Predicting long-term graft survival in adult kidney transplant recipients

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Brett W Pinsky

2012-01-01

Full Text Available The ability to accurately predict a population′s long-term survival has important implications for quantifying the benefits of transplantation. To identify a model that can accurately predict a kidney transplant population′s long-term graft survival, we retrospectively studied the United Network of Organ Sharing data from 13,111 kidney-only transplants completed in 1988- 1989. Nineteen-year death-censored graft survival (DCGS projections were calculated and com-pared with the population′s actual graft survival. The projection curves were created using a two-part estimation model that (1 fits a Kaplan-Meier survival curve immediately after transplant (Part A and (2 uses truncated observational data to model a survival function for long-term projection (Part B. Projection curves were examined using varying amounts of time to fit both parts of the model. The accuracy of the projection curve was determined by examining whether predicted sur-vival fell within the 95% confidence interval for the 19-year Kaplan-Meier survival, and the sample size needed to detect the difference in projected versus observed survival in a clinical trial. The 19-year DCGS was 40.7% (39.8-41.6%. Excellent predictability (41.3% can be achieved when Part A is fit for three years and Part B is projected using two additional years of data. Using less than five total years of data tended to overestimate the population′s long-term survival, accurate prediction of long-term DCGS is possible, but requires attention to the quantity data used in the projection method.

Factors Predicting Survival after Transarterial Chemoembolization of Unresectable Hepatocellular Carcinoma

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Farina M. Hanif

2014-10-01

Full Text Available Background: Transarterial chemoembolization is the preferred treatment for unresectable, intermediate-stage hepatocellular carcinoma. Survival after transarterial chemoembolization can be highly variable. The purpose of this study is to identify the factors that predict overall survival of patients with unresectable hepatocellular carcinoma who undergo transarterial chemoembolization as the initial therapy. Methods:We included patients who underwent transarterial chemoembolization from 2007 to 2012 in this study. Patient’s age, gender, cause of cirrhosis, Child-Turcotte-Pugh score, model of end-stage liver disease score, Cancer of the Liver Italian Program score, Okuda stage, alpha- fetoprotein level, site, size and number of tumors were recorded. Radiological response to transarterial chemoembolization was assessed by computerized tomography scan at 1 and 3 months after the procedure. Repeat sessions of transarterial chemoembolization were performed according to the response. We performed survival assessment and all patients were assessed for survival at the last follow-up. Results: Included in this study were 71 patients of whom there were 57 (80.3 % males, with a mean age of 51.9±12.1 years (range: 18-76 years. The mean follow-up period was 12.5±10.7 months. A total of 31 (43.7% patients had only one session of transarterial chemoembolization, 17 (23.9% underwent 2 and 11 (15.5% had 3 or more sessions. On univariate analysis, significant factors that predicted survival included serum bilirubin (P=0.02, esophageal varices (P=0.002, Cancer of the Liver Italian Program score (P=0.003, tumor size (P=0.005, >3 sessions of transarterial chemoembolization (P=0.006 and patient's age (P=0.001. Cox regression analysis showed that tumor size of 1 transarterial chemoembolization session (P=0.004 were associated with better survival. Conclusion: Our study demonstrates that survival after transarterial chemoem- bolization is predicted by tumor size

Improved survival prediction from lung function data in a large population sample

DEFF Research Database (Denmark)

Miller, M.R.; Pedersen, O.F.; Lange, P.

2008-01-01

Studies relating tung function to survival commonly express lung function impairment as a percent of predicted but this retains age, height and sex bias. We have studied alternative methods of expressing forced expiratory volume in 1 s (FEV1) for predicting all cause and airway related lung disease.......1 respectively. Cut levels of lung function were used to categorise impairment and the HR for multivariate prediction of all cause and airway related lung disease mortality were 10 and 2044 respectively for the worst category of FEV1/ht(2) compared to 5 and 194 respectively for the worst category of FEV1PP....... In univariate predictions of all cause mortality the HR for FEV1/ht(2) categories was 2-4 times higher than those for FEV1PP and 3-10 times higher for airway related tung disease mortality. We conclude that FEV1/ht(2) is superior to FEV1PP for predicting survival. in a general population and this method...

Nomogram including pretherapeutic parameters for prediction of survival after SIRT of hepatic metastases from colorectal cancer

International Nuclear Information System (INIS)

Fendler, Wolfgang Peter; Ilhan, Harun; Paprottka, Philipp M.; Jakobs, Tobias F.; Heinemann, Volker; Bartenstein, Peter; Haug, Alexander R.; Khalaf, Feras; Ezziddin, Samer; Hacker, Marcus

2015-01-01

Pre-therapeutic prediction of outcome is important for clinicians and patients in determining whether selective internal radiation therapy (SIRT) is indicated for hepatic metastases of colorectal cancer (CRC). Pre-therapeutic characteristics of 100 patients with colorectal liver metastases (CRLM) treated by radioembolization were analyzed to develop a nomogram for predicting survival. Prognostic factors were selected by univariate Cox regression analysis and subsequent tested by multivariate analysis for predicting patient survival. The nomogram was validated with reference to an external patient cohort (n = 25) from the Bonn University Department of Nuclear Medicine. Of the 13 parameters tested, four were independently associated with reduced patient survival in multivariate analysis. These parameters included no liver surgery before SIRT (HR:1.81, p = 0.014), CEA serum level ≥ 150 ng/ml (HR:2.08, p = 0.001), transaminase toxicity level ≥2.5 x upper limit of normal (HR:2.82, p = 0.001), and summed computed tomography (CT) size of the largest two liver lesions ≥10 cm (HR:2.31, p < 0.001). The area under the receiver-operating characteristic curve for our prediction model was 0.83 for the external patient cohort, indicating superior performance of our multivariate model compared to a model ignoring covariates. The nomogram developed in our study entailing four pre-therapeutic parameters gives good prediction of patient survival post SIRT. (orig.)

Nomogram including pretherapeutic parameters for prediction of survival after SIRT of hepatic metastases from colorectal cancer

Energy Technology Data Exchange (ETDEWEB)

Fendler, Wolfgang Peter [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Klinik und Poliklinik fuer Nuklearmedizin, Munich (Germany); Ilhan, Harun [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Paprottka, Philipp M. [Ludwig-Maximilians-University of Munich, Department of Clinical Radiology, Munich (Germany); Jakobs, Tobias F. [Hospital Barmherzige Brueder, Department of Diagnostic and Interventional Radiology, Munich (Germany); Heinemann, Volker [Ludwig-Maximilians-University of Munich, Department of Internal Medicine III, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Bartenstein, Peter; Haug, Alexander R. [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Khalaf, Feras [University Hospital Bonn, Department of Nuclear Medicine, Bonn (Germany); Ezziddin, Samer [Saarland University Medical Center, Department of Nuclear Medicine, Homburg (Germany); Hacker, Marcus [Vienna General Hospital, Department of Nuclear Medicine, Vienna (Austria)

2015-09-15

Pre-therapeutic prediction of outcome is important for clinicians and patients in determining whether selective internal radiation therapy (SIRT) is indicated for hepatic metastases of colorectal cancer (CRC). Pre-therapeutic characteristics of 100 patients with colorectal liver metastases (CRLM) treated by radioembolization were analyzed to develop a nomogram for predicting survival. Prognostic factors were selected by univariate Cox regression analysis and subsequent tested by multivariate analysis for predicting patient survival. The nomogram was validated with reference to an external patient cohort (n = 25) from the Bonn University Department of Nuclear Medicine. Of the 13 parameters tested, four were independently associated with reduced patient survival in multivariate analysis. These parameters included no liver surgery before SIRT (HR:1.81, p = 0.014), CEA serum level ≥ 150 ng/ml (HR:2.08, p = 0.001), transaminase toxicity level ≥2.5 x upper limit of normal (HR:2.82, p = 0.001), and summed computed tomography (CT) size of the largest two liver lesions ≥10 cm (HR:2.31, p < 0.001). The area under the receiver-operating characteristic curve for our prediction model was 0.83 for the external patient cohort, indicating superior performance of our multivariate model compared to a model ignoring covariates. The nomogram developed in our study entailing four pre-therapeutic parameters gives good prediction of patient survival post SIRT. (orig.)

Combining Gene Signatures Improves Prediction of Breast Cancer Survival

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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.

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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

Spinal cord multi-parametric magnetic resonance imaging for survival prediction in amyotrophic lateral sclerosis.

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Querin, G; El Mendili, M M; Lenglet, T; Delphine, S; Marchand-Pauvert, V; Benali, H; Pradat, P-F

2017-08-01

Assessing survival is a critical issue in patients with amyotrophic lateral sclerosis (ALS). Neuroimaging seems to be promising in the assessment of disease severity and several studies also suggest a strong relationship between spinal cord (SC) atrophy described by magnetic resonance imaging (MRI) and disease progression. The aim of the study was to determine the predictive added value of multimodal SC MRI on survival. Forty-nine ALS patients were recruited and clinical data were collected. Patients were scored on the Revised ALS Functional Rating Scale and manual muscle testing. They were followed longitudinally to assess survival. The cervical SC was imaged using the 3 T MRI system. Cord volume and cross-sectional area (CSA) at each vertebral level were computed. Diffusion tensor imaging metrics were measured. Imaging metrics and clinical variables were used as inputs for a multivariate Cox regression survival model. On building a multivariate Cox regression model with clinical and MRI parameters, fractional anisotropy, magnetization transfer ratio and CSA at C2-C3, C4-C5, C5-C6 and C6-C7 vertebral levels were significant. Moreover, the hazard ratio calculated for CSA at the C3-C4 and C5-C6 levels indicated an increased risk for patients with SC atrophy (respectively 0.66 and 0.68). In our cohort, MRI parameters seem to be more predictive than clinical variables, which had a hazard ratio very close to 1. It is suggested that multimodal SC MRI could be a useful tool in survival prediction especially if used at the beginning of the disease and when combined with clinical variables. To validate it as a biomarker, confirmation of the results in bigger independent cohorts of patients is warranted. © 2017 EAN.

Early post-transplant immune monitoring can predict long-term kidney graft survival: soluble CD30 levels, anti-HLA antibodies and IgA-anti-Fab autoantibodies.

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Amirzargar, Mohammad Ali; Amirzargar, Aliakbar; Basiri, Abbas; Hajilooi, Mehrdad; Roshanaei, Ghodratollah; Rajabi, Gholamreza; Mohammadiazar, Sina; Solgi, Ghasem

2014-01-01

This study aimed to investigate the predictive power of anti-HLA antibodies, sCD30 levels and IgA-anti-Fab autoantibody before and early after transplantation in relation to long-term kidney allograft survival. Pre- and post-transplant sera samples of 59 living-unrelated donor kidney recipients were tested for above risk factors by enzyme-linked immunoabsorbent assay. 15 out of 59 cases experienced rejection episodes (failure group). Pre- and post-transplant high sCD30 levels were significantly associated with graft failure (P=0.02 and P=0.004) and decreased 4 year graft survival (P = 0.009 and P = 0.001). Higher frequency of post-transplant HLA class-II antibody in the absence of class-I antibody was observed in failure group (P=0.007). Patients with post-transplant HLA class-I and class-II antibodies either alone or in combination showed significant lower 4 year graft survival. Recipients with high sCD30 levels in the presence of HLA class-I or class-II antibodies within 2 weeks post-transplant had poor graft survival (P = 0.004 and P = 0.002, respectively). High levels of post-transplant IgA-anti-Fab antibody was more frequent in functioning-graft patients (P = 0.00001), correlated with decreased serum creatinine levels (P = 0.01) and associated with improved graft survival (P = 0.008). Our findings indicate the deleterious effect of early post-transplant HLA antibodies and increased sCD30 levels dependently and protective effect of IgA-anti-Fab antibodies on long-term renal graft outcomes. Copyright © 2013 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Factors predicting survival following noninvasive ventilation in amyotrophic lateral sclerosis.

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Peysson, S; Vandenberghe, N; Philit, F; Vial, C; Petitjean, T; Bouhour, F; Bayle, J Y; Broussolle, E

2008-01-01

The involvement of respiratory muscles is a major predicting factor for survival in amyotrophic lateral sclerosis (ALS). Recent studies show that noninvasive ventilation (NIV) can relieve symptoms of alveolar hypoventilation. However, factors predicting survival in ALS patients when treated with NIV need to be clarified. We conducted a retrospective study of 33 consecutive ALS patients receiving NIV. Ten patients had bulbar onset. We determined the median survivals from onset, diagnosis and initiation of NIV and factors predicting survival. Statistical analysis was performed using the Kaplan-Meier test and Cox proportional hazard models. The median initial and maximal total uses of NIV were 10 and 14 h/24h. The overall median survival from ALS onset was 34.2 months and worsened with increasing age and bulbar onset of the disease. The median survival from initiation of NIV was 8.4 months and was significantly poorer in patients with advanced age or with airway mucus accumulation. Survival from initiation of NIV was not influenced by respiratory parameters or bulbar symptoms. Advanced age at diagnosis and airway mucus accumulation represent poorer prognostic factors of ALS patients treated with NIV. NIV is a helpful treatment of sleep-disordered breathing, including patients with bulbar involvement. Copyright 2008 S. Karger AG, Basel.

Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours.

