with occult metastatic disease from those with potentially curable disease. Identification of patients with poor prognosis via early classification would help in initial management including the use of neoadjuvant chemotherapy or radiation, or in the choice of postoperative adjuvant therapy. PDAC ranges in appearance from homogeneously isoattenuating masses to heterogeneously hypovascular tumors on CT images; hence, we hypothesize that heterogeneity reflects underlying differences at the histologic or genetic level and will therefore correlate with patient outcome. We quantify heterogeneity of PDAC with texture analysis to predict 2-year survival. Using fuzzy minimum-redundancy maximum-relevance feature selection and a naive Bayes classifier, the proposed features achieve an area under receiver operating characteristic curve (AUC of 0.90 and accuracy (Ac of 82.86% with the leave-one-image-out technique and an AUC of 0.80 and Ac of 75.0% with three-fold cross-validation. We conclude that texture analysis can be used to quantify heterogeneity in CT images to accurately predict 2-year survival in patients with pancreatic cancer. From these data, we infer differences in the biological evolution of pancreatic cancer subtypes measurable in imaging and identify opportunities for optimized patient selection for therapy.
Preliminary study of tumor heterogeneity in imaging predicts two year survival in pancreatic cancer patients.

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Chakraborty, Jayasree; Langdon-Embry, Liana; Cunanan, Kristen M; Escalon, Joanna G; Allen, Peter J; Lowery, Maeve A; O'Reilly, Eileen M; Gönen, Mithat; Do, Richard G; Simpson, Amber L

2017-01-01

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers in the United States with a five-year survival rate of 7.2% for all stages. Although surgical resection is the only curative treatment, currently we are unable to differentiate between resectable patients with occult metastatic disease from those with potentially curable disease. Identification of patients with poor prognosis via early classification would help in initial management including the use of neoadjuvant chemotherapy or radiation, or in the choice of postoperative adjuvant therapy. PDAC ranges in appearance from homogeneously isoattenuating masses to heterogeneously hypovascular tumors on CT images; hence, we hypothesize that heterogeneity reflects underlying differences at the histologic or genetic level and will therefore correlate with patient outcome. We quantify heterogeneity of PDAC with texture analysis to predict 2-year survival. Using fuzzy minimum-redundancy maximum-relevance feature selection and a naive Bayes classifier, the proposed features achieve an area under receiver operating characteristic curve (AUC) of 0.90 and accuracy (Ac) of 82.86% with the leave-one-image-out technique and an AUC of 0.80 and Ac of 75.0% with three-fold cross-validation. We conclude that texture analysis can be used to quantify heterogeneity in CT images to accurately predict 2-year survival in patients with pancreatic cancer. From these data, we infer differences in the biological evolution of pancreatic cancer subtypes measurable in imaging and identify opportunities for optimized patient selection for therapy.
Perineural Invasion Predicts Increased Recurrence, Metastasis, and Death From Prostate Cancer Following Treatment With Dose-Escalated Radiation Therapy

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Feng, Felix Y.; Qian Yushen; Stenmark, Matthew H.; Halverson, Schuyler; Blas, Kevin; Vance, Sean; Sandler, Howard M.; Hamstra, Daniel A.

2011-01-01

Purpose: To assess the prognostic value of perineural invasion (PNI) for patients treated with dose-escalated external-beam radiation therapy for prostate cancer. Methods and Materials: Outcomes were analyzed for 651 men treated for prostate cancer with EBRT to a minimum dose ≥75 Gy. We assessed the impact of PNI as well as pretreatment and treatment-related factors on freedom from biochemical failure (FFBF), freedom from metastasis (FFM), cause-specific survival (CSS), and overall survival. Results: PNI was present in 34% of specimens at biopsy and was significantly associated with higher Gleason score (GS), T stage, and prostate-specific antigen level. On univariate and multivariate analysis, the presence of PNI was associated with worse FFBF (hazard ratio = 1.7, p <0.006), FFM (hazard ratio = 1.8, p <0.03), and CSS (HR = 1.4, p <0.05) compared with absence of PNI; there was no difference in overall survival. Seven-year rates of FFBF, FFM, and CCS were 64% vs. 80%, 84% vs. 92%, and 91% vs. 95% for those patients with and without PNI, respectively. On recursive partitioning analysis, PNI predicted for worse FFM and CSS in patients with GS 8–10, with FFM of 67% vs. 89% (p <0.02), and CSS of 69% vs. 91%, (p <0.04) at 7 years for those with and without PNI, respectively. Conclusions: The presence of PNI in the prostate biopsy predicts worse clinical outcome for patients treated with dose-escalated external-beam radiation therapy. Particularly in patients with GS 8–10 disease, the presence of PNI suggests an increased risk of metastasis and prostate cancer death.
Perineural Invasion Predicts Increased Recurrence, Metastasis, and Death From Prostate Cancer Following Treatment With Dose-Escalated Radiation Therapy

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Feng, Felix Y. [University of Michigan Medical Center, Ann Arbor, MI (United States); Ann Arbor Veteran Affairs Medical System, Ann Arbor, MI (United States); Qian Yushen; Stenmark, Matthew H.; Halverson, Schuyler; Blas, Kevin; Vance, Sean [University of Michigan Medical Center, Ann Arbor, MI (United States); Sandler, Howard M. [Cedars Sinai Medical System, Los Angeles, CA (United States); Hamstra, Daniel A., E-mail: dhamm@med.umich.edu [University of Michigan Medical Center, Ann Arbor, MI (United States)

2011-11-15

Purpose: To assess the prognostic value of perineural invasion (PNI) for patients treated with dose-escalated external-beam radiation therapy for prostate cancer. Methods and Materials: Outcomes were analyzed for 651 men treated for prostate cancer with EBRT to a minimum dose {>=}75 Gy. We assessed the impact of PNI as well as pretreatment and treatment-related factors on freedom from biochemical failure (FFBF), freedom from metastasis (FFM), cause-specific survival (CSS), and overall survival. Results: PNI was present in 34% of specimens at biopsy and was significantly associated with higher Gleason score (GS), T stage, and prostate-specific antigen level. On univariate and multivariate analysis, the presence of PNI was associated with worse FFBF (hazard ratio = 1.7, p <0.006), FFM (hazard ratio = 1.8, p <0.03), and CSS (HR = 1.4, p <0.05) compared with absence of PNI; there was no difference in overall survival. Seven-year rates of FFBF, FFM, and CCS were 64% vs. 80%, 84% vs. 92%, and 91% vs. 95% for those patients with and without PNI, respectively. On recursive partitioning analysis, PNI predicted for worse FFM and CSS in patients with GS 8-10, with FFM of 67% vs. 89% (p <0.02), and CSS of 69% vs. 91%, (p <0.04) at 7 years for those with and without PNI, respectively. Conclusions: The presence of PNI in the prostate biopsy predicts worse clinical outcome for patients treated with dose-escalated external-beam radiation therapy. Particularly in patients with GS 8-10 disease, the presence of PNI suggests an increased risk of metastasis and prostate cancer death.
Sexual quality of life, body image distress, and psychosocial outcomes in colorectal cancer: a longitudinal study.

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Reese, Jennifer Barsky; Handorf, Elizabeth; Haythornthwaite, Jennifer A

2018-04-20

The objectives were to assess changes in sexual QOL and body image distress over time and to examine longitudinal associations between sexual QOL and body image variables with psychosocial outcomes in a sample of colorectal cancer patients. Participants (N = 141) completed a mail-based survey assessing sexual QOL [sexual distress (ISS), treatment impact on sexual function (SFQ), sexual function (FSFI; IIEF)], body image distress (BIS), and psychosocial outcomes [relationship quality (DAS-4), depressive symptoms (CESD-SF), and health-related QOL (HRQOL; FACT-C)]; 88 patients completed 6-month follow-up surveys (62%). Gender and cancer subgroups (male vs. female; rectal vs. colon cancer) were compared and longitudinal models examined associations between sexual QOL and body image variables with psychosocial outcomes over time and by subgroup. Impairments in sexual QOL and body image distress were common. Women and patients with rectal cancer reported worse body image distress compared to men (p = .005) and those with colon cancer (p = .03), respectively; compared to patients with colon cancer, those with rectal cancer reported worse treatment impact (p image distress decreased (p = .02), while sexual QOL was stable (e.g., 58% classified as dysfunctional at both time points, p = .13). For most sexual and body image predictors, worse impairment was associated with worse psychosocial outcomes over time. Several significant gender and cancer subgroup effects were found. Sexual QOL and body image are compromised after colorectal cancer and tend to remain impaired if unaddressed. Sexual concerns should be addressed early to limit broader-reaching psychosocial effects.
Predicting the severity and prognosis of trismus after intensity-modulated radiation therapy for oral cancer patients by magnetic resonance imaging.

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Li-Chun Hsieh

Full Text Available To develop magnetic resonance imaging (MRI indicators to predict trismus outcome for post-operative oral cavity cancer patients who received adjuvant intensity-modulated radiation therapy (IMRT, 22 patients with oral cancer treated with IMRT were studied over a two-year period. Signal abnormality scores (SA scores were computed from Likert-type ratings of the abnormalities of nine masticator structures and compared with the Mann-Whitney U-test and Kruskal-Wallis one-way ANOVA test between groups. Seventeen patients (77.3% experienced different degrees of trismus during the two-year follow-up period. The SA score correlated with the trismus grade (r = 0.52, p<0.005. Patients having progressive trismus had higher mean doses of radiation to multiple structures, including the masticator and lateral pterygoid muscles, and the parotid gland (p<0.05. In addition, this group also had higher SA-masticator muscle dose product at 6 months and SA scores at 12 months (p<0.05. At the optimum cut-off points of 0.38 for the propensity score, the sensitivity was 100% and the specificity was 93% for predicting the prognosis of the trismus patients. The SA score, as determined using MRI, can reflect the radiation injury and correlate to trismus severity. Together with the radiation dose, it could serve as a useful biomarker to predict the outcome and guide the management of trismus following radiation therapy.
In situ immune response after neoadjuvant chemotherapy for breast cancer predicts survival.