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Wilson, Martin; Cummins, Carole L; Macpherson, Lesley; Sun, Yu; Natarajan, Kal; Grundy, Richard G; Arvanitis, Theodoros N; Kauppinen, Risto A; Peet, Andrew C

2013-01-01

Brain tumours cause the highest mortality and morbidity rate of all childhood tumour groups and new methods are required to improve clinical management. (1)H magnetic resonance spectroscopy (MRS) allows non-invasive concentration measurements of small molecules present in tumour tissue, providing clinically useful imaging biomarkers. The primary aim of this study was to investigate whether MRS detectable molecules can predict the survival of paediatric brain tumour patients. Short echo time (30ms) single voxel (1)H MRS was performed on children attending Birmingham Children's Hospital with a suspected brain tumour and 115 patients were included in the survival analysis. Patients were followed-up for a median period of 35 months and Cox-Regression was used to establish the prognostic value of individual MRS detectable molecules. A multivariate model of survival was also investigated to improve prognostic power. Lipids and scyllo-inositol predicted poor survival whilst glutamine and N-acetyl aspartate predicted improved survival (pmodel of survival based on three MRS biomarkers predicted survival with a similar accuracy to histologic grading (p5e-5). A negative correlation between lipids and glutamine was found, suggesting a functional link between these molecules. MRS detectable biomolecules have been identified that predict survival of paediatric brain tumour patients across a range of tumour types. The evaluation of these biomarkers in large prospective studies of specific tumour types should be undertaken. The correlation between lipids and glutamine provides new insight into paediatric brain tumour metabolism that may present novel targets for therapy. Copyright © 2012 Elsevier Ltd. All rights reserved.

A nomogram for predicting survival in patients with breast cancer brain metastasis.

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Huang, Zhou; Sun, Bing; Wu, Shikai; Meng, Xiangying; Cong, Yang; Shen, Ge; Song, Santai

2018-05-01

Brain metastasis (BM) is common in patients with breast cancer. Predicting patient survival is critical for the clinical management of breast cancer brain metastasis (BCBM). The present study was designed to develop and evaluate a prognostic model for patients with newly diagnosed BCBM. Based on the clinical data of patients with BCBM treated in the Affiliated Hospital of Academy of Military Medical Sciences (Beijing, China) between 2002 and 2014, a nomogram was developed to predict survival using proportional hazards regression analysis. The model was validated internally by bootstrapping, and the concordance index (c-index) was calculated. A calibration curve and c-index were used to evaluate discriminatory and predictive ability, in order to compare the nomogram with widely used models, including recursive partitioning analysis (RPA), graded prognostic assessment (GPA) and breast-graded prognostic assessment (Breast-GPA). A total of 411 patients with BCBM were included in the development of this predictive model. The median overall survival time was 14.1 months. Statistically significant predictors for patient survival included biological subtype, Karnofsky performance score, leptomeningeal metastasis, extracranial metastasis, the number of brain metastases and disease-free survival. A nomogram for predicting 1- and 2-year overall survival rates was constructed, which exhibited good accuracy in predicting overall survival with a concordance index of 0.735. This model outperformed RPA, GPA and Breast-GPA, based on the comparisons of the c-indexes. The nomogram constructed based on a multiple factor analysis was able to more accurately predict the individual survival probability of patients with BCBM, compared with existing models.

Serum microRNA-122 predicts survival in patients with liver cirrhosis.

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Oliver Waidmann

Full Text Available BACKGROUND: Liver cirrhosis is associated with high morbidity and mortality. MicroRNAs (miRs circulating in the blood are an emerging new class of biomarkers. In particular, the serum level of the liver-specific miR-122 might be a clinically useful new parameter in patients with acute or chronic liver disease. AIM: Here we investigated if the serum level of miR-122 might be a prognostic parameter in patients with liver cirrhosis. METHODS: 107 patients with liver cirrhosis in the test cohort and 143 patients in the validation cohort were prospectively enrolled into the present study. RNA was extracted from the sera obtained at the time of study enrollment and the level of miR-122 was assessed. Serum miR-122 levels were assessed by quantitative reverse-transcription PCR (RT-PCR and were compared to overall survival time and to different complications of liver cirrhosis. RESULTS: Serum miR-122 levels were reduced in patients with hepatic decompensation in comparison to patients with compensated liver disease. Patients with ascites, spontaneous bacterial peritonitis and hepatorenal syndrome had significantly lower miR-122 levels than patients without these complications. Multivariate Cox regression analysis revealed that the miR-122 serum levels were associated with survival independently from the MELD score, sex and age. CONCLUSIONS: Serum miR-122 is a new independent marker for prediction of survival of patients with liver cirrhosis.

The Value of Serum NR2 Antibody in Prediction of Post-Cardiopulmonary Resuscitation Survival

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Ali Bidari

2015-07-01

Full Text Available Introduction: N-methyl-D-aspartate receptor subunits antibody (NR2-ab is a sensitive marker of ischemic brain damage in clinical circumstances, such as cerebrovascular accidents. We aimed to assess the value of serum NR2-ab in predicting the post-cardiopulmonary resuscitation (CPR survival. Methods: In this cohort study, we examined serum NR2-ab levels 1 hour after the return of spontaneous circulation (ROSC in 49 successfully resuscitated patients. Patients with traumatic or asphyxic arrests, prior neurological insults, or major medical illnesses were excluded. Participants were followed until death or hospital discharge. Demographic data, coronary artery disease risk factors, time before initiation of CPR, and CPR duration were documented.  In addition, Glasgow coma scale (GCS, blood pressure, and survival status of patients were recorded at 1, 6, 24, and 72 hour(s after ROSC. Descriptive analyses were performed, and the Cox proportional hazard model was applied to assess if NR2-ab level is an independent predictive factor of survival. Results: 49 successfully resuscitated patients were evaluated; 27 (55% survived to hospital discharge, 4 (8.1% were in vegetative state, 10 (20.4% were physically disabled, and 13 (26.5% were physically functional. Within 72 hours of ROSC all of the 12 NR2-ab positive patients died. In contrast, 31 (84% of the NR2-ab negative patients survived. Sensitivity, specificity, positive and negative likelihood ratios of NR2-ab in prediction of survival were 54.5% (95%CI=32.7%-74.9%, 100% (95%CI=84.5%-100%, infinite, and 45.5% (95%CI=28.8%-71.8%, respectively. Subsequent analysis showed that both NR2-ab status and GCS were independent risk factors of death. Conclusions: A positive NR2-ab serum test 1 hour after ROSC correlated with lower 72-hour survival. Further studies are required to validate this finding and demonstrate the value of a quantitative NR2-ab assay and its optimal time of measurement.

Survival prediction model for postoperative hepatocellular carcinoma patients.

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Ren, Zhihui; He, Shasha; Fan, Xiaotang; He, Fangping; Sang, Wei; Bao, Yongxing; Ren, Weixin; Zhao, Jinming; Ji, Xuewen; Wen, Hao

2017-09-01

This study is to establish a predictive index (PI) model of 5-year survival rate for patients with hepatocellular carcinoma (HCC) after radical resection and to evaluate its prediction sensitivity, specificity, and accuracy.Patients underwent HCC surgical resection were enrolled and randomly divided into prediction model group (101 patients) and model evaluation group (100 patients). Cox regression model was used for univariate and multivariate survival analysis. A PI model was established based on multivariate analysis and receiver operating characteristic (ROC) curve was drawn accordingly. The area under ROC (AUROC) and PI cutoff value was identified.Multiple Cox regression analysis of prediction model group showed that neutrophil to lymphocyte ratio, histological grade, microvascular invasion, positive resection margin, number of tumor, and postoperative transcatheter arterial chemoembolization treatment were the independent predictors for the 5-year survival rate for HCC patients. The model was PI = 0.377 × NLR + 0.554 × HG + 0.927 × PRM + 0.778 × MVI + 0.740 × NT - 0.831 × transcatheter arterial chemoembolization (TACE). In the prediction model group, AUROC was 0.832 and the PI cutoff value was 3.38. The sensitivity, specificity, and accuracy were 78.0%, 80%, and 79.2%, respectively. In model evaluation group, AUROC was 0.822, and the PI cutoff value was well corresponded to the prediction model group with sensitivity, specificity, and accuracy of 85.0%, 83.3%, and 84.0%, respectively.The PI model can quantify the mortality risk of hepatitis B related HCC with high sensitivity, specificity, and accuracy.

Predicting and Modelling of Survival Data when Cox's Regression Model does not hold

DEFF Research Database (Denmark)

Scheike, Thomas H.; Zhang, Mei-Jie

2002-01-01

Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects...

Improving the Prediction of Prostate Cancer Overall Survival by Supplementing Readily Available Clinical Data with Gene Expression Levels of IGFBP3 and F3 in Formalin-Fixed Paraffin Embedded Core Needle Biopsy Material.

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Zhuochun Peng

Full Text Available A previously reported expression signature of three genes (IGFBP3, F3 and VGLL3 was shown to have potential prognostic value in estimating overall and cancer-specific survivals at diagnosis of prostate cancer in a pilot cohort study using freshly frozen Fine Needle Aspiration (FNA samples.We carried out a new cohort study with 241 prostate cancer patients diagnosed from 2004-2007 with a follow-up exceeding 6 years in order to verify the prognostic value of gene expression signature in formalin fixed paraffin embedded (FFPE prostate core needle biopsy tissue samples. The cohort consisted of four patient groups with different survival times and death causes. A four multiplex one-step RT-qPCR test kit, designed and optimized for measuring the expression signature in FFPE core needle biopsy samples, was used. In archive FFPE biopsy samples the expression differences of two genes (IGFBP3 and F3 were measured. The survival time predictions using the current clinical parameters only, such as age at diagnosis, Gleason score, PSA value and tumor stage, and clinical parameters supplemented with the expression levels of IGFBP3 and F3, were compared.When combined with currently used clinical parameters, the gene expression levels of IGFBP3 and F3 are improving the prediction of survival time as compared to using clinical parameters alone.The assessment of IGFBP3 and F3 gene expression levels in FFPE prostate cancer tissue would provide an improved survival prediction for prostate cancer patients at the time of diagnosis.

Pressure-Flow During Exercise Catheterization Predicts Survival in Pulmonary Hypertension.

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Hasler, Elisabeth D; Müller-Mottet, Séverine; Furian, Michael; Saxer, Stéphanie; Huber, Lars C; Maggiorini, Marco; Speich, Rudolf; Bloch, Konrad E; Ulrich, Silvia

2016-07-01

Pulmonary hypertension manifests with impaired exercise capacity. Our aim was to investigate whether the mean pulmonary arterial pressure to cardiac output relationship (mPAP/CO) predicts transplant-free survival in patients with pulmonary arterial hypertension (PAH) and inoperable chronic thromboembolic pulmonary hypertension (CTEPH). Hemodynamic data according to right heart catheterization in patients with PAH and CTEPH at rest and during supine incremental cycle exercise were analyzed. Transplant-free survival and predictive value of hemodynamics were assessed by using Kaplan-Meier and Cox regression analyses. Seventy patients (43 female; 54 with PAH, 16 with CTEPH; median (quartiles) age, 65 [50; 73] years; mPAP, 34 [29; 44] mm Hg; cardiac index, 2.8 [2.3; 3.5] [L/min]/m(2)) were followed up for 610 (251; 1256) days. Survival at 1, 3, 5, and 7 years was 89%, 81%, 71%, and 59%. Age, World Health Organization-functional class, 6-min walk test, and mixed-venous oxygen saturation (but not resting hemodynamics) predicted transplant-free survival. Maximal workload (hazard ratio [HR], 0.94 [95% CI, 0.89-0.99]; P = .027), peak cardiac index (HR, 0.51 [95% CI, 0.27-0.95]; P = .034), change in cardiac index, 0.25 [95% CI, 0.06-0.94]; P = .040), and mPAP/CO (HR, 1.02 [95% CI, 1.01-1.03]; P = .003) during exercise predicted survival. Values for mPAP/CO predicted 3-year transplant-free survival with an area under the curve of 0.802 (95% CI, 0.66-0.95; P = .004). In this collective of patients with PAH or CTEPH, the pressure-flow relationship during exercise predicted transplant-free survival and correlated with established markers of disease severity and outcome. Right heart catheterization during exercise may provide important complementary prognostic information in the management of pulmonary hypertension. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Acylcarnitines profile best predicts survival in horses with atypical myopathy.

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François Boemer

Full Text Available Equine atypical myopathy (AM is caused by hypoglycin A intoxication and is characterized by a high fatality rate. Predictive estimation of survival in AM horses is necessary to prevent unnecessary suffering of animals that are unlikely to survive and to focus supportive therapy on horses with a possible favourable prognosis of survival. We hypothesized that outcome may be predicted early in the course of disease based on the assumption that the acylcarnitine profile reflects the derangement of muscle energetics. We developed a statistical model to prognosticate the risk of death of diseased animals and found that estimation of outcome may be drawn from three acylcarnitines (C2, C10:2 and C18 -carnitines with a high sensitivity and specificity. The calculation of the prognosis of survival makes it possible to distinguish the horses that will survive from those that will die despite severe signs of acute rhabdomyolysis in both groups.

Acylcarnitines profile best predicts survival in horses with atypical myopathy

Science.gov (United States)

Detilleux, Johann; Cello, Christophe; Amory, Hélène; Marcillaud-Pitel, Christel; Richard, Eric; van Galen, Gaby; van Loon, Gunther; Lefère, Laurence; Votion, Dominique-Marie

2017-01-01

Equine atypical myopathy (AM) is caused by hypoglycin A intoxication and is characterized by a high fatality rate. Predictive estimation of survival in AM horses is necessary to prevent unnecessary suffering of animals that are unlikely to survive and to focus supportive therapy on horses with a possible favourable prognosis of survival. We hypothesized that outcome may be predicted early in the course of disease based on the assumption that the acylcarnitine profile reflects the derangement of muscle energetics. We developed a statistical model to prognosticate the risk of death of diseased animals and found that estimation of outcome may be drawn from three acylcarnitines (C2, C10:2 and C18 -carnitines) with a high sensitivity and specificity. The calculation of the prognosis of survival makes it possible to distinguish the horses that will survive from those that will die despite severe signs of acute rhabdomyolysis in both groups. PMID:28846683

The accuracy of survival time prediction for patients with glioma is improved by measuring mitotic spindle checkpoint gene expression.

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Li Bie

Full Text Available Identification of gene expression changes that improve prediction of survival time across all glioma grades would be clinically useful. Four Affymetrix GeneChip datasets from the literature, containing data from 771 glioma samples representing all WHO grades and eight normal brain samples, were used in an ANOVA model to screen for transcript changes that correlated with grade. Observations were confirmed and extended using qPCR assays on RNA derived from 38 additional glioma samples and eight normal samples for which survival data were available. RNA levels of eight major mitotic spindle assembly checkpoint (SAC genes (BUB1, BUB1B, BUB3, CENPE, MAD1L1, MAD2L1, CDC20, TTK significantly correlated with glioma grade and six also significantly correlated with survival time. In particular, the level of BUB1B expression was highly correlated with survival time (p<0.0001, and significantly outperformed all other measured parameters, including two standards; WHO grade and MIB-1 (Ki-67 labeling index. Measurement of the expression levels of a small set of SAC genes may complement histological grade and other clinical parameters for predicting survival time.

Postoperative Insulin-Like Growth Factor 1 Levels Reflect the Graft's Function and Predict Survival after Liver Transplantation.

Directory of Open Access Journals (Sweden)

Daniele Nicolini

Full Text Available The reduction of insulin-like growth factor 1 (IGF-1 plasma levels is associated with the degree of liver dysfunction and mortality in cirrhotic patients. However, little research is available on the recovery of the IGF-1 level and its prognostic role after liver transplantation (LT.From April 2010 to May 2011, 31 patients were prospectively enrolled (25/6 M/F; mean age±SEM: 55.2±1.4 years, and IGF-1 serum levels were assessed preoperatively and at 15, 30, 90, 180 and 365 days after transplantation. The influence of the donor and recipient characteristics (age, use of extended criteria donor grafts, D-MELD and incidence of early allograft dysfunction on hormonal concentration was analyzed. The prognostic role of IGF-1 level on patient survival and its correlation with routine liver function tests were also investigated.All patients showed low preoperative IGF-1 levels (mean±SEM: 29.5±2.1, and on postoperative day 15, a significant increase in the IGF-1 plasma level was observed (102.7±11.7 ng/ml; p65 years or extended criteria donor grafts. An inverse correlation between IGF-1 and bilirubin serum levels at day 15 (r = -0.3924, p = 0.0320 and 30 (r = -0.3894, p = 0.0368 was found. After multivariate analysis, early (within 15 days IGF-1 normalization [Exp(b = 3.913; p = 0.0484] was the only prognostic factor associated with an increased 3-year survival rate.IGF-1 postoperative levels are correlated with the graft's quality and reflect liver function. Early IGF-1 recovery is associated with a higher 3-year survival rate after LT.

SU-F-R-04: Radiomics for Survival Prediction in Glioblastoma (GBM)

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Zhang, H; Molitoris, J; Bhooshan, N; Choi, W; Lu, W; Mehta, M; D’Souza, W [University of Maryland School of Medicine, Baltimore, MD (United States); Tan, S [Huazhong University of Science & Technology, Wuhan (China); Giacomelli, I; Scartoni, D [University of Florence, Florence (Italy); Gzell, C [Northern Sydney Cancer Centre, Sydney (Australia)

2016-06-15

Purpose: To develop a quantitative radiomics approach for survival prediction of glioblastoma (GBM) patients treated with chemoradiotherapy (CRT). Methods: 28 GBM patients who received CRT at our institution were retrospectively studied. 255 radiomic features were extracted from 3 gadolinium-enhanced T1 weighted MRIs for 2 regions of interest (ROIs) (the surgical cavity and its surrounding enhancement rim). The 3 MRIs were at pre-treatment, 1-month and 3-month post-CRT. The imaging features comprehensively quantified the intensity, spatial variation (texture), geometric property and their spatial-temporal changes for the 2 ROIs. 3 demographics features (age, race, gender) and 12 clinical parameters (KPS, extent of resection, whether concurrent temozolomide was adjusted/stopped and radiotherapy related information) were also included. 4 Machine learning models (logistic regression (LR), support vector machine (SVM), decision tree (DT), neural network (NN)) were applied to predict overall survival (OS) and progression-free survival (PFS). The number of cases and percentage of cases predicted correctly were collected and AUC (area under the receiver operating characteristic (ROC) curve) were determined after leave-one-out cross-validation. Results: From univariate analysis, 27 features (1 demographic, 1 clinical and 25 imaging) were statistically significant (p<0.05) for both OS and PFS. Two sets of features (each contained 24 features) were algorithmically selected from all features to predict OS and PFS. High prediction accuracy of OS was achieved by using NN (96%, 27 of 28 cases were correctly predicted, AUC = 0.99), LR (93%, 26 of 28 cases were correctly predicted, AUC = 0.95) and SVM (93%, 26 of 28 cases were correctly predicted, AUC = 0.90). When predicting PFS, NN obtained the highest prediction accuracy (89%, 25 of 28 cases were correctly predicted, AUC = 0.92). Conclusion: Radiomics approach combined with patients’ demographics and clinical parameters can

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

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van der Burgh, Hannelore K; Schmidt, Ruben; Westeneng, Henk-Jan; de Reus, Marcel A; van den Berg, Leonard H; van den Heuvel, Martijn P

2017-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clinical characteristics in combination with MRI data to predict survival of ALS patients using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 ALS patients was included from whom high-resolution diffusion-weighted and T1-weighted images were acquired at the first visit to the outpatient clinic. Next, each of the patients was monitored carefully and survival time to death was recorded. Patients were labeled as short, medium or long survivors, based on their recorded time to death as measured from the time of disease onset. In the deep learning procedure, the total group of 135 patients was split into a training set for deep learning (n = 83 patients), a validation set (n = 20) and an independent evaluation set (n = 32) to evaluate the performance of the obtained deep learning networks. Deep learning based on clinical characteristics predicted survival category correctly in 68.8% of the cases. Deep learning based on MRI predicted 62.5% correctly using structural connectivity and 62.5% using brain morphology data. Notably, when we combined the three sources of information, deep learning prediction accuracy increased to 84.4%. Taken together, our findings show the added value of MRI with respect to predicting survival in ALS, demonstrating the advantage of deep learning in disease prognostication.

Simulated biologic intelligence used to predict length of stay and survival of burns.

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Frye, K E; Izenberg, S D; Williams, M D; Luterman, A

1996-01-01

From July 13, 1988, to May 14, 1995, 1585 patients with burns and no other injuries besides inhalation were treated; 4.5% did not survive. Artificial neural networks were trained on patient presentation data with known outcomes on 90% of the randomized cases. The remaining cases were then used to predict survival and length of stay in cases not trained on. Survival was predicted with more than 98% accuracy and length of stay to within a week with 72% accuracy in these cases. For anatomic area involved by burn, burns involving the feet, scalp, or both had the largest negative effect on the survival prediction. In survivors burns involving the buttocks, transport to this burn center by the military or by helicopter, electrical burns, hot tar burns, and inhalation were associated with increasing the length of stay prediction. Neural networks can be used to accurately predict the clinical outcome of a burn. What factors affect that prediction can be investigated.

Urate levels predict survival in amyotrophic lateral sclerosis: Analysis of the expanded Pooled Resource Open-Access ALS clinical trials database.

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Paganoni, Sabrina; Nicholson, Katharine; Chan, James; Shui, Amy; Schoenfeld, David; Sherman, Alexander; Berry, James; Cudkowicz, Merit; Atassi, Nazem

2018-03-01

Urate has been identified as a predictor of amyotrophic lateral sclerosis (ALS) survival in some but not all studies. Here we leverage the recent expansion of the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database to study the association between urate levels and ALS survival. Pooled data of 1,736 ALS participants from the PRO-ACT database were analyzed. Cox proportional hazards regression models were used to evaluate associations between urate levels at trial entry and survival. After adjustment for potential confounders (i.e., creatinine and body mass index), there was an 11% reduction in risk of reaching a survival endpoint during the study with each 1-mg/dL increase in uric acid levels (adjusted hazard ratio 0.89, 95% confidence interval 0.82-0.97, P ALS and confirms the utility of the PRO-ACT database as a powerful resource for ALS epidemiological research. Muscle Nerve 57: 430-434, 2018. © 2017 Wiley Periodicals, Inc.

Clinical prediction of 5-year survival in systemic sclerosis

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Fransen, Julie Munk; Popa-Diaconu, D; Hesselstrand, R

2011-01-01

Systemic sclerosis (SSc) is associated with a significant reduction in life expectancy. A simple prognostic model to predict 5-year survival in SSc was developed in 1999 in 280 patients, but it has not been validated in other patients. The predictions of a prognostic model are usually less accura...

Intratumoral heterogeneity of 18F-FDG uptake predicts survival in patients with pancreatic ductal adenocarcinoma

International Nuclear Information System (INIS)

Hyun, Seung Hyup; Kim, Ho Seong; Lee, Kyung-Han; Kim, Byung-Tae; Choi, Joon Young; Choi, Seong Ho; Choi, Dong Wook; Lee, Jong Kyun; Lee, Kwang Hyuck; Park, Joon Oh

2016-01-01

To assess whether intratumoral heterogeneity measured by 18 F-FDG PET texture analysis has potential as a prognostic imaging biomarker in patients with pancreatic ductal adenocarcinoma (PDAC). We evaluated a cohort of 137 patients with newly diagnosed PDAC who underwent pretreatment 18 F-FDG PET/CT from January 2008 to December 2010. First-order (histogram indices) and higher-order (grey-level run length, difference, size zone matrices) textural features of primary tumours were extracted by PET texture analysis. Conventional PET parameters including metabolic tumour volume (MTV), total lesion glycolysis (TLG), and standardized uptake value (SUV) were also measured. To assess and compare the predictive performance of imaging biomarkers, time-dependent receiver operating characteristic (ROC) curves for censored survival data and areas under the ROC curve (AUC) at 2 years after diagnosis were used. Associations between imaging biomarkers and overall survival were assessed using Cox proportional hazards regression models. The best imaging biomarker for overall survival prediction was first-order entropy (AUC = 0.720), followed by TLG (AUC = 0.697), MTV (AUC = 0.692), and maximum SUV (AUC = 0.625). After adjusting for age, sex, clinical stage, tumour size and serum CA19-9 level, multivariable Cox analysis demonstrated that higher entropy (hazard ratio, HR, 5.59; P = 0.028) was independently associated with worse survival, whereas TLG (HR 0.98; P = 0.875) was not an independent prognostic factor. Intratumoral heterogeneity of 18 F-FDG uptake measured by PET texture analysis is an independent predictor of survival along with tumour stage and serum CA19-9 level in patients with PDAC. In addition, first-order entropy as a measure of intratumoral metabolic heterogeneity is a better quantitative imaging biomarker of prognosis than conventional PET parameters. (orig.)

A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients

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Oberije, Cary, E-mail: cary.oberije@maastro.nl [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); De Ruysscher, Dirk [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); Universitaire Ziekenhuizen Leuven, KU Leuven (Belgium); Houben, Ruud [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); Heuvel, Michel van de; Uyterlinde, Wilma [Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam (Netherlands); Deasy, Joseph O. [Memorial Sloan Kettering Cancer Center, New York (United States); Belderbos, Jose [Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam (Netherlands); Dingemans, Anne-Marie C. [Department of Pulmonology, University Hospital Maastricht, Research Institute GROW of Oncology, Maastricht (Netherlands); Rimner, Andreas; Din, Shaun [Memorial Sloan Kettering Cancer Center, New York (United States); Lambin, Philippe [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands)

2015-07-15

Purpose: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Methods and Materials: Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). Results: The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability ( (www.predictcancer.org)). The data set can be downloaded at (https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048). Conclusions: The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.

Predicting functional decline and survival in amyotrophic lateral sclerosis.

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Ong, Mei-Lyn; Tan, Pei Fang; Holbrook, Joanna D

2017-01-01

Better predictors of amyotrophic lateral sclerosis disease course could enable smaller and more targeted clinical trials. Partially to address this aim, the Prize for Life foundation collected de-identified records from amyotrophic lateral sclerosis sufferers who participated in clinical trials of investigational drugs and made them available to researchers in the PRO-ACT database. In this study, time series data from PRO-ACT subjects were fitted to exponential models. Binary classes for decline in the total score of amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) (fast/slow progression) and survival (high/low death risk) were derived. Data was segregated into training and test sets via cross validation. Learning algorithms were applied to the demographic, clinical and laboratory parameters in the training set to predict ALSFRS-R decline and the derived fast/slow progression and high/low death risk categories. The performance of predictive models was assessed by cross-validation in the test set using Receiver Operator Curves and root mean squared errors. A model created using a boosting algorithm containing the decline in four parameters (weight, alkaline phosphatase, albumin and creatine kinase) post baseline, was able to predict functional decline class (fast or slow) with fair accuracy (AUC = 0.82). However similar approaches to build a predictive model for decline class by baseline subject characteristics were not successful. In contrast, baseline values of total bilirubin, gamma glutamyltransferase, urine specific gravity and ALSFRS-R item score-climbing stairs were sufficient to predict survival class. Using combinations of small numbers of variables it was possible to predict classes of functional decline and survival across the 1-2 year timeframe available in PRO-ACT. These findings may have utility for design of future ALS clinical trials.