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Ladoire, Sylvain; Mignot, Grégoire; Dabakuyo, Sandrine; Arnould, Laurent; Apetoh, Lionel; Rébé, Cedric; Coudert, Bruno; Martin, Francois; Bizollon, Marie Hélène; Vanoli, André; Coutant, Charles; Fumoleau, Pierre; Bonnetain, Franck; Ghiringhelli, François

2011-07-01

Accumulating preclinical evidence suggests that anticancer immune responses contribute to the success of chemotherapy. However, the predictive value of tumour-infiltrating lymphocytes after neoadjuvant chemotherapy for breast cancer remains unknown. We hypothesized that the nature of the immune infiltrate following neoadjuvant chemotherapy would predict patient survival. In a series of 111 consecutive HER2- and a series of 51 non-HER2-overexpressing breast cancer patients treated by neoadjuvant chemotherapy, we studied by immunohistochemistry tumour infiltration by FOXP3 and CD8 T lymphocytes before and after chemotherapy. Kaplan-Meier analysis and Cox modelling were used to assess relapse-free survival (RFS) and overall survival (OS). A predictive scoring system using American Joint Committee on Cancer (AJCC) pathological staging and immunological markers was created. Association of high CD8 and low FOXP3 cell infiltrates after chemotherapy was significantly associated with improved RFS (p = 0.02) and OS (p = 0.002), and outperformed classical predictive factors in multivariate analysis. A combined score associating CD8/FOXP3 ratio and pathological AJCC staging isolated a subgroup of patients with a long-term overall survival of 100%. Importantly, this score also identified patients with a favourable prognosis in an independent cohort of HER2-negative breast cancer patients. These results suggest that immunological CD8 and FOXP3 cell infiltrate after treatment is an independent predictive factor of survival in breast cancer patients treated with neoadjuvant chemotherapy and provides new insights into the role of the immune milieu and cancer. Copyright © 2011 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
NTP Monograph: Developmental Effects and Pregnancy Outcomes Associated With Cancer Chemotherapy Use During Pregnancy.

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2013-05-01

The National Toxicology Program (NTP) Office of Health Assessment and Translation (OHAT) conducted an evaluation of the developmental effects and pregnancy outcomes associated with cancer chemotherapy use during pregnancy in humans. The final NTP monograph was completed in May 2013 (available at http:// ntp.niehs.nih.gov/go/36495). The incidence of cancer during pregnancy has been reported to occur from 17 to 100 per 100,000 pregnant women. Chemotherapy is a common treatment for cancer; however, most chemotherapy agents are classified as known or suspected human teratogens. Cancer chemotherapy use during pregnancy was selected for evaluation by the NTP because of the: (1) paucity of comprehensive reviews on the pregnancy outcomes following cancer chemotherapy use during pregnancy in humans, including the integration of the developmental animal toxicology literature with the observational studies in humans, and (2) growing public interest in the developmental effects of chemotherapy on offspring exposed to cancer chemotherapy during gestation due to the expected incidence of cancer diagnosed during pregnancy as women delay pregnancy to later ages. Of the approximately 110 cancer chemotherapeutic agents currently in use, the NTP monograph includes data on 56 agents used during 1,261 pregnancies for which pregnancy outcomes were documented. Overall, the NTP evaluation found that treatment with chemotherapy for cancer appeared to be associated with: (1) a higher rate of major malformations following exposure during the first trimester compared to exposure in the second and/or third trimester; (2) an increase the rate of stillbirth following exposure in the second and/ or third trimester; abnormally low levels of amniotic fluid (primarily attributable to Trastuzumab); and (3), also data are insufficient, impaired fetal growth and myelosuppression. Treatment with chemotherapy for cancer during pregnancy did not appear to increase spontaneous preterm birth, or impair
The Prognostic Nutritional Index Predicts Survival and Identifies Aggressiveness of Gastric Cancer.

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Eo, Wan Kyu; Chang, Hye Jung; Suh, Jungho; Ahn, Jin; Shin, Jeong; Hur, Joon-Young; Kim, Gou Young; Lee, Sookyung; Park, Sora; Lee, Sanghun

2015-01-01

Nutritional status has been associated with long-term outcomes in cancer patients. The prognostic nutritional index (PNI) is calculated by serum albumin concentration and absolute lymphocyte count, and it may be a surrogate biomarker for nutritional status and possibly predicts overall survival (OS) of gastric cancer. We evaluated the value of the PNI as a predictor for disease-free survival (DFS) in addition to OS in a cohort of 314 gastric cancer patients who underwent curative surgical resection. There were 77 patients in PNI-low group (PNI ≤ 47.3) and 237 patients in PNI-high group (PNI > 47.3). With a median follow-up of 36.5 mo, 5-yr DFS rates in PNI-low group and PNI-high group were 63.5% and 83.6% and 5-yr OS rates in PNI-low group and PNI-high group were 63.5% and 88.4%, respectively (DFS, P < 0.0001; OS, P < 0.0001). In the multivariate analysis, the only predictors for DFS were PNI, tumor-node-metastasis (TNM) stage, and perineural invasion, whereas the only predictors for OS were PNI, age, TNM stage, and perineural invasion. In addition, the PNI was independent of various inflammatory markers. In conclusion, the PNI is an independent prognostic factor for both DFS and OS, and provides additional prognostic information beyond pathologic parameters.
Prediction of cognitive outcome based on the progression of auditory discrimination during coma.

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Juan, Elsa; De Lucia, Marzia; Tzovara, Athina; Beaud, Valérie; Oddo, Mauro; Clarke, Stephanie; Rossetti, Andrea O

2016-09-01

To date, no clinical test is able to predict cognitive and functional outcome of cardiac arrest survivors. Improvement of auditory discrimination in acute coma indicates survival with high specificity. Whether the degree of this improvement is indicative of recovery remains unknown. Here we investigated if progression of auditory discrimination can predict cognitive and functional outcome. We prospectively recorded electroencephalography responses to auditory stimuli of post-anoxic comatose patients on the first and second day after admission. For each recording, auditory discrimination was quantified and its evolution over the two recordings was used to classify survivors as "predicted" when it increased vs. "other" if not. Cognitive functions were tested on awakening and functional outcome was assessed at 3 months using the Cerebral Performance Categories (CPC) scale. Thirty-two patients were included, 14 "predicted survivors" and 18 "other survivors". "Predicted survivors" were more likely to recover basic cognitive functions shortly after awakening (ability to follow a standardized neuropsychological battery: 86% vs. 44%; p=0.03 (Fisher)) and to show a very good functional outcome at 3 months (CPC 1: 86% vs. 33%; p=0.004 (Fisher)). Moreover, progression of auditory discrimination during coma was strongly correlated with cognitive performance on awakening (phonemic verbal fluency: rs=0.48; p=0.009 (Spearman)). Progression of auditory discrimination during coma provides early indication of future recovery of cognitive functions. The degree of improvement is informative of the degree of functional impairment. If confirmed in a larger cohort, this test would be the first to predict detailed outcome at the single-patient level. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Pre-delivery fibrinogen predicts adverse maternal or neonatal outcomes in patients with placental abruption.

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Wang, Liangcheng; Matsunaga, Shigetaka; Mikami, Yukiko; Takai, Yasushi; Terui, Katsuo; Seki, Hiroyuki

2016-07-01

Placental abruption is a severe obstetric complication of pregnancy that can cause disseminated intravascular coagulation and progress to massive post-partum hemorrhage. Coagulation disorder due to extreme consumption of fibrinogen is considered the main pathogenesis of disseminated intravascular coagulation in patients with placental abruption. The present study sought to determine if the pre-delivery fibrinogen level could predict adverse maternal or neonatal outcomes in patients with placental abruption. This retrospective medical chart review was conducted in a center for maternal, fetal, and neonatal medicine in Japan with 61 patients with placental abruption. Fibrinogen levels prior to delivery were collected and evaluated for the prediction of maternal and neonatal outcomes. The main outcome measures for maternal outcomes were disseminated intravascular coagulation and hemorrhage, and the main outcome measures for neonatal outcomes were Apgar score at 5 min, umbilical artery pH, and stillbirth. The receiver-operator curve and multivariate logistic regression analyses indicated that fibrinogen significantly predicted overt disseminated intravascular coagulation and the requirement of ≥6 red blood cell units, ≥10 fresh frozen plasma units, and ≥20 fresh frozen plasma units for transfusion. Moderate hemorrhage occurred in 71.5% of patients with a decrease in fibrinogen levels to 155 mg/dL. Fibrinogen could also predict neonatal outcomes. Umbilical artery pH neonatal outcomes with placental abruption. © 2016 Japan Society of Obstetrics and Gynecology. © 2016 Japan Society of Obstetrics and Gynecology.
Socio-economic Status Plays Important Roles in Childhood Cancer Treatment Outcome in Indonesia

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Mostert, S.; Gunawan, S.; Wolters, E.; van de Ven, P.M.; Sitaresmi, M.N.; van Dongen, J.; Veerman, A.J.P.; Mantik, M.F.J.; Kaspers, G.J.L.

2012-01-01

Background: The influence of parental socio-economic status on childhood cancer treatment outcome in low-income countries has not been sufficiently investigated. Our study examined this influence and explored parental experiences during cancer treatment of their children in an Indonesian academic
The platelet-to-lymphocyte ratio as a predictor of patient outcomes in ovarian cancer: a meta-analysis.