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

Convergent RANK- and c-Met-mediated signaling components predict survival of patients with prostate cancer: an interracial comparative study.

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Hu, Peizhen; Chung, Leland W K; Berel, Dror; Frierson, Henry F; Yang, Hua; Liu, Chunyan; Wang, Ruoxiang; Li, Qinlong; Rogatko, Andre; Zhau, Haiyen E

2013-01-01

We reported (PLoS One 6 (12):e28670, 2011) that the activation of c-Met signaling in RANKL-overexpressing bone metastatic LNCaP cell and xenograft models increased expression of RANK, RANKL, c-Met, and phosphorylated c-Met, and mediated downstream signaling. We confirmed the significance of the RANK-mediated signaling network in castration resistant clinical human prostate cancer (PC) tissues. In this report, we used a multispectral quantum dot labeling technique to label six RANK and c-Met convergent signaling pathway mediators simultaneously in formalin fixed paraffin embedded (FFPE) tissue specimens, quantify the intensity of each expression at the sub-cellular level, and investigated their potential utility as predictors of patient survival in Caucasian-American, African-American and Chinese men. We found that RANKL and neuropilin-1 (NRP-1) expression predicts survival of Caucasian-Americans with PC. A Gleason score ≥ 8 combined with nuclear p-c-Met expression predicts survival in African-American PC patients. Neuropilin-1, p-NF-κB p65 and VEGF are predictors for the overall survival of Chinese men with PC. These results collectively support interracial differences in cell signaling networks that can predict the survival of PC patients.

A predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic

International Nuclear Information System (INIS)

Chow, Edward; Fung, KinWah; Panzarella, Tony; Bezjak, Andrea; Danjoux, Cyril; Tannock, Ian

2002-01-01

Purpose: To develop a predictive model for survival from the time of presentation in an outpatient palliative radiotherapy clinic. Methods and Materials: Sixteen factors were analyzed prospectively in 395 patients seen in a dedicated palliative radiotherapy clinic in a large tertiary cancer center using Cox's proportional hazards regression model. Results: Six prognostic factors had a statistically significant impact on survival, as follows: primary cancer site, site of metastases, Karnofsky performance score (KPS), and fatigue, appetite, and shortness of breath scores from the modified Edmonton Symptom Assessment Scale. Risk group stratification was performed (1) by assigning weights to the prognostic factors based on their levels of significance, and (2) by the number of risk factors present. The weighting method provided a Survival Prediction Score (SPS), ranging from 0 to 32. The survival probability at 3, 6, and 12 months was 83%, 70%, and 51%, respectively, for patients with SPS ≤13 (n=133); 67%, 41%, and 20% for patients with SPS 14-19 (n=129); and 36%, 18%, and 4% for patients with SPS ≥20 (n=133) (p<0.0001). Corresponding survival probabilities based on number of risk factors were as follows: 85%, 72%, and 52% (≤3 risk factors) (n=98); 68%, 47%, and 24% (4 risk factors) (n=117); and 46%, 24%, and 11% (≥5 factors) (n=180) (p<0.0001). Conclusion: Clinical prognostic factors can be used to predict prognosis among patients attending a palliative radiotherapy clinic. If validated in an independent series of patients, the model can be used to guide clinical decisions, plan supportive services, and allocate resource use

Predictive modelling of Lactobacillus casei KN291 survival in fermented soy beverage.

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Zielińska, Dorota; Dorota, Zielińska; Kołożyn-Krajewska, Danuta; Danuta, Kołożyn-Krajewska; Goryl, Antoni; Antoni, Goryl; Motyl, Ilona

2014-02-01

The aim of the study was to construct and verify predictive growth and survival models of a potentially probiotic bacteria in fermented soy beverage. The research material included natural soy beverage (Polgrunt, Poland) and the strain of lactic acid bacteria (LAB) - Lactobacillus casei KN291. To construct predictive models for the growth and survival of L. casei KN291 bacteria in the fermented soy beverage we design an experiment which allowed the collection of CFU data. Fermented soy beverage samples were stored at various temperature conditions (5, 10, 15, and 20°C) for 28 days. On the basis of obtained data concerning the survival of L. casei KN291 bacteria in soy beverage at different temperature and time conditions, two non-linear models (r(2)= 0.68-0.93) and two surface models (r(2)=0.76-0.79) were constructed; these models described the behaviour of the bacteria in the product to a satisfactory extent. Verification of the surface models was carried out utilizing the validation data - at 7°C during 28 days. It was found that applied models were well fitted and charged with small systematic errors, which is evidenced by accuracy factor - Af, bias factor - Bf and mean squared error - MSE. The constructed microbiological growth and survival models of L. casei KN291 in fermented soy beverage enable the estimation of products shelf life period, which in this case is defined by the requirement for the level of the bacteria to be above 10(6) CFU/cm(3). The constructed models may be useful as a tool for the manufacture of probiotic foods to estimate of their shelf life period.

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.

A clinical tool for predicting survival in ALS.

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Knibb, Jonathan A; Keren, Noa; Kulka, Anna; Leigh, P Nigel; Martin, Sarah; Shaw, Christopher E; Tsuda, Miho; Al-Chalabi, Ammar

2016-12-01

Amyotrophic lateral sclerosis (ALS) is a progressive and usually fatal neurodegenerative disease. Survival from diagnosis varies considerably. Several prognostic factors are known, including site of onset (bulbar or limb), age at symptom onset, delay from onset to diagnosis and the use of riluzole and non-invasive ventilation (NIV). Clinicians and patients would benefit from a practical way of using these factors to provide an individualised prognosis. 575 consecutive patients with incident ALS from a population-based registry in South-East England register for ALS (SEALS) were studied. Their survival was modelled as a two-step process: the time from diagnosis to respiratory muscle involvement, followed by the time from respiratory involvement to death. The effects of predictor variables were assessed separately for each time interval. Younger age at symptom onset, longer delay from onset to diagnosis and riluzole use were associated with slower progression to respiratory involvement, and NIV use was associated with lower mortality after respiratory involvement, each with a clinically significant effect size. Riluzole may have a greater effect in younger patients and those with longer delay to diagnosis. A patient's survival time has a roughly 50% chance of falling between half and twice the predicted median. A simple and clinically applicable graphical method of predicting an individual patient's survival from diagnosis is presented. The model should be validated in an independent cohort, and extended to include other important prognostic factors. 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/.

Convergent RANK- and c-Met-mediated signaling components predict survival of patients with prostate cancer: an interracial comparative study.

Directory of Open Access Journals (Sweden)

Peizhen Hu

Full Text Available We reported (PLoS One 6 (12:e28670, 2011 that the activation of c-Met signaling in RANKL-overexpressing bone metastatic LNCaP cell and xenograft models increased expression of RANK, RANKL, c-Met, and phosphorylated c-Met, and mediated downstream signaling. We confirmed the significance of the RANK-mediated signaling network in castration resistant clinical human prostate cancer (PC tissues. In this report, we used a multispectral quantum dot labeling technique to label six RANK and c-Met convergent signaling pathway mediators simultaneously in formalin fixed paraffin embedded (FFPE tissue specimens, quantify the intensity of each expression at the sub-cellular level, and investigated their potential utility as predictors of patient survival in Caucasian-American, African-American and Chinese men. We found that RANKL and neuropilin-1 (NRP-1 expression predicts survival of Caucasian-Americans with PC. A Gleason score ≥ 8 combined with nuclear p-c-Met expression predicts survival in African-American PC patients. Neuropilin-1, p-NF-κB p65 and VEGF are predictors for the overall survival of Chinese men with PC. These results collectively support interracial differences in cell signaling networks that can predict the survival of PC patients.

Camouflage predicts survival in ground-nesting birds.

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Troscianko, Jolyon; Wilson-Aggarwal, Jared; Stevens, Martin; Spottiswoode, Claire N

2016-01-29

Evading detection by predators is crucial for survival. Camouflage is therefore a widespread adaptation, but despite substantial research effort our understanding of different camouflage strategies has relied predominantly on artificial systems and on experiments disregarding how camouflage is perceived by predators. Here we show for the first time in a natural system, that survival probability of wild animals is directly related to their level of camouflage as perceived by the visual systems of their main predators. Ground-nesting plovers and coursers flee as threats approach, and their clutches were more likely to survive when their egg contrast matched their surrounds. In nightjars - which remain motionless as threats approach - clutch survival depended on plumage pattern matching between the incubating bird and its surrounds. Our findings highlight the importance of pattern and luminance based camouflage properties, and the effectiveness of modern techniques in capturing the adaptive properties of visual phenotypes.

Review and evaluation of performance measures for survival prediction models in external validation settings

Directory of Open Access Journals (Sweden)

M. Shafiqur Rahman

2017-04-01

Full Text Available Abstract Background When developing a prediction model for survival data it is essential to validate its performance in external validation settings using appropriate performance measures. Although a number of such measures have been proposed, there is only limited guidance regarding their use in the context of model validation. This paper reviewed and evaluated a wide range of performance measures to provide some guidelines for their use in practice. Methods An extensive simulation study based on two clinical datasets was conducted to investigate the performance of the measures in external validation settings. Measures were selected from categories that assess the overall performance, discrimination and calibration of a survival prediction model. Some of these have been modified to allow their use with validation data, and a case study is provided to describe how these measures can be estimated in practice. The measures were evaluated with respect to their robustness to censoring and ease of interpretation. All measures are implemented, or are straightforward to implement, in statistical software. Results Most of the performance measures were reasonably robust to moderate levels of censoring. One exception was Harrell’s concordance measure which tended to increase as censoring increased. Conclusions We recommend that Uno’s concordance measure is used to quantify concordance when there are moderate levels of censoring. Alternatively, Gönen and Heller’s measure could be considered, especially if censoring is very high, but we suggest that the prediction model is re-calibrated first. We also recommend that Royston’s D is routinely reported to assess discrimination since it has an appealing interpretation. The calibration slope is useful for both internal and external validation settings and recommended to report routinely. Our recommendation would be to use any of the predictive accuracy measures and provide the corresponding predictive

Long-Term Survival Prediction for Coronary Artery Bypass Grafting: Validation of the ASCERT Model Compared With The Society of Thoracic Surgeons Predicted Risk of Mortality.

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Lancaster, Timothy S; Schill, Matthew R; Greenberg, Jason W; Ruaengsri, Chawannuch; Schuessler, Richard B; Lawton, Jennifer S; Maniar, Hersh S; Pasque, Michael K; Moon, Marc R; Damiano, Ralph J; Melby, Spencer J

2018-05-01

The recently developed American College of Cardiology Foundation-Society of Thoracic Surgeons (STS) Collaboration on the Comparative Effectiveness of Revascularization Strategy (ASCERT) Long-Term Survival Probability Calculator is a valuable addition to existing short-term risk-prediction tools for cardiac surgical procedures but has yet to be externally validated. Institutional data of 654 patients aged 65 years or older undergoing isolated coronary artery bypass grafting between 2005 and 2010 were reviewed. Predicted survival probabilities were calculated using the ASCERT model. Survival data were collected using the Social Security Death Index and institutional medical records. Model calibration and discrimination were assessed for the overall sample and for risk-stratified subgroups based on (1) ASCERT 7-year survival probability and (2) the predicted risk of mortality (PROM) from the STS Short-Term Risk Calculator. Logistic regression analysis was performed to evaluate additional perioperative variables contributing to death. Overall survival was 92.1% (569 of 597) at 1 year and 50.5% (164 of 325) at 7 years. Calibration assessment found no significant differences between predicted and actual survival curves for the overall sample or for the risk-stratified subgroups, whether stratified by predicted 7-year survival or by PROM. Discriminative performance was comparable between the ASCERT and PROM models for 7-year survival prediction (p validated for prediction of long-term survival after coronary artery bypass grafting in all risk groups. The widely used STS PROM performed comparably as a predictor of long-term survival. Both tools provide important information for preoperative decision making and patient counseling about potential outcomes after coronary artery bypass grafting. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Performance of an easy-to-use prediction model for renal patient survival: an external validation study using data from the ERA-EDTA Registry.

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Hemke, Aline C; Heemskerk, Martin B A; van Diepen, Merel; Kramer, Anneke; de Meester, Johan; Heaf, James G; Abad Diez, José Maria; Torres Guinea, Marta; Finne, Patrik; Brunet, Philippe; Vikse, Bjørn E; Caskey, Fergus J; Traynor, Jamie P; Massy, Ziad A; Couchoud, Cécile; Groothoff, Jaap W; Nordio, Maurizio; Jager, Kitty J; Dekker, Friedo W; Hoitsma, Andries J

2018-01-16

An easy-to-use prediction model for long-term renal patient survival based on only four predictors [age, primary renal disease, sex and therapy at 90 days after the start of renal replacement therapy (RRT)] has been developed in The Netherlands. To assess the usability of this model for use in Europe, we externally validated the model in 10 European countries. Data from the European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) Registry were used. Ten countries that reported individual patient data to the registry on patients starting RRT in the period 1995-2005 were included. Patients prediction model was evaluated for the 10- (primary endpoint), 5- and 3-year survival predictions by assessing the calibration and discrimination outcomes. We used a data set of 136 304 patients from 10 countries. The calibration in the large and calibration plots for 10 deciles of predicted survival probabilities showed average differences of 1.5, 3.2 and 3.4% in observed versus predicted 10-, 5- and 3-year survival, with some small variation on the country level. The concordance index, indicating the discriminatory power of the model, was 0.71 in the complete ERA-EDTA Registry cohort and varied according to country level between 0.70 and 0.75. A prediction model for long-term renal patient survival developed in a single country, based on only four easily available variables, has a comparably adequate performance in a wide range of other European countries. © The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Validation of a Predictive Model for Survival in Metastatic Cancer Patients Attending an Outpatient Palliative Radiotherapy Clinic

International Nuclear Information System (INIS)

Chow, Edward; Abdolell, Mohamed; Panzarella, Tony; Harris, Kristin; Bezjak, Andrea; Warde, Padraig; Tannock, Ian

2009-01-01

Purpose: To validate a predictive model for survival of patients attending a palliative radiotherapy clinic. Methods and Materials: We described previously a model that had good predictive value for survival of patients referred during 1999 (1). The six prognostic factors (primary cancer site, site of metastases, Karnofsky performance score, and the fatigue, appetite and shortness-of-breath items from the Edmonton Symptom Assessment Scale) identified in this training set were extracted from the prospective database for the year 2000. We generated a partial score whereby each prognostic factor was assigned a value proportional to its prognostic weight. The sum of the partial scores for each patient was used to construct a survival prediction score (SPS). Patients were also grouped according to the number of these risk factors (NRF) that they possessed. The probability of survival at 3, 6, and 12 months was generated. The models were evaluated for their ability to predict survival in this validation set with appropriate statistical tests. Results: The median survival and survival probabilities of the training and validation sets were similar when separated into three groups using both SPS and NRF methods. There was no statistical difference in the performance of the SPS and NRF methods in survival prediction. Conclusion: Both the SPS and NRF models for predicting survival in patients referred for palliative radiotherapy have been validated. The NRF model is preferred because it is simpler and avoids the need to remember the weightings among the prognostic factors

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

Serum albumin predicts survival in patients with hilar cholangiocarcinoma.

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Waghray, Abhijeet; Sobotka, Anastasia; Marrero, Carlos Romero; Estfan, Bassam; Aucejo, Federico; Narayanan Menon, K V

2017-02-01

Hilar cholangiocarcinoma is a devastating malignancy with incidence varying by geography and other risk factors. Rapid progression of disease and delays in diagnosis restrict the number of patients eligible for curative therapy. The objective of this study was to determine prognostic factors of overall survival in all patients presenting with hilar cholangiocarcinoma. All adult patients with histologically confirmed hilar cholangiocarcinoma from 2003 to 2013 were evaluated for predictors of survival using demographic factors, laboratory data, symptoms and radiological characteristics at presentation. A total of 116 patients were identified to have pathological diagnosis of hilar cholangiocarcinoma and were included in the analysis. Patients with a serum albumin level >3.0 g/dL (P 3.0 g/dL was identified as an independent predictor of overall survival (hazard ratio 0.31; 95% confidence interval 0.14-0.70) with a survival benefit of 44 weeks. This study was the largest analysis to date of prognostic factors in patients with hilar cholangiocarcinoma. A serum albumin level >3.0 g/dL conferred an independent survival advantage with a significantly greater length of survival. © The Author(s) 2016. Published by Oxford University Press and Sixth Affiliated Hospital of Sun Yat-Sen University.

Factors predictive of survival and estimated years of life lost in the decade following nontraumatic and traumatic spinal cord injury.

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Hatch, B B; Wood-Wentz, C M; Therneau, T M; Walker, M G; Payne, J M; Reeves, R K

2017-06-01

Retrospective chart review. To identify factors predictive of survival after spinal cord injury (SCI). Tertiary care institution. Multiple-variable Cox proportional hazards regression analysis for 759 patients with SCI (535 nontraumatic and 221 traumatic) included age, sex, completeness of injury, level of injury, functional independence measure (FIM) scores, rehabilitation length of stay and SCI cause. Estimated years of life lost in the decade after injury was calculated for patients vs uninjured controls. Median follow-up was 11.4 years. Population characteristics included paraplegia, 58%; complete injury, 11%; male sex, 64%; and median rehabilitation length of stay, 16 days. Factors independently predictive of decreased survival were increased age (+10 years; hazard ratio (HR (95% CI)), 1.6 (1.4-1.7)), male sex (1.3 (1.0-1.6)), lower dismissal FIM score (-10 points; 1.3 (1.2-1.3)) and all nontraumatic causes. Metastatic cancer had the largest decrease in survival (HR (95% CI), 13.3 (8.7-20.2)). Primary tumors (HR (95% CI), 2.5 (1.7-3.8)), vascular (2.5 (1.6-3.8)), musculoskeletal/stenosis (1.7 (1.2-2.5)) and other nontraumatic SCI (2.3 (1.5-3.6)) were associated with decreased survival. Ten-year survival was decreased in nontraumatic SCI (mean (s.d.), 1.8 (0.3) years lost), with largest decreases in survival for metastatic cancer and spinal cord ischemia. Age, male sex and lower dismissal FIM score were associated with decreased survival, but neither injury severity nor level was associated with it. Survival after SCI varies depending on SCI cause, with survival better after traumatic SCI than after nontraumatic SCI. Metastatic cancer and vascular ischemia were associated with the greatest survival reduction.

A hemocyte gene expression signature correlated with predictive capacity of oysters to survive Vibrio infections

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Rosa Rafael

2012-06-01

Full Text Available Abstract Background The complex balance between environmental and host factors is an important determinant of susceptibility to infection. Disturbances of this equilibrium may result in multifactorial diseases as illustrated by the summer mortality syndrome, a worldwide and complex phenomenon that affects the oysters, Crassostrea gigas. The summer mortality syndrome reveals a physiological intolerance making this oyster species susceptible to diseases. Exploration of genetic basis governing the oyster resistance or susceptibility to infections is thus a major goal for understanding field mortality events. In this context, we used high-throughput genomic approaches to identify genetic traits that may characterize inherent survival capacities in C. gigas. Results Using digital gene expression (DGE, we analyzed the transcriptomes of hemocytes (immunocompetent cells of oysters able or not able to survive infections by Vibrio species shown to be involved in summer mortalities. Hemocytes were nonlethally collected from oysters before Vibrio experimental infection, and two DGE libraries were generated from individuals that survived or did not survive. Exploration of DGE data and microfluidic qPCR analyses at individual level showed an extraordinary polymorphism in gene expressions, but also a set of hemocyte-expressed genes whose basal mRNA levels discriminate oyster capacity to survive infections by the pathogenic V. splendidus LGP32. Finally, we identified a signature of 14 genes that predicted oyster survival capacity. Their expressions are likely driven by distinct transcriptional regulation processes associated or not associated to gene copy number variation (CNV. Conclusions We provide here for the first time in oyster a gene expression survival signature that represents a useful tool for understanding mortality events and for assessing genetic traits of interest for disease resistance selection programs.

ROCK I Has More Accurate Prognostic Value than MET in Predicting Patient Survival in Colorectal Cancer.

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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.

Illness perceptions predict survival in haemodialysis patients.

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Chilcot, Joseph; Wellsted, David; Farrington, Ken

2011-01-01

Illness perceptions have been shown to be important determinants of functional and psychosocial outcomes, including quality of life and treatment adherence in end-stage renal disease patients. The aim of this prospective study was to determine whether haemodialysis patients' illness perceptions impact upon survival. Haemodialysis patients from a UK renal service completed the Revised Illness Perception Questionnaire. Over the study period (May 2007 to December 2010), all-cause mortality was recorded as the endpoint. 223 patients were followed up for a median of 15.9 months (min. 10 days, max. 42.7 months). The median dialysis vintage was 17.6 months (min. 4 days, max. 391.3 months). Treatment control perceptions demonstrated a significant association with mortality (HR = 0.91, 95% CI: 0.83-0.99, p = 0.03). After controlling for covariates, including age, albumin, extra renal comorbidity and depression scores, perception of treatment control remained a significant predictor of mortality (HR = 0.89, 95% CI: 0.80-0.99, p = 0.03). Patients' perceptions of treatment control (dialysis therapy) predict survival independently of survival risk factors, including comorbidity. Studies are required to test whether psychological interventions designed to modify maladaptive illness perceptions influence clinical outcomes in this patient setting. Copyright © 2011 S. Karger AG, Basel.

Development of a Summarized Health Index (SHI for use in predicting survival in sea turtles.

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Tsung-Hsien Li

Full Text Available Veterinary care plays an influential role in sea turtle rehabilitation, especially in endangered species. Physiological characteristics, hematological and plasma biochemistry profiles, are useful references for clinical management in animals, especially when animals are during the convalescence period. In this study, these factors associated with sea turtle surviving were analyzed. The blood samples were collected when sea turtles remained alive, and then animals were followed up for surviving status. The results indicated that significantly negative correlation was found between buoyancy disorders (BD and sea turtle surviving (p < 0.05. Furthermore, non-surviving sea turtles had significantly higher levels of aspartate aminotranspherase (AST, creatinine kinase (CK, creatinine and uric acid (UA than surviving sea turtles (all p < 0.05. After further analysis by multiple logistic regression model, only factors of BD, creatinine and UA were included in the equation for calculating summarized health index (SHI for each individual. Through evaluation by receiver operating characteristic (ROC curve, the result indicated that the area under curve was 0.920 ± 0.037, and a cut-off SHI value of 2.5244 showed 80.0% sensitivity and 86.7% specificity in predicting survival. Therefore, the developed SHI could be a useful index to evaluate health status of sea turtles and to improve veterinary care at rehabilitation facilities.

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.

Preirradiation PSA predicts biochemical disease-free survival in patients treated with postprostatectomy external beam irradiation

International Nuclear Information System (INIS)

Crane, Christopher H.; Rich, Tyvin A.; Read, Paul W.; Sanfilippo, Nicholas J.; Gillenwater, Jay Y.; Kelly, Maria D.

1997-01-01

Purpose: To assess the clinical outcome and prostate-specific antigen (PSA) response and to determine prognostic factors for biochemical disease-free survival in patients treated with external beam radiotherapy following radical prostatectomy without hormonal therapy. Methods and Materials: Forty-eight patients were treated after prostatectomy with radiotherapy between March, 1988 and December, 1993. Seven patients had undetectable PSA ( 2.7. Five-year actuarial biochemical disease-free survival values were 71, 48, and 0%, respectively, for the three groups. Biochemical disease-free survival was not affected by preoperative PSA level, clinical stage, Gleason's score, pathologic stage, surgical margins, presence of undetectable PSA after surgery, surgery to radiation interval, total dose, or presence of clinically suspicious local disease. Based on digital rectal exam, there were no local failures. Conclusion: Biochemical disease-free survival after postprostatectomy radiation is predicted by the PSA at the time of irradiation. Clinical local control is excellent, but distant failure remains a significant problem in this population. The addition of concomitant systemic therapy should be investigated in patients with PSA >2.7

Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction

International Nuclear Information System (INIS)

Garzon, Benjamin; Emblem, Kyrre E.; Mouridsen, Kim; Nedregaard, Baard; Due-Toennessen, Paulina; Nome, Terje; Hald, John K.; Bjoernerud, Atle; Haaberg, Asta K.; Kvinnsland, Yngve

2011-01-01

Background. A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking. Purpose. To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients. Material and Methods. T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression. Results. Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001). Conclusion. Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients

Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction

Energy Technology Data Exchange (ETDEWEB)

Garzon, Benjamin (Dept. of Circulation and Medical Imaging, NTNU, Trondheim (Norway)), email: benjamin.garzon@ntnu.no; Emblem, Kyrre E. (The Interventional Center, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway); Dept. of Radiology, MGH-HST AA Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston (United States)); Mouridsen, Kim (Center of Functionally Integrative Neuroscience, Aarhus Univ., Aarhus (Denmark)); Nedregaard, Baard; Due-Toennessen, Paulina; Nome, Terje; Hald, John K. (Dept. of Radiology and Nuclear Medicine, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway)); Bjoernerud, Atle (The Interventional Center, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway)); Haaberg, Asta K. (Dept. of Circulation and Medical Imaging, NTNU, Trondheim (Norway); Dept. of Medical Imaging, St Olav' s Hospital, Trondheim (Norway)); Kvinnsland, Yngve (NordicImagingLab, Bergen (Norway))

2011-11-15

Background. A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking. Purpose. To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients. Material and Methods. T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression. Results. Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001). Conclusion. Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

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Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

Factors predicting survival in amyotrophic lateral sclerosis patients on non-invasive ventilation.