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Ma, X-M; Sun, X; Yang, G-W; Yu, M-W; Zhang, G-L; Yu, J; Zhang, Y; Wang, X-M

2017-10-01

The platelet-to-lymphocyte ratio (PLR) is a predictive clinical biomarker for different cancers. However, the results of several studies investigating the association between the PLR and the prognosis of ovarian cancer have been inconclusive. Therefore, there is a need to conduct a meta-analysis to estimate the prognostic value of the PLR in ovarian cancer. We searched the EMBASE, Medline, PubMed, and Web of Science databases to identify clinical studies that had evaluated the association between the PLR and ovarian cancer prognosis. Outcomes evaluated included overall survival (OS) and progression-free survival (PFS). We also analyzed PLR differences between malignant ovarian masses and the controls. Twelve relevant studies that comprised 2340 patients were selected for the meta-analysis. The results revealed that elevated PLR was significantly associated with poor OS (hazard ratio (HR) 1.63, 95% confidence interval (CI) 1.05-2.56, p < 0.01) and PFS (HR 1.61, 95% CI 1.03-2.51, p < 0.01). The PLRs in malignant cases were higher than in controls (mean difference = 63.57, 95% CI 39.47-87.66, p < 0.00001). An elevated PLR is associated with poor prognosis in patients with ovarian cancer. The PLR could be employed as a prognostic marker in patients with ovarian cancer.

Older age impacts on survival outcome in patients receiving curative surgery for solid cancer

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Chang-Hsien Lu

2018-07-01

Full Text Available Summary: Background: Given the global increase in aging populations and cancer incidence, understanding the influence of age on postoperative outcome after cancer surgery is imperative. This study aimed to evaluate the impact of age on survival outcome in solid cancer patients receiving curative surgery. Methods: A total of 37,288 patients receiving curative surgeries for solid cancers between 2007 and 2012 at four affiliated Chang Gung Memorial Hospital were included in the study. All patients were categorized into age groups by decades for survival analysis. Results: The percentages of patient populations aged <40 years, 40–49 years, 50–59 years, 60–69 years, 70–79 years, and ≥80 years were 9.7%, 17.7%, 27.8%, 22.1%, 16.9%, and 5.7%, respectively. The median follow-up period was 38.9 months (range, 22.8–60.4 months and the overall, cancer-specific, and noncancer-specific mortality rates were 26.0%, 17.6%, and 8.5%, respectively. The overall mortality rate of patients in different age groups were 18.5%, 21.1%, 22.0%, 25.3%, 35.3%, and 49.0%, respectively. Compared to patients aged <40 years, more significant decrease in long-term survival were observed in aging patients. Multivariate analysis showed higher postoperative short-term mortality rates in patients older than 70 years, and the adjusted odds ratio of mortality risk ranged from 1.47 to 1.74 and 2.26 to 3.03 in patients aged 70–79 years and ≥80 years, respectively, compared to those aged <40 years. Conclusion: Aging was a negative prognostic factor of survival outcome in solid cancer patients receiving curative surgery. After adjustment of other clinicopathologic factors, the influence of age on survival outcome was less apparent in the elderly. Keywords: Age, Solid cancer, Surgical resection, Prognosis
Risk prediction model for colorectal cancer: National Health Insurance Corporation study, Korea.

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Aesun Shin

Full Text Available PURPOSE: Incidence and mortality rates of colorectal cancer have been rapidly increasing in Korea during last few decades. Development of risk prediction models for colorectal cancer in Korean men and women is urgently needed to enhance its prevention and early detection. METHODS: Gender specific five-year risk prediction models were developed for overall colorectal cancer, proximal colon cancer, distal colon cancer, colon cancer and rectal cancer. The model was developed using data from a population of 846,559 men and 479,449 women who participated in health examinations by the National Health Insurance Corporation. Examinees were 30-80 years old and free of cancer in the baseline years of 1996 and 1997. An independent population of 547,874 men and 415,875 women who participated in 1998 and 1999 examinations was used to validate the model. Model validation was done by evaluating its performance in terms of discrimination and calibration ability using the C-statistic and Hosmer-Lemeshow-type chi-square statistics. RESULTS: Age, body mass index, serum cholesterol, family history of cancer, and alcohol consumption were included in all models for men, whereas age, height, and meat intake frequency were included in all models for women. Models showed moderately good discrimination ability with C-statistics between 0.69 and 0.78. The C-statistics were generally higher in the models for men, whereas the calibration abilities were generally better in the models for women. CONCLUSIONS: Colorectal cancer risk prediction models were developed from large-scale, population-based data. Those models can be used for identifying high risk groups and developing preventive intervention strategies for colorectal cancer.
Outcome of esophageal cancer in the elderly - systematic review of the literature.

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Skorus, Urszula A; Kenig, Jakub

2017-12-01

As the population ages, the number of elderly patients with esophageal cancer increases. Esophageal cancer has a poor prognosis and is associated with decreased life quality. To review the literature about the outcome of esophageal cancer in patients over 65. Articles published between January 2006 and November 2016 in the PubMed/Medline and ResearchGate databases were reviewed. Nineteen retrospective studies were included. Six thousand seven hundred and twenty-nine patients over 65 were analyzed. Thirty-day mortality ranges from 3.2% to 8.1%. Overall 5-year survival rates range from 0% to 49.2%, and the median survival rate ranges from 9.6 to 108.2 months. The incidence of complications in the surgery group ranges from 27% to 69%. Chemoradiotherapy grade ≥ 3 toxicity was observed in 22-36% of patients. Chronological age seems to have little influence on outcome of esophageal cancer. Open esophagectomy seems to be the mainstay of treatment for patients with esophageal cancer, regardless of age. There is still high mortality and morbidity involved in this procedure. To reduce them, some less invasive methods are being trialed.
Cosmetic outcome and curative effect of radiotherapy for early breast cancer after conservative surgery

International Nuclear Information System (INIS)

Ma Changuo; Ma Yuanyuan; Zhao Shuhong; Wang Hong

2007-01-01

Objective: To study the cosmetic outcome and curative effect of 6 MV X-ray tangential field radiotherapy for early stage breast cancer after conservative surgery. Methods: The eligible criteria were single tumor ≤3 cm in diameter, surgical margin negative and lymph node negative. The exclusive criteria were inflammatory carcinoma or male breast cancer. After conservative surgery, 42 patients with stage 0, I or II breast cancer were treated with conventional radiotherapy with a total dose of 50 Gy to the whole breast and 10 Gy boost to the tumor bed. The efficacy and the cosmetic outcome of radiotherapy were evaluated every 3 months for the first 2 years and every 6 months after that and every 12 months after 5 years. Results: The follow up time was 19-90 months (median 56 months). Two patients died of metastasis after 16 months and 36 months, which was diagnosed by CT scan. Excellent or good cosmetic outcome was > 93% at 36 months. The local control rate was 100%. The 1- and 3-year survival rates was 100% and 98%, respectively. Conclusions: Tangential field radiotherapy for early breast cancer after conservative surgery has a satisfied result in both tumor control and cosmetic outcome, which can definitely improve the life quality of the patients. (authors)
BAX protein expression and clinical outcome in epithelial ovarian cancer.

Science.gov (United States)

Tai, Y T; Lee, S; Niloff, E; Weisman, C; Strobel, T; Cannistra, S A

1998-08-01

Expression of the pro-apoptotic protein BAX sensitizes ovarian cancer cell lines to paclitaxel in vitro by enhancing the pathway of programmed cell death. The present study was performed to determine the relationship between BAX expression and clinical outcome in 45 patients with newly diagnosed ovarian cancer. BAX protein expression was analyzed by immunohistochemistry, and its relationship with clinical outcome was determined. Assessment of BAX mRNA transcript levels and mutational analysis of the BAX coding region were also performed. BAX protein was expressed at high levels (defined as > or = 50% of tumor cells positive) in tumor tissue from 60% of newly diagnosed patients. All patients whose tumors expressed high levels of BAX achieved a complete response (CR) to first-line chemotherapy that contained paclitaxel plus a platinum analogue, compared with 57% of patients in the low-BAX group (P = .036). After a median follow-up of 1.9 years, the median disease-free survival (DFS) of patients in the high-BAX group has not been reached, compared with a median DFS of 1.1 years for low-BAX expressors (P = .0061). BAX retained independent prognostic significance in multivariate analysis when corrected for stage and histology. BAX mRNA transcripts were easily detected in samples with low BAX protein expression, and no BAX mutations were identified. The correlation between high BAX levels and improved clinical outcome suggests that an intact apoptotic pathway is an important determinant of chemoresponsiveness in ovarian cancer patients who receive paclitaxel.
Selecting the minimum prediction base of historical data to perform 5-year predictions of the cancer burden: The GoF-optimal method.

Science.gov (United States)

Valls, Joan; Castellà, Gerard; Dyba, Tadeusz; Clèries, Ramon

2015-06-01

Predicting the future burden of cancer is a key issue for health services planning, where a method for selecting the predictive model and the prediction base is a challenge. A method, named here Goodness-of-Fit optimal (GoF-optimal), is presented to determine the minimum prediction base of historical data to perform 5-year predictions of the number of new cancer cases or deaths. An empirical ex-post evaluation exercise for cancer mortality data in Spain and cancer incidence in Finland using simple linear and log-linear Poisson models was performed. Prediction bases were considered within the time periods 1951-2006 in Spain and 1975-2007 in Finland, and then predictions were made for 37 and 33 single years in these periods, respectively. The performance of three fixed different prediction bases (last 5, 10, and 20 years of historical data) was compared to that of the prediction base determined by the GoF-optimal method. The coverage (COV) of the 95% prediction interval and the discrepancy ratio (DR) were calculated to assess the success of the prediction. The results showed that (i) models using the prediction base selected through GoF-optimal method reached the highest COV and the lowest DR and (ii) the best alternative strategy to GoF-optimal was the one using the base of prediction of 5-years. The GoF-optimal approach can be used as a selection criterion in order to find an adequate base of prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.
National Cancer Patient Registry--a patient registry/clinical database to evaluate the health outcomes of patients undergoing treatment for cancers in Malaysia.

Science.gov (United States)

Lim, G C C; Azura, D

2008-09-01

Cancer burden in Malaysia is increasing. Although there have been improvements in cancer treatment, these new therapies may potentially cause an exponential increase in the cost of cancer treatment. Therefore, justification for the use of these treatments is mandated. Availability of local data will enable us to evaluate and compare the outcome of our patients. This will help to support our clinical decision making and local policy, improve access to treatment and improve the provision and delivery of oncology services in Malaysia. The National Cancer Patient Registry was proposed as a database for cancer patients who seek treatment in Malaysia. It will be a valuable tool to provide timely and robust data on the actual setting in oncology practice, safety and cost effectiveness of treatment and most importantly the outcome of these patients.
Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery.

Directory of Open Access Journals (Sweden)

Rubén Armañanzas

Full Text Available Epilepsy surgery is effective in reducing both the number and frequency of seizures, particularly in temporal lobe epilepsy (TLE. Nevertheless, a significant proportion of these patients continue suffering seizures after surgery. Here we used a machine learning approach to predict the outcome of epilepsy surgery based on supervised classification data mining taking into account not only the common clinical variables, but also pathological and neuropsychological evaluations. We have generated models capable of predicting whether a patient with TLE secondary to hippocampal sclerosis will fully recover from epilepsy or not. The machine learning analysis revealed that outcome could be predicted with an estimated accuracy of almost 90% using some clinical and neuropsychological features. Importantly, not all the features were needed to perform the prediction; some of them proved to be irrelevant to the prognosis. Personality style was found to be one of the key features to predict the outcome. Although we examined relatively few cases, findings were verified across all data, showing that the machine learning approach described in the present study may be a powerful method. Since neuropsychological assessment of epileptic patients is a standard protocol in the pre-surgical evaluation, we propose to include these specific psychological tests and machine learning tools to improve the selection of candidates for epilepsy surgery.
Predictive value of bcl-2 immunoreactivity in prostate cancer patients treated with radiotherapy

International Nuclear Information System (INIS)

Bylund, A.; Widmark, A.; Stattin, P.; Bergh, A.

1998-01-01

Background and purpose: Recent experimental evidence suggests that overexpression of bcl-2, a protein functioning by blocking apoptosis, may influence the treatment outcome in human tumours, including prostate cancer. To test the clinical implications of this hypothesis, tumours from patients with prostate cancer treated with external beam radiotherapy were investigated for bcl-2 immunoreactivity (IR) and correlated with prognosis and treatment outcome. Materials and methods: Bcl-2 IR was evaluated in archival tumour specimens obtained through transurethral resection from 42 patients with localized prostate cancer (T0-T4, N0 and M0). Bcl-2 IR expression was related to stage, grade and cancer-specific survival. Specimens were obtained prior to administrating routine radiotherapy for all patients. Results: Bcl-2 IR was present in 19/42 (45%) tumours. The bcl-2-positive patients had a significantly longer cancer-specific survival than the bcl-2-negative patients (10.3 versus 3.4 years, P<0.04). At follow-up (7-19 years), nine patients were still alive, 26 patients had died of prostate cancer and seven patients had died of other causes. Conclusions: This study indicates that pre-treatment bcl-2 overexpression is related to a favourable outcome in prostate cancer treated with radiotherapy. Low bcl-2 along with a high stage may be a predictor of poor prognosis and these patients might benefit from additional treatment. (Copyright (c) 1998 Elsevier Science B.V., Amsterdam. All rights reserved.)
Medical assessment of adverse health outcomes in long-term survivors of childhood cancer

NARCIS (Netherlands)

Geenen, Maud M.; Cardous-Ubbink, Mathilde C.; Kremer, Leontien C. M.; van den Bos, Cor; van der Pal, Helena J. H.; Heinen, Richard C.; Jaspers, Monique W. M.; Koning, Caro C. E.; Oldenburger, Foppe; Langeveld, Nelia E.; Hart, Augustinus A. M.; Bakker, Piet J. M.; Caron, Huib N.; van Leeuwen, Flora E.

2007-01-01

CONTEXT: Improved survival of children with cancer has been accompanied by multiple treatment-related complications. However, most studies in survivors of childhood cancer focused on only 1 late effect. OBJECTIVE: To assess the total burden of adverse health outcomes (clinical or subclinical
Body mass index and cholesterol level predict surgical outcome in patients with hepatocellular carcinoma in Taiwan - a cohort study.

Science.gov (United States)

Lee, Ya-Ling; Li, Wan-Chun; Tsai, Tung-Hu; Chiang, Hsin-Yu; Ting, Chin-Tsung

2016-04-19

Curative surgical resection (CSR) remains the most effective therapeutic intervention for patients with hepatocellular carcinoma (HCC); however, frequent post-surgical recurrence leads to high cancer related mortality. This study aimed to clarify the role of body mass index (BMI) and serum cholesterol level in predicting post-surgical outcomes in HCC patients after CSR. A total of 484 HCC patients including 213 BMIhigh and 271 BMIlow patients were included. Overall survival (OS) and recurrence-free survival (RFS) rates were examined in patients with differential BMI and serum cholesterol level. The analysis showed that significant different 1-, 3- and 5-year cumulative OS rates (P-value=0.015) and RFS rate (P-value=0.010) between BMIlow and BMIhigh patients. Further analysis in groups with differential serum cholesterol levels among BMIlow and BMIhigh patients indicated that the BMIlow/Chollow patients exhibited the significant lower cumulative OS and RFS rates in comparison with the remaining subjects (P-value=0.007 and 0.039 for OS and RFS rates, respectively). In conclusion, the coexistence of low BMI and low serum cholesterol level could serve as prognostic factors to predict post-operative outcomes in HCC patients undergoing surgical hepatectomy.
Comparative Risk Predictions of Second Cancers After Carbon-Ion Therapy Versus Proton Therapy

Energy Technology Data Exchange (ETDEWEB)

Eley, John G., E-mail: jeley@som.umaryland.edu [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); University of Texas Graduate School of Biomedical Sciences, Houston, Texas (United States); Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland (United States); Friedrich, Thomas [GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt (Germany); Homann, Kenneth L.; Howell, Rebecca M. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); University of Texas Graduate School of Biomedical Sciences, Houston, Texas (United States); Scholz, Michael; Durante, Marco [GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt (Germany); Newhauser, Wayne D. [Department of Physics and Astronomy, Louisiana State University and Agricultural and Mechanical College, Baton Rouge, Louisiana (United States); Mary Bird Perkins Cancer Center, Baton Rouge, Louisiana (United States)

2016-05-01

Purpose: This work proposes a theoretical framework that enables comparative risk predictions for second cancer incidence after particle beam therapy for different ion species for individual patients, accounting for differences in relative biological effectiveness (RBE) for the competing processes of tumor initiation and cell inactivation. Our working hypothesis was that use of carbon-ion therapy instead of proton therapy would show a difference in the predicted risk of second cancer incidence in the breast for a sample of Hodgkin lymphoma (HL) patients. Methods and Materials: We generated biologic treatment plans and calculated relative predicted risks of second cancer in the breast by using two proposed methods: a full model derived from the linear quadratic model and a simpler linear-no-threshold model. Results: For our reference calculation, we found the predicted risk of breast cancer incidence for carbon-ion plans-to-proton plan ratio, , to be 0.75 ± 0.07 but not significantly smaller than 1 (P=.180). Conclusions: Our findings suggest that second cancer risks are, on average, comparable between proton therapy and carbon-ion therapy.
Does Treatment Duration Affect Outcome After Radiotherapy for Prostate Cancer?

International Nuclear Information System (INIS)

D'Ambrosio, David J.; Li Tianyu; Horwitz, Eric M.; Chen, David Y.T.; Pollack, Alan; Buyyounouski, Mark K.

2008-01-01

Purpose: The protraction of external beam radiotherapy (RT) time is detrimental in several disease sites. In prostate cancer, the overall treatment time can be considerable, as can the potential for treatment breaks. We evaluated the effect of elapsed treatment time on outcome after RT for prostate cancer. Methods and Materials: Between April 1989 and November 2004, 1,796 men with prostate cancer were treated with RT alone. The nontreatment day ratio (NTDR) was defined as the number of nontreatment days divided by the total elapsed days of RT. This ratio was used to account for the relationship between treatment duration and total RT dose. Men were stratified into low risk (n = 789), intermediate risk (n = 798), and high risk (n = 209) using a single-factor model. Results: The 10-year freedom from biochemical failure (FFBF) rate was 68% for a NTDR <33% vs. 58% for NTDR ≥33% (p = 0.02; BF was defined as a prostate-specific antigen nadir + 2 ng/mL). In the low-risk group, the 10-year FFBF rate was 82% for NTDR <33% vs. 57% for NTDR ≥33% (p = 0.0019). The NTDR was independently predictive for FFBF (p = 0.03), in addition to T stage (p = 0.005) and initial prostate-specific antigen level (p < 0.0001) on multivariate analysis, including Gleason score and radiation dose. The NTDR was not a significant predictor of FFBF when examined in the intermediate-risk group, high-risk group, or all risk groups combined. Conclusions: A proportionally longer treatment duration was identified as an adverse factor in low-risk patients. Treatment breaks resulting in a NTDR of ≥33% (e.g., four or more breaks during a 40-fraction treatment, 5 d/wk) should be avoided
Patient-Reported Outcomes After Radiation Therapy in Men With Prostate Cancer: A Systematic Review of Prognostic Tool Accuracy and Validity