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Gonzalez Calzada, Nuria; Prats Soro, Enric; Mateu Gomez, Lluis; Giro Bulta, Esther; Cordoba Izquierdo, Ana; Povedano Panades, Monica; Dorca Sargatal, Jordi; Farrero Muñoz, Eva

2016-01-01

Non invasive ventilation (NIV) improves quality of life and extends survival in amyotrophic lateral sclerosis (ALS) patients. However, few data exist about the factors related to survival. We intended to assess the predictive factors that influence survival in patients after NIV initiation. Patients who started NIV from 2000 to 2014 and were tolerant (compliance ≥ 4 hours) were included; demographic, disease related and respiratory variables at NIV initiation were analysed. Statistical analysis was performed using the Kaplan-Meier test and Cox proportional hazard models. 213 patients were included with median survival from NIV initiation of 13.5 months. In univariate analysis, the identified risk factors for mortality were severity of bulbar involvement (HR 2), Forced Vital Capacity (FVC) % (HR 0.99) and ALSFRS-R (HR 0.97). Multivariate analysis showed that bulbar involvement (HR 1.92) and ALSFRS-R (HR 0.97) were independent predictive factors of survival in patients on NIV. In our study, the two prognostic factors in ALS patients following NIV were the severity of bulbar involvement and ALSFRS-R at the time on NIV initiation. A better assessment of bulbar involvement, including evaluation of the upper airway, and a careful titration on NIV are necessary to optimize treatment efficacy.

Serum level of soluble urokinase-type plasminogen activator receptor is a strong and independent predictor of survival in human immunodeficiency virus infection

DEFF Research Database (Denmark)

Sidenius, N; Sier, C.F.M.; Ullum, H

2000-01-01

levels of soluble uPAR (suPAR) in patients with advanced HIV-1 disease and whether the serum level of suPAR is predictive of clinical outcome. Using an enzyme-linked immunosorbent assay, the level of suPAR was measured retrospectively in serum samples from 314 patients with HIV-1 infection. By Kaplan......-Meier and Cox regression analyses, the serum suPAR levels were correlated to survival with AIDS-related death as the end point. High levels of serum suPAR (greater than median) were associated with poor overall survival, and Kaplan-Meier analysis on patients stratified by suPAR level demonstrated a continuous...

Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird

OpenAIRE

Milenkaya, Olga; Catlin, Daniel H.; Legge, Sarah; Walters, Jeffrey R.

2015-01-01

Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival ove...

Efficacy of a composite biological age score to predict ten-year survival among Kansas and Nebraska Mennonites.

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Uttley, M; Crawford, M H

1994-02-01

In 1980 and 1981 Mennonite descendants of a group of Russian immigrants participated in a multidisciplinary study of biological aging. The Mennonites live in Goessel, Kansas, and Henderson, Nebraska. In 1991 the survival status of the participants was documented by each church secretary. Data are available for 1009 individuals, 177 of whom are now deceased. They ranged from 20 to 95 years in age when the data were collected. Biological ages were computed using a stepwise multiple regression procedure based on 38 variables previously identified as being related to survival, with chronological age as the dependent variable. Standardized residuals place participants in either a predicted-younger or a predicted-older group. The independence of the variables biological age and survival status is tested with the chi-square statistic. The significance of biological age differences between surviving and deceased Mennonites is determined by t test values. The two statistics provide consistent results. Predicted age group classification and survival status are related. The group of deceased participants is generally predicted to be older than the group of surviving participants, although neither statistic is significant for all subgroups of Mennonites. In most cases, however, individuals in the predicted-older groups are at a relatively higher risk of dying compared with those in the predicted-younger groups, although the increased risk is not always significant.

Pre- and Posttransplant IgA Anti-Fab Antibodies to Predict Long-term Kidney Graft Survival.

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Amirzargar, M A; Amirzargar, A; Basiri, A; Hajilooi, M; Roshanaei, G; Rajabi, G; Solgi, G

2015-05-01

Immunologic factors are reliable markers for allograft monitoring, because of their seminal role in rejection process. One of these factors is the immunoglobulin (Ig)A anti-Fab of the IgG antibody. This study aimed to evaluate the predictive value of pre- and posttransplant levels of this marker for kidney allograft function and survival. Sera samples of 59 living unrelated donor kidney recipients were collected before and after transplantation (days 7, 14, and 30) and investigated for IgA anti-Fab of IgG antibody levels using enzyme-linked immunosorbent assay in relation with allograft outcome. Among 59 patients, 15 cases (25%) including 10 with acute rejection and 5 with chronic rejection episodes showed graft failure during a mean of 5 years of follow-up. High posttransplant levels of IgA anti-Fab antibodies were observed more frequently in patients with stable graft function (SGF) compared with patients with graft failure (P = 2 × 10(-6)). None of patients with acute or chronic rejection episodes had high levels of IgA anti-Fab antibodies at day 30 posttransplant compared with the SGF group (P = 10(-6) and P = .01, respectively). In addition, high levels of IgA anti-Fab antibody correlated with lesser concentration of serum creatinine at 1 month posttransplantation (P = .01). Five-year graft survival was associated with high levels of pre- and posttransplant IgA anti-Fab antibodies (P = .02 and P = .003, respectively). Our findings indicate the protective effect of higher levels of IgA anti-Fab antibodies regarding to kidney allograft outcomes and long-term graft survival. Copyright © 2015 Elsevier Inc. All rights reserved.

Evaluating the efficacy of tumor markers CA 19-9 and CEA to predict operability and survival in pancreatic malignancies.

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Mehta, Jay; Prabhu, Ramkrishna; Eshpuniyani, Priya; Kantharia, Chetan; Supe, Avinash

2010-01-01

Using CA 19-9 and CEA (elevated > 2 times of normal) as predictors in determining operability and survival in pancreatic tumors. Levels of CA 19-9 and CEA were measured (pre and post operatively) in 49 patients of pancreatic malignancy. CECT was performed for diagnosis and staging. An experienced surgeon determined the operability. The levels of tumor markers were correlated with the operability and the survival based on CECT and intra-operative findings. 16/24 (67%) patients with CA 19-9 levels (CEA levels (CEA levels (p = 0.003) were found to be non-resectable. Of the 27 patients, found resectable on CECT, 5 were non-resectable intra-operatively. All of these had elevated levels of CA 19-9 and 4/5 (80%) had elevated levels of CEA. Only 5/21 (23%) non-resectable patients, with elevated levels of CA 19-9 reported at 1 year follow up. None of the non-resectable patients with CA 19-9 levels > 1000 U/ml reported at 6 month follow-up. None of the resectable patients pre-operatively showed evidence of recurrence. All achieved normal values post surgery. Elevated levels of CA 19-9 and CEA (> 2 times) predict increased chances of inoperability and poor survival in pancreatic tumors. Levels > 3 times had increased risk of inoperability even in patients deemed resectable on CT-Scan. Diagnostic laparoscopy would be beneficial in these patients. Levels of CA 19-9 (> 1000 U/ml) indicate a dismal survival in non-resectable group of patients.

Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis.

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Attiyeh, Marc A; Chakraborty, Jayasree; Doussot, Alexandre; Langdon-Embry, Liana; Mainarich, Shiana; Gönen, Mithat; Balachandran, Vinod P; D'Angelica, Michael I; DeMatteo, Ronald P; Jarnagin, William R; Kingham, T Peter; Allen, Peter J; Simpson, Amber L; Do, Richard K

2018-04-01

Pancreatic cancer is a highly lethal cancer with no established a priori markers of survival. Existing nomograms rely mainly on post-resection data and are of limited utility in directing surgical management. This study investigated the use of quantitative computed tomography (CT) features to preoperatively assess survival for pancreatic ductal adenocarcinoma (PDAC) patients. A prospectively maintained database identified consecutive chemotherapy-naive patients with CT angiography and resected PDAC between 2009 and 2012. Variation in CT enhancement patterns was extracted from the tumor region using texture analysis, a quantitative image analysis tool previously described in the literature. Two continuous survival models were constructed, with 70% of the data (training set) using Cox regression, first based only on preoperative serum cancer antigen (CA) 19-9 levels and image features (model A), and then on CA19-9, image features, and the Brennan score (composite pathology score; model B). The remaining 30% of the data (test set) were reserved for independent validation. A total of 161 patients were included in the analysis. Training and test sets contained 113 and 48 patients, respectively. Quantitative image features combined with CA19-9 achieved a c-index of 0.69 [integrated Brier score (IBS) 0.224] on the test data, while combining CA19-9, imaging, and the Brennan score achieved a c-index of 0.74 (IBS 0.200) on the test data. We present two continuous survival prediction models for resected PDAC patients. Quantitative analysis of CT texture features is associated with overall survival. Further work includes applying the model to an external dataset to increase the sample size for training and to determine its applicability.

High serum uric acid concentration predicts poor survival in patients with breast cancer.

Science.gov (United States)

Yue, Cai-Feng; Feng, Pin-Ning; Yao, Zhen-Rong; Yu, Xue-Gao; Lin, Wen-Bin; Qian, Yuan-Min; Guo, Yun-Miao; Li, Lai-Sheng; Liu, Min

2017-10-01

Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Survival prediction of trauma patients: a study on US National Trauma Data Bank.

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Sefrioui, I; Amadini, R; Mauro, J; El Fallahi, A; Gabbrielli, M

2017-12-01

Exceptional circumstances like major incidents or natural disasters may cause a huge number of victims that might not be immediately and simultaneously saved. In these cases it is important to define priorities avoiding to waste time and resources for not savable victims. Trauma and Injury Severity Score (TRISS) methodology is the well-known and standard system usually used by practitioners to predict the survival probability of trauma patients. However, practitioners have noted that the accuracy of TRISS predictions is unacceptable especially for severely injured patients. Thus, alternative methods should be proposed. In this work we evaluate different approaches for predicting whether a patient will survive or not according to simple and easily measurable observations. We conducted a rigorous, comparative study based on the most important prediction techniques using real clinical data of the US National Trauma Data Bank. Empirical results show that well-known Machine Learning classifiers can outperform the TRISS methodology. Based on our findings, we can say that the best approach we evaluated is Random Forest: it has the best accuracy, the best area under the curve, and k-statistic, as well as the second-best sensitivity and specificity. It has also a good calibration curve. Furthermore, its performance monotonically increases as the dataset size grows, meaning that it can be very effective to exploit incoming knowledge. Considering the whole dataset, it is always better than TRISS. Finally, we implemented a new tool to compute the survival of victims. This will help medical practitioners to obtain a better accuracy than the TRISS tools. Random Forests may be a good candidate solution for improving the predictions on survival upon the standard TRISS methodology.

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

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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

Individualized Prediction of Overall Survival After Postoperative Radiation Therapy in Patients With Early-Stage Cervical Cancer: A Korean Radiation Oncology Group Study (KROG 13-03)

International Nuclear Information System (INIS)

Lee, Hyun Jin; Han, Seungbong; Kim, Young Seok; Nam, Joo-Hyun; Kim, Hak Jae; Kim, Jae Weon; Park, Won; Kim, Byoung-Gie; Kim, Jin Hee; Cha, Soon Do; Kim, Juree; Lee, Ki-Heon; Yoon, Mee Sun

2013-01-01

Purpose: A nomogram is a predictive statistical model that generates the continuous probability of a clinical event such as death or recurrence. The aim of the study was to construct a nomogram to predict 5-year overall survival after postoperative radiation therapy for stage IB to IIA cervical cancer. Methods and Materials: The clinical data from 1702 patients with early-stage cervical cancer, treated at 10 participating hospitals from 1990 to 2011, were reviewed to develop a prediction nomogram based on the Cox proportional hazards model. Demographic, clinical, and pathologic variables were included and analyzed to formulate the nomogram. The discrimination and calibration power of the model was measured using a concordance index (c-index) and calibration curve. Results: The median follow-up period for surviving patients was 75.6 months, and the 5-year overall survival probability was 87.1%. The final model was constructed using the following variables: age, number of positive pelvic lymph nodes, parametrial invasion, lymphovascular invasion, and the use of concurrent chemotherapy. The nomogram predicted the 5-year overall survival with a c-index of 0.69, which was superior to the predictive power of the International Federation of Gynecology and Obstetrics (FIGO) staging system (c-index of 0.54). Conclusions: A survival-predicting nomogram that offers an accurate level of prediction and discrimination was developed based on a large multi-center study. The model may be more useful than the FIGO staging system for counseling individual patients regarding prognosis

Individualized Prediction of Overall Survival After Postoperative Radiation Therapy in Patients With Early-Stage Cervical Cancer: A Korean Radiation Oncology Group Study (KROG 13-03)

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Lee, Hyun Jin [Department of Radiation Oncology, Asan Medical Center, University of Ulsan, College of Medicine, Seoul (Korea, Republic of); Han, Seungbong [Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan, College of Medicine, Seoul (Korea, Republic of); Kim, Young Seok, E-mail: ysk@amc.seoul.kr [Department of Radiation Oncology, Asan Medical Center, University of Ulsan, College of Medicine, Seoul (Korea, Republic of); Nam, Joo-Hyun [Department of Obstetrics and Gynecology, Asan Medical Center, University of Ulsan, College of Medicine, Seoul (Korea, Republic of); Kim, Hak Jae [Department of Radiation Oncology, Seoul National University Hospital, Seoul (Korea, Republic of); Kim, Jae Weon [Department of Obstetrics and Gynecology, Seoul National University Hospital, Seoul (Korea, Republic of); Park, Won [Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of); Kim, Byoung-Gie [Department of Obstetrics and Gynecology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of); Kim, Jin Hee [Department of Radiation Oncology, Dongsan Medical Center, Keimyung University School of Medicine, Daegu (Korea, Republic of); Cha, Soon Do [Department of Obstetrics and Gynecology, Dongsan Medical Center, Keimyung University School of Medicine, Daegu (Korea, Republic of); Kim, Juree [Department of Radiation Oncology, Cheil General Hospital and Women' s Healthcare Center, Kwandong University, College of Medicine, Seoul (Korea, Republic of); Lee, Ki-Heon [Department of Obstetrics and Gynecology, Cheil General Hospital and Women' s Healthcare Center, Kwandong University, College of Medicine, Seoul (Korea, Republic of); Yoon, Mee Sun [Department of Radiation Oncology, Chonnam National University Hwasun Hospital, Chonnam National University Medical School, Jeollanam-do (Korea, Republic of); and others

2013-11-15

Purpose: A nomogram is a predictive statistical model that generates the continuous probability of a clinical event such as death or recurrence. The aim of the study was to construct a nomogram to predict 5-year overall survival after postoperative radiation therapy for stage IB to IIA cervical cancer. Methods and Materials: The clinical data from 1702 patients with early-stage cervical cancer, treated at 10 participating hospitals from 1990 to 2011, were reviewed to develop a prediction nomogram based on the Cox proportional hazards model. Demographic, clinical, and pathologic variables were included and analyzed to formulate the nomogram. The discrimination and calibration power of the model was measured using a concordance index (c-index) and calibration curve. Results: The median follow-up period for surviving patients was 75.6 months, and the 5-year overall survival probability was 87.1%. The final model was constructed using the following variables: age, number of positive pelvic lymph nodes, parametrial invasion, lymphovascular invasion, and the use of concurrent chemotherapy. The nomogram predicted the 5-year overall survival with a c-index of 0.69, which was superior to the predictive power of the International Federation of Gynecology and Obstetrics (FIGO) staging system (c-index of 0.54). Conclusions: A survival-predicting nomogram that offers an accurate level of prediction and discrimination was developed based on a large multi-center study. The model may be more useful than the FIGO staging system for counseling individual patients regarding prognosis.