Energy Technology Data Exchange (ETDEWEB)

O' Callaghan, Michael E., E-mail: elspeth.raymond@health.sa.gov.au [South Australian Prostate Cancer Clinical Outcomes Collaborative (Australia); Freemasons Foundation Centre for Men' s Health, University of Adelaide (Australia); Urology Unit, Repatriation General Hospital, SA Health, Flinders Centre for Innovation in Cancer (Australia); Raymond, Elspeth [South Australian Prostate Cancer Clinical Outcomes Collaborative (Australia); Campbell, Jared M. [Joanna Briggs Institute, University of Adelaide (Australia); Vincent, Andrew D. [Freemasons Foundation Centre for Men' s Health, University of Adelaide (Australia); Beckmann, Kerri [South Australian Prostate Cancer Clinical Outcomes Collaborative (Australia); Centre for Population Health Research, University of South Australia (Australia); Roder, David [Centre for Population Health Research, University of South Australia (Australia); Evans, Sue; McNeil, John [Epidemiology and Preventative Medicine, Monash University (Australia); Millar, Jeremy [Radiation Oncology, Alfred Health (Australia); Zalcberg, John [Epidemiology and Preventative Medicine, Monash University (Australia); Borg, Martin [South Australian Prostate Cancer Clinical Outcomes Collaborative (Australia); Adelaide Radiotherapy Centre (Australia); Moretti, Kim [South Australian Prostate Cancer Clinical Outcomes Collaborative (Australia); Freemasons Foundation Centre for Men' s Health, University of Adelaide (Australia); Flinders Centre for Innovation in Cancer, Centre for Population Health Research, University of South Australia (Australia); Discipline of Surgery, University of Adelaide (Australia)

2017-06-01

Purpose: To identify, through a systematic review, all validated tools used for the prediction of patient-reported outcome measures (PROMs) in patients being treated with radiation therapy for prostate cancer, and provide a comparative summary of accuracy and generalizability. Methods and Materials: PubMed and EMBASE were searched from July 2007. Title/abstract screening, full text review, and critical appraisal were undertaken by 2 reviewers, whereas data extraction was performed by a single reviewer. Eligible articles had to provide a summary measure of accuracy and undertake internal or external validation. Tools were recommended for clinical implementation if they had been externally validated and found to have accuracy ≥70%. Results: The search strategy identified 3839 potential studies, of which 236 progressed to full text review and 22 were included. From these studies, 50 tools predicted gastrointestinal/rectal symptoms, 29 tools predicted genitourinary symptoms, 4 tools predicted erectile dysfunction, and no tools predicted quality of life. For patients treated with external beam radiation therapy, 3 tools could be recommended for the prediction of rectal toxicity, gastrointestinal toxicity, and erectile dysfunction. For patients treated with brachytherapy, 2 tools could be recommended for the prediction of urinary retention and erectile dysfunction. Conclusions: A large number of tools for the prediction of PROMs in prostate cancer patients treated with radiation therapy have been developed. Only a small minority are accurate and have been shown to be generalizable through external validation. This review provides an accessible catalogue of tools that are ready for clinical implementation as well as which should be prioritized for validation.
Nutritional Care of Gastric Cancer Patients with Clinical Outcomes and Complications: A Review

OpenAIRE

Choi, Wook Jin; Kim, Jeongseon

2016-01-01

The incidence and mortality of gastric cancer have been steadily decreased over the past few decades. However, gastric cancer is still one of the leading causes of cancer deaths across many regions of the world, particularly in Asian countries. In previous studies, nutrition has been considered one of significant risk factors in gastric cancer patients. Especially, malnourished patients are at greater risk of adverse clinical outcomes (e.g., longer hospital stay) and higher incidence of compl...
Preoperative MRI findings predict two-year postoperative clinical outcome in lumbar spinal stenosis.

Directory of Open Access Journals (Sweden)

Pekka Kuittinen

Full Text Available To study the predictive value of preoperative magnetic resonance imaging (MRI findings for the two-year postoperative clinical outcome in lumbar spinal stenosis (LSS.84 patients (mean age 63±11 years, male 43% with symptoms severe enough to indicate LSS surgery were included in this prospective observational single-center study. Preoperative MRI of the lumbar spine was performed with a 1.5-T unit. The imaging protocol conformed to the requirements of the American College of Radiology for the performance of MRI of the adult spine. Visual and quantitative assessment of MRI was performed by one experienced neuroradiologist. At the two-year postoperative follow-up, functional ability was assessed with the Oswestry Disability Index (ODI 0-100% and treadmill test (0-1000 m, pain symptoms with the overall Visual Analogue Scale (VAS 0-100 mm, and specific low back pain (LBP and specific leg pain (LP separately with a numeric rating scale from 0-10 (NRS-11. Satisfaction with the surgical outcome was also assessed.Preoperative severe central stenosis predicted postoperatively lower LP, LBP, and VAS when compared in patients with moderate central stenosis (p<0.05. Moreover, severe stenosis predicted higher postoperative satisfaction (p = 0.029. Preoperative scoliosis predicted an impaired outcome in the ODI (p = 0.031 and lowered the walking distance in the treadmill test (p = 0.001. The preoperative finding of only one stenotic level in visual assessment predicted less postoperative LBP when compared with patients having 2 or more stenotic levels (p = 0.026. No significant differences were detected between quantitative measurements and the patient outcome.Routine preoperative lumbar spine MRI can predict the patient outcome in a two-year follow up in patients with LSS surgery. Severe central stenosis and one-level central stenosis are predictors of good outcome. Preoperative finding of scoliosis may indicate worse functional ability.
Predicting survival in patients with metastatic kidney cancer by gene-expression profiling in the primary tumor.

Science.gov (United States)

Vasselli, James R; Shih, Joanna H; Iyengar, Shuba R; Maranchie, Jodi; Riss, Joseph; Worrell, Robert; Torres-Cabala, Carlos; Tabios, Ray; Mariotti, Andra; Stearman, Robert; Merino, Maria; Walther, McClellan M; Simon, Richard; Klausner, Richard D; Linehan, W Marston

2003-06-10

To identify potential molecular determinants of tumor biology and possible clinical outcomes, global gene-expression patterns were analyzed in the primary tumors of patients with metastatic renal cell cancer by using cDNA microarrays. We used grossly dissected tumor masses that included tumor, blood vessels, connective tissue, and infiltrating immune cells to obtain a gene-expression "profile" from each primary tumor. Two patterns of gene expression were found within this uniformly staged patient population, which correlated with a significant difference in overall survival between the two patient groups. Subsets of genes most significantly associated with survival were defined, and vascular cell adhesion molecule-1 (VCAM-1) was the gene most predictive for survival. Therefore, despite the complex biological nature of metastatic cancer, basic clinical behavior as defined by survival may be determined by the gene-expression patterns expressed within the compilation of primary gross tumor cells. We conclude that survival in patients with metastatic renal cell cancer can be correlated with the expression of various genes based solely on the expression profile in the primary kidney tumor.
Early prediction of outcome of activities of daily living after stroke: a systematic review

OpenAIRE

Veerbeek, J.M.; Kwakkel, G.; Wegen, van, E.E.H.; Ket, J.C.F.; Heijmans, M.W.

2011-01-01

BACKGROUND AND PURPOSE-Knowledge about robust and unbiased factors that predict outcome of activities of daily living (ADL) is paramount in stroke management. This review investigates the methodological quality of prognostic studies in the early poststroke phase for final ADL to identify variables that are predictive or not predictive for outcome of ADL after stroke. METHODS-PubMed, Ebsco/Cinahl and Embase were systematically searched for prognostic studies in which stroke patients were inclu...
Psychological and behavioural predictors of pain management outcomes in patients with cancer

DEFF Research Database (Denmark)

Jacobsen, Ramune; Møldrup, Claus; Christrup, Lona Louring

2010-01-01

To better understand the phenomenon of patient-related barriers to cancer pain management and address them more effectively in interventional studies, a theoretical model related to psychological aspects of pain experience and pain-related behaviours was elaborated. The aim of the study was to an......To better understand the phenomenon of patient-related barriers to cancer pain management and address them more effectively in interventional studies, a theoretical model related to psychological aspects of pain experience and pain-related behaviours was elaborated. The aim of the study...... was to analyse the impact of patient-related barriers on cancer pain management outcomes following this model. Thirty-three patients responded to the Brief Pain Inventory Pain scale, the Danish Barriers Questionnaire II (DBQ-II), the Hospital Anxiety and Depression scale (HADS), the Danish version of Patient...... was explained by patients' emotional distress (symptoms of anxiety and depression) and that pain relief was explained by cognitive barriers. In conclusion, interventions in emotional distress and patients' concerns may supposedly result in better cancer pain management outcomes....
Convergence of biomarkers, bioinformatics and nanotechnology for individualized cancer treatment

Science.gov (United States)

Phan, John H.; Moffitt, Richard A.; Stokes, Todd H.; Liu, Jian; Young, Andrew N.; Nie, Shuming; Wang, May D.

2013-01-01

Recent advances in biomarker discovery, biocomputing, and nanotechnology have raised new opportunities for the emerging field of personalized medicine in which disease detection, diagnosis, and therapy are tailored to each individual’s molecular profile, and also for predictive medicine that uses genetic/molecular information to predict disease development, progression, and clinical outcome. Here we discuss advanced biocomputing tools for cancer biomarker discovery and multiplexed nanoparticle probes for cancer biomarker profiling, together with prospects and challenges in correlating biomolecular signatures with clinical outcome. This bio-nano-info convergence holds great promise for molecular diagnosis and individualized therapy of cancer and other human diseases. PMID:19409634

Methodological Challenges in Examining the Impact of Healthcare Predictive Analytics on Nursing-Sensitive Patient Outcomes.

Science.gov (United States)

Jeffery, Alvin D

2015-06-01

The expansion of real-time analytic abilities within current electronic health records has led to innovations in predictive modeling and clinical decision support systems. However, the ability of these systems to influence patient outcomes is currently unknown. Even though nurses are the largest profession within the healthcare workforce, little research has been performed to explore the impact of clinical decision support on their decisions and the patient outcomes associated with them. A scoping literature review explored the impact clinical decision support systems containing healthcare predictive analytics have on four nursing-sensitive patient outcomes (pressure ulcers, failure to rescue, falls, and infections). While many articles discussed variable selection and predictive model development/validation, only four articles examined the impact on patient outcomes. The novelty of predictive analytics and the inherent methodological challenges in studying clinical decision support impact are likely responsible for this paucity of literature. Major methodological challenges include (1) multilevel nature of intervention, (2) treatment fidelity, and (3) adequacy of clinicians' subsequent behavior. There is currently insufficient evidence to demonstrate efficacy of healthcare predictive analytics-enhanced clinical decision support systems on nursing-sensitive patient outcomes. Innovative research methods and a greater emphasis on studying this phenomenon are needed.
Prostate Cancer Diagnosed After Repeat Biopsies Have a Favorable Pathological Outcome but Similar Recurrence Rate

Science.gov (United States)

Lopez-Corona, Ernesto; Ohori, Makoto; Wheeler, Thomas M.; Reuter, Victor E.; Scardino, Peter T.; Kattan, Michael W.; Eastham, James A.

2007-01-01

Purpose We investigated whether repeat prostate biopsies are associated with more favorable prognoses, less extensive disease or higher rates of IC in patients who are ultimately diagnosed with prostate cancer and treated with RRP. Materials and Methods We examined standard clinical and pathological data on 1,357 patients treated with RRP from 1983 to 2001. In addition, we noted the rate of IC in a subgroup of 847 patients in whom tumor volume was measured. Results Cancer was found in 1,042 patients (77%) at the first biopsy, in 227 (17%) at the second biopsy, in 59 (4%) at the third biopsy and in 29 (2%) at the fourth or later biopsy. Patients with 2 or greater biopsies had a higher rate of clinical T1c stage cancer and larger prostates than patients with only 1 biopsy (each p <0.0001). After RRP patients with 1 biopsy had a lower rate of organ confined tumors (61% vs 75%, p <0.0001), and a higher rate of extracapsular extension, seminal vesicle invasion, lymph node metastases and Gleason sum 7 or greater than other patients. IC was found in 10% of patients with 1 biopsy and 18% of those with 2 or greater biopsies (p = 0.018). Despite these more favorable pathological outcomes there was no difference in biochemical recurrence rate. Conclusions Although we found that a greater number of biopsies was related to a better pathological outcome after RRP, the number of biopsies did not predict disease recurrence. The increasing number of biopsies currently being performed, especially in patients with larger prostates, likely results in higher rates of IC. PMID:16469581
Postoperative Radiotherapy for Maxillary Sinus Cancer: Long-Term Outcomes and Toxicities of Treatment

International Nuclear Information System (INIS)

Bristol, Ian J.; Ahamad, Anesa; Garden, Adam S.; Morrison, William H.; Hanna, Ehab Y.; Papadimitrakopoulou, Vassiliki A.; Rosenthal, David I.; Ang, K. Kian

2007-01-01

Purpose: To determine the effects of three changes in radiotherapy technique on the outcomes for patients irradiated postoperatively for maxillary sinus cancer. Methods and Materials: The data of 146 patients treated between 1969 and 2002 were reviewed. The patients were separated into two groups according to the date of treatment. Group 1 included 90 patients treated before 1991 and Group 2 included 56 patients treated after 1991, when the three changes were implemented. The outcomes were compared between the two groups. Results: No differences were found in the 5-year overall survival, recurrence-free survival, local control, nodal control, or distant metastasis rates between the two groups (51% vs. 62%, 51% vs. 57%, 76% vs. 70%, 82% vs. 83%, and 28% vs. 17% for Groups 1 and 2, respectively). The three changes were to increase the portals to cover the base of the skull in patients with perineural invasion, reducing their risk of local recurrence; the addition of elective neck irradiation in patients with squamous or undifferentiated histologic features, improving the nodal control, distant metastasis, and recurrence-free survival rates (64% vs. 93%, 20% vs. 3%, and 45% vs. 67%, respectively; p < 0.05 for all comparisons); and improving the dose distributions within the target volume, reducing the late Grade 3-4 complication rates (34% in Group 1 vs. 8% in Group 2, p = 0.014). Multivariate analysis revealed advancing age, the need for enucleation, and positive margins as independent predictors of worse overall survival. The need for enucleation also predicted for worse local control. Conclusion: The three changes in radiotherapy technique improved the outcomes for select patients as predicted. Despite these changes, little demonstrable overall improvement occurred in local control or survival for these patients and additional work must be done
Cyclophilin B Expression Is Associated with In Vitro Radioresistance and Clinical Outcome after Radiotherapy

Directory of Open Access Journals (Sweden)

Paul D. Williams

2011-12-01

Full Text Available The tools for predicting clinical outcome after radiotherapy are not yet optimal. To improve on this, we applied the COXEN informatics approach to in vitro radiation sensitivity data of transcriptionally profiled human cells and gene expression data from untreated head and neck squamous cell carcinoma (HNSCC and bladder tumors to generate a multigene predictive model that is independent of histologic findings and reports on tumor radiosensitivity. The predictive ability of this 41-gene model was evaluated in patients with HNSCC and was found to stratify clinical outcome after radiotherapy. In contrast, this model was not useful in stratifying similar patients not treated with radiation. This led us to hypothesize that expression of some of the 41 genes contributes to tumor radioresistance and clinical recurrence. Hence, we evaluated the expression the 41 genes as a function of in vitro radioresistance in the NCI-60 cancer cell line panel and found cyclophilin B (PPIB, a peptidylprolyl isomerase and target of cyclosporine A (CsA, had the strongest direct correlation. Functional inhibition of PPIB by small interfering RNA depletion or CsA treatment leads to radiosensitization in cancer cells and reduced cellular DNA repair. Immunohistochemical evaluation of PPIB expression in patients with HNSCC was found to be associated with outcome after radiotherapy. This work demonstrates that a novel 41-gene expression model of radiation sensitivity developed in bladder cancer cell lines and human skin fibroblasts predicts clinical outcome after radiotherapy in head and neck cancer patients and identifies PPIB as a potential target for clinical radiosensitization.
Noninvasive work of breathing improves prediction of post-extubation outcome.

Science.gov (United States)

Banner, Michael J; Euliano, Neil R; Martin, A Daniel; Al-Rawas, Nawar; Layon, A Joseph; Gabrielli, Andrea

2012-02-01

We hypothesized that non-invasively determined work of breathing per minute (WOB(N)/min) (esophageal balloon not required) may be useful for predicting extubation outcome, i.e., appropriate work of breathing values may be associated with extubation success, while inappropriately increased values may be associated with failure. Adult candidates for extubation were divided into a training set (n = 38) to determine threshold values of indices for assessing extubation and a prospective validation set (n = 59) to determine the predictive power of the threshold values for patients successfully extubated and those who failed extubation. All were evaluated for extubation during a spontaneous breathing trial (5 cmH(2)O pressure support ventilation, 5 cmH(2)O positive end expiratory pressure) using routine clinical practice standards. WOB(N)/min data were blinded to attending physicians. Area under the receiver operating characteristic curves (AUC), sensitivity, specificity, and positive and negative predictive values of all extubation indices were determined. AUC for WOB(N)/min was 0.96 and significantly greater (p indices. WOB(N)/min had a specificity of 0.83, the highest sensitivity at 0.96, positive predictive value at 0.84, and negative predictive value at 0.96 compared to all indices. For 95% of those successfully extubated, WOB(N)/min was ≤10 J/min. WOB(N)/min had the greatest overall predictive accuracy for extubation compared to traditional indices. WOB(N)/min warrants consideration for use in a complementary manner with spontaneous breathing pattern data for predicting extubation outcome.
Prediction modelling for trauma using comorbidity and 'true' 30-day outcome.

Science.gov (United States)

Bouamra, Omar; Jacques, Richard; Edwards, Antoinette; Yates, David W; Lawrence, Thomas; Jenks, Tom; Woodford, Maralyn; Lecky, Fiona

2015-12-01

Prediction models for trauma outcome routinely control for age but there is uncertainty about the need to control for comorbidity and whether the two interact. This paper describes recent revisions to the Trauma Audit and Research Network (TARN) risk adjustment model designed to take account of age and comorbidities. In addition linkage between TARN and the Office of National Statistics (ONS) database allows patient's outcome to be accurately identified up to 30 days after injury. Outcome at discharge within 30 days was previously used. Prospectively collected data between 2010 and 2013 from the TARN database were analysed. The data for modelling consisted of 129 786 hospital trauma admissions. Three models were compared using the area under the receiver operating curve (AuROC) for assessing the ability of the models to predict outcome, the Akaike information criteria to measure the quality between models and test for goodness-of-fit and calibration. Model 1 is the current TARN model, Model 2 is Model 1 augmented by a modified Charlson comorbidity index and Model 3 is Model 2 with ONS data on 30 day outcome. The values of the AuROC curve for Model 1 were 0.896 (95% CI 0.893 to 0.899), for Model 2 were 0.904 (0.900 to 0.907) and for Model 3 0.897 (0.896 to 0.902). No significant interaction was found between age and comorbidity in Model 2 or in Model 3. The new model includes comorbidity and this has improved outcome prediction. There was no interaction between age and comorbidity, suggesting that both independently increase vulnerability to mortality after injury. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Updating risk prediction tools: a case study in prostate cancer.