Facial morphology predicts male fitness and rank but not survival in Second World War Finnish soldiers.

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Loehr, John; O'Hara, Robert B

2013-08-23

We investigated fitness, military rank and survival of facial phenotypes in large-scale warfare using 795 Finnish soldiers who fought in the Winter War (1939-1940). We measured facial width-to-height ratio-a trait known to predict aggressive behaviour in males-and assessed whether facial morphology could predict survival, lifetime reproductive success (LRS) and social status. We found no difference in survival along the phenotypic gradient, however, wider-faced individuals had greater LRS, but achieved a lower military rank.

Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer

NARCIS (Netherlands)

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.

2017-01-01

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

Radiomic features from the peritumoral brain parenchyma on treatment-naive multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings

Energy Technology Data Exchange (ETDEWEB)

Prasanna, Prateek; Patel, Jay; Madabhushi, Anant; Tiwari, Pallavi [Case Western Reserve University, Department of Biomedical Engineering, Cleveland, OH (United States); Partovi, Sasan [University Hospitals Case Medical Center, Case Western Reserve School of Medicine, Cleveland, OH (United States)

2017-10-15

Despite 90 % of glioblastoma (GBM) recurrences occurring in the peritumoral brain zone (PBZ), its contribution in patient survival is poorly understood. The current study leverages computerized texture (i.e. radiomic) analysis to evaluate the efficacy of PBZ features from pre-operative MRI in predicting long- (>18 months) versus short-term (<7 months) survival in GBM. Sixty-five patient examinations (29 short-term, 36 long-term) with gadolinium-contrast T{sub 1w}, FLAIR and T{sub 2w} sequences from the Cancer Imaging Archive were employed. An expert manually segmented each study as: enhancing lesion, PBZ and tumour necrosis. 402 radiomic features (capturing co-occurrence, grey-level dependence and directional gradients) were obtained for each region. Evaluation was performed using threefold cross-validation, such that a subset of studies was used to select the most predictive features, and the remaining subset was used to evaluate their efficacy in predicting survival. A subset of ten radiomic 'peritumoral' MRI features, suggestive of intensity heterogeneity and textural patterns, was found to be predictive of survival (p = 1.47 x 10{sup -5}) as compared to features from enhancing tumour, necrotic regions and known clinical factors. Our preliminary analysis suggests that radiomic features from the PBZ on routine pre-operative MRI may be predictive of long- versus short-term survival in GBM. (orig.)

Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird.

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Olga Milenkaya

Full Text Available Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch, a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous

Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird.

Science.gov (United States)

Milenkaya, Olga; Catlin, Daniel H; Legge, Sarah; Walters, Jeffrey R

2015-01-01

Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage) such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous interpretation of

Nomogram incorporating PSA level to predict cancer-specific survival for men with clinically localized prostate cancer managed without curative intent

Science.gov (United States)

Kattan, Michael W.; Cuzick, Jack; Fisher, Gabrielle; Berney, Daniel M.; Oliver, Tim; Foster, Christopher S.; Møller, Henrik; Reuter, Victor; Fearn, Paul; Eastham, James; Scardino, Peter T.

2012-01-01

Introduction The prognosis of men with clinically localized prostate cancer is highly variable, and it is difficult to counsel a man who may be considering avoiding, or delaying, aggressive therapy. After collecting data on a large cohort of men who received no initial active prostate cancer therapy, we sought to develop, and to internally validate, a nomogram for prediction of disease-specific survival. Methods Working with 6 cancer registries within England and numerous hospitals in the region, we constructed a population-based cohort of men diagnosed with prostate cancer between 1990 and 1996. All men had baseline serum prostate specific antigen (PSA) measurements, centralized pathologic grading, and centralized review of clinical stage assignment. Based upon the clinical and pathological data from 1,911 men, we developed and validated a statistical model that served as the basis for the nomogram. The discrimination and calibration of the nomogram were assessed with use of one third of the men, who were omitted from modeling and used as a test sample. Results The median age of the included men was 70.4 years. The 25th and 75th percentiles of PSA were 7.3 and 32.6 ng/ml respectively, and the median was 15.4 ng/ml. Forty-two percent of the men had high grade disease. The nomogram predicted well with a concordance index of 0.73 and had good calibration. Conclusions We have developed an accurate tool for predicting the probability that a man with clinically localized prostate cancer will survive his disease for 120 months if the cancer is not treated with curative intent immediately. The tool should be helpful for patient counseling and clinical trial design. PMID:18000803

Predicting survival time in noncurative patients with advanced cancer: a prospective study in China.

Science.gov (United States)

Cui, Jing; Zhou, Lingjun; Wee, B; Shen, Fengping; Ma, Xiuqiang; Zhao, Jijun

2014-05-01

Accurate prediction of prognosis for cancer patients is important for good clinical decision making in therapeutic and care strategies. The application of prognostic tools and indicators could improve prediction accuracy. This study aimed to develop a new prognostic scale to predict survival time of advanced cancer patients in China. We prospectively collected items that we anticipated might influence survival time of advanced cancer patients. Participants were recruited from 12 hospitals in Shanghai, China. We collected data including demographic information, clinical symptoms and signs, and biochemical test results. Log-rank tests, Cox regression, and linear regression were performed to develop a prognostic scale. Three hundred twenty patients with advanced cancer were recruited. Fourteen prognostic factors were included in the prognostic scale: Karnofsky Performance Scale (KPS) score, pain, ascites, hydrothorax, edema, delirium, cachexia, white blood cell (WBC) count, hemoglobin, sodium, total bilirubin, direct bilirubin, aspartate aminotransferase (AST), and alkaline phosphatase (ALP) values. The score was calculated by summing the partial scores, ranging from 0 to 30. When using the cutoff points of 7-day, 30-day, 90-day, and 180-day survival time, the scores were calculated as 12, 10, 8, and 6, respectively. We propose a new prognostic scale including KPS, pain, ascites, hydrothorax, edema, delirium, cachexia, WBC count, hemoglobin, sodium, total bilirubin, direct bilirubin, AST, and ALP values, which may help guide physicians in predicting the likely survival time of cancer patients more accurately. More studies are needed to validate this scale in the future.

Preliminary study of tumor heterogeneity in imaging predicts two year survival in pancreatic cancer patients.

Directory of Open Access Journals (Sweden)

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.

Science.gov (United States)

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.

The impact of groundwater level on soil seed bank survival

NARCIS (Netherlands)

Bekker, RM; Oomes, MJM; Bakker, JP

Seed longevity of plant species is an important topic in restoration management, and little is known about the effects of environmental conditions on seed survival and longevity under natural conditions. Therefore, the effect of groundwater level on the survival of seeds in the soil seed bank of a

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

A NEW METHOD FOR PREDICTING SURVIVAL AND ESTIMATING UNCERTAINTY IN TRAUMA PATIENTS

Directory of Open Access Journals (Sweden)

V. G. Schetinin

2017-01-01

Full Text Available The Trauma and Injury Severity Score (TRISS is the current “gold” standard of screening patient’s condition for purposes of predicting survival probability. More than 40 years of TRISS practice revealed a number of problems, particularly, 1 unexplained fluctuation of predicted values caused by aggregation of screening tests, and 2 low accuracy of uncertainty intervals estimations. We developed a new method made it available for practitioners as a web calculator to reduce negative effect of factors given above. The method involves Bayesian methodology of statistical inference which, being computationally expensive, in theory provides most accurate predictions. We implemented and tested this approach on a data set including 571,148 patients registered in the US National Trauma Data Bank (NTDB with 1–20 injuries. These patients were distributed over the following categories: (1 174,647 with 1 injury, (2 381,137 with 2–10 injuries, and (3 15,364 with 11–20 injuries. Survival rates in each category were 0.977, 0.953, and 0.831, respectively. The proposed method has improved prediction accuracy by 0.04%, 0.36%, and 3.64% (p-value <0.05 in the categories 1, 2, and 3, respectively. Hosmer-Lemeshow statistics showed a significant improvement of the new model calibration. The uncertainty 2σ intervals were reduced from 0.628 to 0.569 for patients of the second category and from 1.227 to 0.930 for patients of the third category, both with p-value <0.005. The new method shows the statistically significant improvement (p-value <0.05 in accuracy of predicting survival and estimating the uncertainty intervals. The largest improvement has been achieved for patients with 11–20 injuries. The method is available for practitioners as a web calculator http://www.traumacalc.org.

[The survival prediction model of advanced gallbladder cancer based on Bayesian network: a multi-institutional study].

Science.gov (United States)

Tang, Z H; Geng, Z M; Chen, C; Si, S B; Cai, Z Q; Song, T Q; Gong, P; Jiang, L; Qiu, Y H; He, Y; Zhai, W L; Li, S P; Zhang, Y C; Yang, Y

2018-05-01

Objective: To investigate the clinical value of Bayesian network in predicting survival of patients with advanced gallbladder cancer(GBC)who underwent curative intent surgery. Methods: The clinical data of patients with advanced GBC who underwent curative intent surgery in 9 institutions from January 2010 to December 2015 were analyzed retrospectively.A median survival time model based on a tree augmented naïve Bayes algorithm was established by Bayesia Lab software.The survival time, number of metastatic lymph nodes(NMLN), T stage, pathological grade, margin, jaundice, liver invasion, age, sex and tumor morphology were included in this model.Confusion matrix, the receiver operating characteristic curve and area under the curve were used to evaluate the accuracy of the model.A priori statistical analysis of these 10 variables and a posterior analysis(survival time as the target variable, the remaining factors as the attribute variables)was performed.The importance rankings of each variable was calculated with the polymorphic Birnbaum importance calculation based on the posterior analysis results.The survival probability forecast table was constructed based on the top 4 prognosis factors. The survival curve was drawn by the Kaplan-Meier method, and differences in survival curves were compared using the Log-rank test. Results: A total of 316 patients were enrolled, including 109 males and 207 females.The ratio of male to female was 1.0∶1.9, the age was (62.0±10.8)years.There was 298 cases(94.3%) R0 resection and 18 cases(5.7%) R1 resection.T staging: 287 cases(90.8%) T3 and 29 cases(9.2%) T4.The median survival time(MST) was 23.77 months, and the 1, 3, 5-year survival rates were 67.4%, 40.8%, 32.0%, respectively.For the Bayesian model, the number of correctly predicted cases was 121(≤23.77 months) and 115(>23.77 months) respectively, leading to a 74.86% accuracy of this model.The prior probability of survival time was 0.503 2(≤23.77 months) and 0.496 8

Soluble CD30 levels in recipients undergoing heart transplantation do not predict post-transplant outcome.

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Ypsilantis, Efthymios; Key, Timothy; Bradley, J Andrew; Morgan, C Helen; Tsui, Stephen; Parameshwar, Jayan; Taylor, Craig J

2009-11-01

The pre-transplant serum level of soluble CD30 (sCD30), a proteolytic derivative of the lymphocyte surface receptor CD30, has been suggested as a biomarker for immunologic risk after organ transplantation. Pre-transplant serum sCD30 levels were determined in 200 consecutive adult heart transplant recipients undertaken at a single center. Transplant outcome (acute rejection in the first 12 months and patient survival up to 5 years post-transplant) was determined. Patients treated with a left ventricular assist device (LVAD) prior to transplantation (n = 28) had higher levels of sCD30 (median 64 U/ml, range 12 to 112 U/ml) than those (n = 172) with no LVAD (median 36 U/ml, range 1 to 158 U/ml, p sCD30 levels were "low" (lower quartile, 58 U/ml, n = 50). Neither acute rejection nor recipient survival differed according to sCD30 level, with values (mean +/- SEM) of 0.30 +/- 0.04, 0.23 +/- 0.03 and 0.30 +/- 0.05 acute rejection episodes per 100 days in the low, intermediate and high groups, respectively, with recipient survival rates at 1 year of 77.7%, 84.9% and 86% and at 5 years of 73.6%, 67.9% and 75.8%, respectively. Pre-transplant serum sCD30 level does not predict acute allograft rejection or recipient survival after heart transplantation, although sCD30 levels are increased by LVAD, possibly as a result of biomaterial-host immune interaction.