Science.gov (United States)

Ankerst, Donna P; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J; Feng, Ziding; Sanda, Martin G; Partin, Alan W; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M

2012-01-01

Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically, the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [-2]proPSA measured on an external case-control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
An etiologic prediction model incorporating biomarkers to predict the bladder cancer risk associated with occupational exposure to aromatic amines: a pilot study

OpenAIRE

Mastrangelo, Giuseppe; Carta, Angela; Arici, Cecilia; Pavanello, Sofia; Porru, Stefano

2017-01-01

Background No etiological prediction model incorporating biomarkers is available to predict bladder cancer risk associated with occupational exposure to aromatic amines. Methods Cases were 199 bladder cancer patients. Clinical, laboratory and genetic data were predictors in logistic regression models (full and short) in which the dependent variable was 1 for 15 patients with aromatic amines related bladder cancer and 0 otherwise. The receiver operating characteristics approach was adopted; th...
Short- and long-term outcomes of laparoscopic surgery vs open surgery for transverse colon cancer: a retrospective multicenter study.

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Kim, Jong Wan; Kim, Jeong Yeon; Kang, Byung Mo; Lee, Bong Hwa; Kim, Byung Chun; Park, Jun Ho

2016-01-01

The purpose of the present study was to compare the perioperative and oncologic outcomes between laparoscopic surgery and open surgery for transverse colon cancer. We conducted a retrospective review of patients who underwent surgery for transverse colon cancer at six Hallym University-affiliated hospitals between January 2005 and June 2015. The perioperative outcomes and oncologic outcomes were compared between laparoscopic and open surgery. Of 226 patients with transverse colon cancer, 103 underwent laparoscopic surgery and 123 underwent open surgery. There were no differences in the patient characteristics between the two groups. Regarding perioperative outcomes, the operation time was significantly longer in the laparoscopic group than in the open group (267.3 vs 172.7 minutes, Pstudy showed that laparoscopic surgery is associated with several perioperative benefits and similar oncologic outcomes to open surgery for the resection of transverse colon cancer. Therefore, laparoscopic surgery offers a safe alternative to open surgery in patients with transverse colon cancer.
A proposal for a comprehensive risk scoring system for predicting postoperative complications in octogenarian patients with medically operable lung cancer: JACS1303.

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Saji, Hisashi; Ueno, Takahiko; Nakamura, Hiroshige; Okumura, Norihito; Tsuchida, Masanori; Sonobe, Makoto; Miyazaki, Takuro; Aokage, Keiju; Nakao, Masayuki; Haruki, Tomohiro; Ito, Hiroyuki; Kataoka, Kazuhiko; Okabe, Kazunori; Tomizawa, Kenji; Yoshimoto, Kentaro; Horio, Hirotoshi; Sugio, Kenji; Ode, Yasuhisa; Takao, Motoshi; Okada, Morihito; Chida, Masayuki

2018-04-01

Although some retrospective studies have reported clinicopathological scoring systems for predicting postoperative complications and survival outcomes for elderly lung cancer patients, optimized scoring systems remain controversial. The Japanese Association for Chest Surgery (JACS) conducted a nationwide multicentre prospective cohort and enrolled a total of 1019 octogenarians with medically operable lung cancer. Details of the clinical factors, comorbidities and comprehensive geriatric assessment were recorded for 895 patients to develop a comprehensive risk scoring (RS) system capable of predicting severe complications. Operative (30 days) and hospital mortality rates were 1.0% and 1.6%, respectively. Complications were observed in 308 (34%) patients, of whom 81 (8.4%) had Grade 3-4 severe complications. Pneumonia was the most common severe complication, observed in 27 (3.0%) patients. Five predictive factors, gender, comprehensive geriatric assessment75: memory and Simplified Comorbidity Score (SCS): diabetes mellitus, albumin and percentage vital capacity, were identified as independent predictive factors for severe postoperative complications (odds ratio = 2.73, 1.86, 1.54, 1.66 and 1.61, respectively) through univariate and multivariate analyses. A 5-fold cross-validation was performed as an internal validation to reconfirm these 5 predictive factors (average area under the curve 0.70). We developed a simplified RS system as follows: RS = 3 (gender: male) + 2 (comprehensive geriatric assessment 75: memory: yes) + 2 (albumin: <3.8 ng/ml) + 1 (percentage vital capacity: ≤90) + 1 (SCS: diabetes mellitus: yes). The current series shows that octogenarians can be successfully treated for lung cancer with surgical resection with an acceptable rate of severe complications and mortality. We propose a simplified RS system to predict severe complications in octogenarian patients with medically operative lung cancer. JACS1303 (UMIN000016756).
Combining Spot Sign and Intracerebral Hemorrhage Score to Estimate Functional Outcome: Analysis From the PREDICT Cohort.

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Schneider, Hauke; Huynh, Thien J; Demchuk, Andrew M; Dowlatshahi, Dar; Rodriguez-Luna, David; Silva, Yolanda; Aviv, Richard; Dzialowski, Imanuel

2018-06-01

The intracerebral hemorrhage (ICH) score is the most commonly used grading scale for stratifying functional outcome in patients with acute ICH. We sought to determine whether a combination of the ICH score and the computed tomographic angiography spot sign may improve outcome prediction in the cohort of a prospective multicenter hemorrhage trial. Prospectively collected data from 241 patients from the observational PREDICT study (Prediction of Hematoma Growth and Outcome in Patients With Intracerebral Hemorrhage Using the CT-Angiography Spot Sign) were analyzed. Functional outcome at 3 months was dichotomized using the modified Rankin Scale (0-3 versus 4-6). Performance of (1) the ICH score and (2) the spot sign ICH score-a scoring scale combining ICH score and spot sign number-was tested. Multivariable analysis demonstrated that ICH score (odds ratio, 3.2; 95% confidence interval, 2.2-4.8) and spot sign number (n=1: odds ratio, 2.7; 95% confidence interval, 1.1-7.4; n>1: odds ratio, 3.8; 95% confidence interval, 1.2-17.1) were independently predictive of functional outcome at 3 months with similar odds ratios. Prediction of functional outcome was not significantly different using the spot sign ICH score compared with the ICH score alone (spot sign ICH score area under curve versus ICH score area under curve: P =0.14). In the PREDICT cohort, a prognostic score adding the computed tomographic angiography-based spot sign to the established ICH score did not improve functional outcome prediction compared with the ICH score. © 2018 American Heart Association, Inc.
Integrated genomic analyses identify KDM1A's role in cell proliferation via modulating E2F signaling activity and associate with poor clinical outcome in oral cancer.

Science.gov (United States)

Narayanan, Sathiya Pandi; Singh, Smriti; Gupta, Amit; Yadav, Sandhya; Singh, Shree Ram; Shukla, Sanjeev

2015-10-28

The histone demethylase KDM1A specifically demethylates lysine residues and its deregulation has been implicated in the initiation and progression of various cancers. However, KDM1A's molecular role and its pathological consequences, and prognostic significance in oral cancer remain less understood. In the present study, we sought to investigate the expression of KDM1A and its downstream role in oral cancer pathogenesis. By comparing mRNA expression profiles, we identified an elevated KDM1A expression in oral tumors when compared to normal oral tissues. In silico pathway prediction identified the association between KDM1A and E2F1 signaling in oral cancer. Pathway scanning, functional annotation analysis and In vitro assays showed the KDM1A's involvement in oral cancer cell proliferation and the cell cycle. Moreover, real time PCR and luciferase assays confirmed KDM1A's role in regulation of E2F1 signaling activity in oral cancer. Elevated KDM1A expression is associated with poor clinical outcome in oral cancer. Our data indicate that deregulated KDM1A expression is positively associated with proliferative phenotype of oral cancer and confers poor clinical outcome. These cumulative data suggest that KDM1A might be a potential diagnostic and therapeutic target for oral cancer. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Intact Mre11/Rad50/Nbs1 Complex Predicts Good Response to Radiotherapy in Early Breast Cancer

International Nuclear Information System (INIS)

Soederlund, Karin; Stal, Olle; Skoog, Lambert; Rutqvist, Lars Erik; Nordenskjoeld, Bo; Askmalm, Marie Stenmark

2007-01-01

Purpose: To investigate the expression and predictive role of the Mre11/Rad50/Nbs1 (MRN) complex and the ataxia-telangiectasia mutated protein (ATM) for the outcome of radiotherapy in breast cancer patients. Methods and Materials: The protein expression of ATM and the DNA repair proteins in the MRN complex were investigated using immunohistochemistry in tumors from 224 women with early breast cancer, who were randomized to receive postoperative radiotherapy or adjuvant chemotherapy. Results: Compared with normal breast tissue, the staining intensity of Mre11, Rad50, Nbs1, and ATM was reduced in a majority of the tumors. Weak expression of the MRN complex was correlated with high histologic grade and estrogen receptor negativity (p = 0.01 and p 0.0001, respectively). Radiotherapy significantly reduced the risk of local recurrence as compared with chemotherapy (p = 0.04). The greatest benefit of radiotherapy was seen in patients with moderate/strong expression of the MRN complex (relative risk = 0.27, 95% confidence interval = 0.098-0.72, p 0.009), whereas patients with negative/weak MRN expression had no benefit of radiotherapy compared with adjuvant chemotherapy. These results suggest that an intact MRN complex is important for the tumor cell eradicating effect of radiotherapy. Conclusions: Reduced expression of the MRN complex predicts a poor effect of radiotherapy in patients with early breast cancer
Epigenetic Biomarkers of Breast Cancer Risk: Across the Breast Cancer Prevention Continuum.

Science.gov (United States)

Terry, Mary Beth; McDonald, Jasmine A; Wu, Hui Chen; Eng, Sybil; Santella, Regina M

2016-01-01

Epigenetic biomarkers, such as DNA methylation, can increase cancer risk through altering gene expression. The Cancer Genome Atlas (TCGA) Network has demonstrated breast cancer-specific DNA methylation signatures. DNA methylation signatures measured at the time of diagnosis may prove important for treatment options and in predicting disease-free and overall survival (tertiary prevention). DNA methylation measurement in cell free DNA may also be useful in improving early detection by measuring tumor DNA released into the blood (secondary prevention). Most evidence evaluating the use of DNA methylation markers in tertiary and secondary prevention efforts for breast cancer comes from studies that are cross-sectional or retrospective with limited corresponding epidemiologic data, raising concerns about temporality. Few prospective studies exist that are large enough to address whether DNA methylation markers add to the prediction of tertiary and secondary outcomes over and beyond standard clinical measures. Determining the role of epigenetic biomarkers in primary prevention can help in identifying modifiable pathways for targeting interventions and reducing disease incidence. The potential is great for DNA methylation markers to improve cancer outcomes across the prevention continuum. Large, prospective epidemiological studies will provide essential evidence of the overall utility of adding these markers to primary prevention efforts, screening, and clinical care.
Writing Abilities Longitudinally Predict Academic Outcomes of Adolescents with ADHD

Science.gov (United States)

Molitor, Stephen J.; Langberg, Joshuah M.; Bourchtein, Elizaveta; Eddy, Laura D.; Dvorsky, Melissa R.; Evans, Steven W.

2016-01-01

Students with ADHD often experience a host of negative academic outcomes and deficits in reading and mathematics abilities contribute to these academic impairments. Students with ADHD may also have difficulties with written expression but there has been minimal research in this area and it is not clear whether written expression abilities uniquely contribute to the academic functioning of students with ADHD. The current study included a sample of 104 middle school students diagnosed with ADHD (grades 6–8). Participants were followed longitudinally to evaluate whether written expression abilities at baseline predicted student GPA and parent ratings of academic impairment 18 months later, after controlling for reading ability and additional relevant covariates. Written expression abilities longitudinally predicted both academic outcomes above and beyond ADHD and ODD symptoms, medication use, reading ability, and baseline values of GPA and parent-rated academic impairment. Follow-up analyses revealed that no single aspect of written expression was demonstrably more impactful on academic outcomes than the others, suggesting that writing as an entire process should be the focus of intervention. PMID:26783650
Prediction of delayed cerebral ischemia, rebleeding, and outcome after aneurysmal subarachnoid hemorrhage

NARCIS (Netherlands)

Hijdra, A.; van Gijn, J.; Nagelkerke, N. J.; Vermeulen, M.; van Crevel, H.

1988-01-01

Using logistic regression, we analyzed the predictive value of a number of entry variables with respect to the outcome variables delayed cerebral ischemia, rebleeding, and poor outcome (death or severe disability) in patients with aneurysmal subarachnoid hemorrhage. The entry variables were clinical
Preoperative Pulmonary Function Tests (PFTs) and Outcomes from Resected Early Stage Non-small Cell Lung Cancer (NSCLC).

Science.gov (United States)

Almquist, Daniel; Khanal, Nabin; Smith, Lynette; Ganti, Apar Kishor

2018-05-01

Preoperative pulmonary function tests (PFTs) predict operative morbidity and mortality after resection in lung cancer. However, the impact of preoperative PFTs on overall outcomes in surgically-resected stage I and II non-small cell lung cancer (NSCLC) has not been well studied. This is a retrospective study of 149 patients who underwent surgical resection as first-line treatment for stage I and II NSCLC at a single center between 2003 and 2014. PFTs [forced expiratory volume in 1 sec (FEV1), Diffusing Capacity (DLCO)], both absolute values and percent predicted values were categorized into quartiles. The Kaplan-Meier method and Cox regression analysis were used to determine whether PFTs predicted for overall survival (OS). Logistic regression was used to estimate the risk of postoperative complications and length of stay (LOS) greater than 10 days based on the results of PFTs. The median age of the cohort was 68 years. The cohort was predominantly males (98.6%), current or ex-smokers (98%), with stage I NSCLC (82.76%). The majority of patients underwent a lobectomy (n=121, 81.21%). The predominant tumor histology was adenocarcinoma (n=70, 47%) followed by squamous cell carcinoma (n=61, 41%). The median follow-up of surviving patients was 53.2 months. DLCO was found to be a significant predictor of OS (HR=0.93, 95% CI=0.87-0.99; p=0.03) on univariate analysis. Although PFTs did not predict for postoperative complications, worse PFTs were significant predictors of length of stay >10 days. Preoperative PFTs did not predict for survival from resected early-stage NSCLC, but did predict for prolonged hospital stay following surgery. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
Stereotactic body radiotherapy for low-risk prostate cancer: five-year outcomes

Directory of Open Access Journals (Sweden)

King Christopher R

2011-01-01

Full Text Available Abstract Purpose Hypofractionated, stereotactic body radiotherapy (SBRT is an emerging treatment approach for prostate cancer. We present the outcomes for low-risk prostate cancer patients with a median follow-up of 5 years after SBRT. Method and Materials Between Dec. 2003 and Dec. 2005, a pooled cohort of 41 consecutive patients from Stanford, CA and Naples, FL received SBRT with CyberKnife for clinically localized, low-risk prostate cancer. Prescribed dose was 35-36.25 Gy in five fractions. No patient received hormone therapy. Kaplan-Meier biochemical progression-free survival (defined using the Phoenix method and RTOG toxicity outcomes were assessed. Results At a median follow-up of 5 years, the biochemical progression-free survival was 93% (95% CI = 84.7% to 100%. Acute side effects resolved within 1-3 months of treatment completion. There were no grade 4 toxicities. No late grade 3 rectal toxicity occurred, and only one late grade 3 genitourinary toxicity occurred following repeated urologic instrumentation. Conclusion Five-year results of SBRT for localized prostate cancer demonstrate the efficacy and safety of shorter courses of high dose per fraction radiation delivered with SBRT technique. Ongoing clinical trials are underway to further explore this treatment approach.
The role of {sup 18}F-fluorodeoxyglucose uptake of bone marrow on PET/CT in predicting clinical outcomes in non-small cell lung cancer patients treated with chemoradiotherapy

Energy Technology Data Exchange (ETDEWEB)

Lee, Jeong Won [Catholic Kwandong University College of Medicine, International St. Mary' s Hospital, Department of Nuclear Medicine, Incheon (Korea, Republic of); Catholic Kwandong University College of Medicine, International St. Mary' s Hospital, Institute for Integrative Medicine, Incheon (Korea, Republic of); Seo, Ki Hyun [Soonchunhyang University Cheonan Hospital, Division of Pulmonary Medicine, Department of Internal Medicine, Cheonan (Korea, Republic of); Kim, Eun-Seog [Soonchunhyang University Cheonan Hospital, Department of Radiation Oncology, Cheonan (Korea, Republic of); Lee, Sang Mi [Soonchunhyang University Cheonan Hospital, Department of Nuclear Medicine, Cheonan, Chungcheongnam-do (Korea, Republic of)

2017-05-15

This study aimed to assess the relationship between bone marrow (BM) FDG uptake on PET/CT and serum inflammatory markers and to evaluate the prognostic value of BM FDG uptake for predicting clinical outcomes in non-small cell lung cancer (NSCLC) patients. One hundred and six NSCLC patients who underwent FDG PET/CT for staging work-up and received chemoradiotherapy were enrolled. Mean BM FDG uptake (BM SUV) and BM-to-liver uptake ratio (BLR) were measured, along with volumetric parameters of PET/CT. The relationship of BM SUV and BLR with hematologic parameters and serum inflammatory markers was evaluated. Prognostic values of BM SUV and BLR for predicting progression-free survival (PFS) and overall survival (OS) were assessed. BM SUV and BLR were significantly correlated with white blood cell count and C-reactive protein level. On univariate analysis, BLR was a significant prognostic factor for both PFS and OS. On multivariate analysis, TNM stage and BLR were independent prognostic factors for PFS, and only TNM stage was an independent prognostic factor for OS. In NSCLC patients, FDG uptake of BM reflects the systemic inflammatory response and can be used as a biomarker to identify patients with poor prognosis. (orig.)
Laparoscopic colectomy for transverse colon cancer: comparative analysis of short- and long-term outcomes.

Science.gov (United States)

Sheng, Weizheng; Zhang, Bo; Chen, Weifeng; Gu, Dayong; Gao, Weidong

2015-01-01

This study evaluated the short- and long-term outcomes of laparoscopic colectomy compared with open colectomy for patients with transverse colon cancer by matched-pair analysis. This study enrolled 59 patients who underwent laparoscopic colectomy and compared them with 59 matched patients who underwent open colectomy for transverse colon cancer. The following parameters were matched: clinical stage and type of resection. Both short- and long-term outcomes of laparoscopic colectomy were compared with those of open colectomy. No difference was observed between the two groups in terms of age, gender, ASA score, comorbidity, clinical stage and operative procedures. Regarding short-term outcomes, blood loss, time to first flatus, time to liquid diet and postoperative stay were significantly shorter in the laparoscopy group than in the open group, while operation time was significantly longer in the laparoscopy group than in the open group. Postoperative complication was similar between the two groups. With respect to long-term outcomes, the two groups did not differ significantly in terms of 5-year overall and disease-free survival. In summary, laparoscopic colectomy is a safe and feasible option for selected patients with transverse colon cancer. The short- and long-term outcomes of laparoscopic colectomy are considered to be acceptable.

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