Predictive markers of survival in HIV-seropositive and HIV-seronegative Tanzanian patients with extrapulmonary tuberculosis

NARCIS (Netherlands)

Richter, C.; Koelemay, M. J.; Swai, A. B.; Perenboom, R.; Mwakyusa, D. H.; Oosting, J.

1995-01-01

Prediction of survival in Tanzanian patients with extrapulmonary tuberculosis (TB). To evaluate the prognostic value of clinical and laboratory parameters on survival in human immunodeficiency virus (HIV) seropositive and HIV seronegative patients with extrapulmonary TB. Over an 8-month period 192

Volumetric parameters on FDG PET can predict early intrahepatic recurrence-free survival in patients with hepatocellular carcinoma after curative surgical resection

Energy Technology Data Exchange (ETDEWEB)

Lee, Jeong Won [Catholic Kwandong University College of Medicine, Department of Nuclear Medicine, Incheon (Korea, Republic of); Hwang, Sang Hyun; Kim, Hyun Jeong; Kim, Dongwoo; Cho, Arthur; Yun, Mijin [Yonsei University College of Medicine, Department of Nuclear Medicine, Seoul (Korea, Republic of)

2017-11-15

This study assessed the prognostic values of volumetric parameters on {sup 18}F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in predicting early intrahepatic recurrence-free survival (RFS) after curative resection in patients with hepatocellular carcinoma (HCC). A retrospective analysis was performed on 242 patients with HCC who underwent staging FDG PET and subsequent curative surgical resection. The tumor-to-non-tumorous liver uptake ratio, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the HCC lesions on PET were measured. The prognostic values of clinical factors and PET parameters for predicting overall RFS, overall survival (OS), extrahepatic RFS, and early and late intrahepatic RFS were assessed. The median follow-up period was 54.7 months, during which 110 patients (45.5%) experienced HCC recurrence and 62 (25.6%) died. Patients with extrahepatic and early intrahepatic recurrence showed worse OS than did those with no recurrence or late intrahepatic recurrence (p < 0.001). Serum bilirubin level, MTV, and TLG were independent prognostic factors for overall RFS and OS (p < 0.05). Only MTV and TLG were prognostic for extrahepatic RFS (p < 0.05). Serum alpha-fetoprotein and bilirubin levels, MTV, and TLG were prognostic for early intrahepatic RFS (p < 0.05) and hepatitis C virus (HCV) positivity and serum albumin level were independently prognostic for late intrahepatic RFS (p < 0.05). Intrahepatic recurrence showed different prognoses according to the time interval of recurrence in which early recurrence had as poor survival as extrahepatic recurrence. MTV and TLG on initial staging PET were significant independent factors for predicting early intrahepatic and extrahepatic RFS in patients with HCC after curative resection. Only HCV positivity and serum albumin level were significant for late intrahepatic RFS, which is mainly attributable to the de novo formation of new primary HCC. (orig.)

Risk Prediction of One-Year Mortality in Patients with Cardiac Arrhythmias Using Random Survival Forest

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Fen Miao

2015-01-01

Full Text Available Existing models for predicting mortality based on traditional Cox proportional hazard approach (CPH often have low prediction accuracy. This paper aims to develop a clinical risk model with good accuracy for predicting 1-year mortality in cardiac arrhythmias patients using random survival forest (RSF, a robust approach for survival analysis. 10,488 cardiac arrhythmias patients available in the public MIMIC II clinical database were investigated, with 3,452 deaths occurring within 1-year followups. Forty risk factors including demographics and clinical and laboratory information and antiarrhythmic agents were analyzed as potential predictors of all-cause mortality. RSF was adopted to build a comprehensive survival model and a simplified risk model composed of 14 top risk factors. The built comprehensive model achieved a prediction accuracy of 0.81 measured by c-statistic with 10-fold cross validation. The simplified risk model also achieved a good accuracy of 0.799. Both results outperformed traditional CPH (which achieved a c-statistic of 0.733 for the comprehensive model and 0.718 for the simplified model. Moreover, various factors are observed to have nonlinear impact on cardiac arrhythmias prognosis. As a result, RSF based model which took nonlinearity into account significantly outperformed traditional Cox proportional hazard model and has great potential to be a more effective approach for survival analysis.

Early social networks predict survival in wild bottlenose dolphins.

Directory of Open Access Journals (Sweden)

Margaret A Stanton

Full Text Available A fundamental question concerning group-living species is what factors influence the evolution of sociality. Although several studies link adult social bonds to fitness, social patterns and relationships are often formed early in life and are also likely to have fitness consequences, particularly in species with lengthy developmental periods, extensive social learning, and early social bond-formation. In a longitudinal study of bottlenose dolphins (Tursiops sp., calf social network structure, specifically the metric eigenvector centrality, predicted juvenile survival in males. Additionally, male calves that died post-weaning had stronger ties to juvenile males than surviving male calves, suggesting that juvenile males impose fitness costs on their younger counterparts. Our study indicates that selection is acting on social traits early in life and highlights the need to examine the costs and benefits of social bonds during formative life history stages.

Cell survival in carbon beams - comparison of amorphous track model predictions

DEFF Research Database (Denmark)

Grzanka, L.; Greilich, S.; Korcyl, M.

Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under i....... Amorphous track modelling of luminescence detector efficiency in proton and carbon beams. 4.Tsuruoka C, Suzuki M, Kanai T, et al. LET and ion species dependence for cell killing in normal human skin fibroblasts. Radiat Res. 2005;163:494-500.......Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under ion....... [2] . In addition, a new approach based on microdosimetric distributions is presented and investigated [3] . Material and methods: A suitable software library embrasing the mentioned amorphous track models including numerous submodels with respect to delta-electron range models, radial dose...

The Preoperative Controlling Nutritional Status Score Predicts Survival After Curative Surgery in Patients with Pathological Stage I Non-small Cell Lung Cancer.

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Shoji, Fumihiro; Haratake, Naoki; Akamine, Takaki; Takamori, Shinkichi; Katsura, Masakazu; Takada, Kazuki; Toyokawa, Gouji; Okamoto, Tatsuro; Maehara, Yoshihiko

2017-02-01

The prognostic Controlling Nutritional Status (CONUT) score is used to evaluate immuno-nutritional conditions and is a predictive factor of postoperative survival in patients with digestive tract cancer. We retrospectively analyzed clinicopathological features of patients with pathological stage I non-small cell lung cancer (NSCLC) to identify predictors or prognostic factors of postoperative survival and to investigate the role of preoperative CONUT score in predicting survival. We selected 138 consecutive patients with pathological stage I NSCLC treated from August 2005 to August 2010. We measured their preoperative CONUT score in uni- and multivariate Cox regression analyses of postoperative survival. A high CONUT score was positively associated with preoperative serum carcinoembryonic antigen level (p=0.0100) and postoperative recurrence (p=0.0767). In multivariate analysis, the preoperative CONUT score [relative risk (RR)=6.058; 95% confidence interval (CI)=1.068-113.941; p=0.0407), increasing age (RR=7.858; 95% CI=2.034-36.185; p=0.0029), and pleural invasion (RR=36.615; 95% CI=5.900-362.620; pcancer-specific survival (CS), and overall survival (OS), the group with high CONUT score had a significantly shorter RFS, CS, and OS than did the low-CONUT score group by log-rank test (p=0.0458, p=0.0104 and p=0.0096, respectively). The preoperative CONUT score is both a predictive and prognostic factor in patients with pathological stage I NSCLC. This immuno-nutritional score can indicate patients at high risk of postoperative recurrence and death. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

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.

Landscape‐level patterns in fawn survival across North America

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Gingery, Tess M.; Diefenbach, Duane R.; Wallingford, Bret D.; Rosenberry, Christopher S.

2018-01-01

A landscape‐level meta‐analysis approach to examining early survival of ungulates may elucidate patterns in survival not evident from individual studies. Despite numerous efforts, the relationship between fawn survival and habitat characteristics remains unclear and there has been no attempt to examine trends in survival across landscape types with adequate replication. In 2015–2016, we radiomarked 98 white‐tailed deer (Odocoileus virginianus) fawns in 2 study areas in Pennsylvania. By using a meta‐analysis approach, we compared fawn survival estimates from across North America using published data from 29 populations in 16 states to identify patterns in survival and cause‐specific mortality related to landscape characteristics, predator communities, and deer population density. We modeled fawn survival relative to percentage of agricultural land cover and deer density. Estimated average survival to 3–6 months of age was 0.414 ± 0.062 (SE) in contiguous forest landscapes (no agriculture) and for every 10% increase in land area in agriculture, fawn survival increased 0.049 ± 0.014. We classified cause‐specific mortality as human‐caused, natural (excluding predation), and predation according to agriculturally dominated, forested, and mixed (i.e., both agricultural and forest cover) landscapes. Predation was the greatest source of mortality in all landscapes. Landscapes with mixed forest and agricultural cover had greater proportions and rates of human‐caused mortalities, and lower proportions and rates of mortality due to predators, when compared to forested landscapes. Proportion and rate of natural deaths did not differ among landscapes. We failed to detect any relationship between fawn survival and deer density. The results highlight the need to consider multiple spatial scales when accounting for factors that influence fawn survival. Furthermore, variation in mortality sources and rates among landscapes indicate the potential for

Lung Shunt Fraction prior to Yttrium-90 Radioembolization Predicts Survival in Patients with Neuroendocrine Liver Metastases: Single-Center Prospective Analysis

International Nuclear Information System (INIS)

Ludwig, Johannes M.; Ambinder, Emily McIntosh; Ghodadra, Anish; Xing, Minzhi; Prajapati, Hasmukh J.; Kim, Hyun S.

2016-01-01

ObjectiveTo investigate survival outcomes following radioembolization with Yttrium-90 (Y90) for neuroendocrine tumor liver metastases (NETLMs). This study was designed to assess the efficacy of Y90 radioembolization and to evaluate lung shunt fraction (LSF) as a predictor for survival.MethodsA single-center, prospective study of 44 consecutive patients (median age: 58.5 years, 29.5 % male) diagnosed with pancreatic (52.3 %) or carcinoid (47.7 %) NETLMs from 2006 to 2012 who underwent Y90 radioembolization was performed. Patients’ baseline characteristics, including LSF and median overall survival (OS) from first Y90 radioembolization, were recorded and compared between patients with high (≥10 %) and low ( 1.2 mg (p = 0.016), and lack of pretreatment with octreotide (p = 0.01) as independent prognostic factors for poorer survival. Tumor type and total radiation dose did not predict survival.ConclusionsLSF ≥10 %, elevated bilirubin levels, and lack of pretreatment with octreotide were found to be independent prognostic factors for poorer survival in patients with NETLMs.

Nomogram based overall survival prediction in stereotactic body radiotherapy for oligo-metastatic lung disease

DEFF Research Database (Denmark)

Tanadini-Lang, S; Rieber, J; Filippi, A R

2017-01-01

BACKGROUND: Radical local treatment of pulmonary metastases is practiced with increasing frequency due to acknowledgment and better understanding of oligo-metastatic disease. This study aimed to develop a nomogram predicting overall survival (OS) after stereotactic body radiotherapy (SBRT......) for pulmonary metastases. PATIENTS AND METHODS: A multi-institutional database of 670 patients treated with SBRT for pulmonary metastases was used as training cohort. Cox regression analysis with bidirectional variable elimination was performed to identify factors to be included into the nomogram model...... to predict 2-year OS. The calibration rate of the nomogram was assessed by plotting the actual Kaplan-Meier 2-year OS against the nomogram predicted survival. The nomogram was externally validated using two separate monocentric databases of 145 and 92 patients treated with SBRT for pulmonary metastases...

Prognostic value of pre-treatment DCE-MRI parameters in predicting disease free and overall survival for breast cancer patients undergoing neoadjuvant chemotherapy

International Nuclear Information System (INIS)

Pickles, Martin D.; Manton, David J.; Lowry, Martin; Turnbull, Lindsay W.

2009-01-01

The purpose of this study was to investigate whether dynamic contrast enhanced MRI (DCE-MRI) data, both pharmacokinetic and empirical, can predict, prior to neoadjuvant chemotherapy, which patients are likely to have a shorter disease free survival (DFS) and overall survival (OS) interval following surgery. Traditional prognostic parameters were also included in the survival analysis. Consequently, a comparison of the prognostic value could be made between all the parameters studied. MR examinations were conducted on a 1.5 T system in 68 patients prior to the initiation of neoadjuvant chemotherapy. DCE-MRI consisted of a fast spoiled gradient echo sequence acquired over 35 phases with a mean temporal resolution of 11.3 s. Both pharmacokinetic and empirical parameters were derived from the DCE-MRI data. Kaplan-Meier survival plots were generated for each parameter and group comparisons were made utilising logrank tests. The results from the 54 patients entered into the univariate survival analysis demonstrated that traditional prognostic parameters (tumour grade, hormonal status and size), empirical parameters (maximum enhancement index, enhancement index at 30 s, area under the curve and initial slope) and adjuvant therapies demonstrated significant differences in survival intervals. Further multivariate Cox regression survival analysis revealed that empirical enhancement parameters contributed the greatest prediction of both DFS and OS in the resulting models. In conclusion, this study has demonstrated that in patients who exhibit high levels of perfusion and vessel permeability pre-treatment, evidenced by elevated empirical DCE-MRI parameters, a significantly lower disease free survival and overall survival can be expected.

Prognostic value of pre-treatment DCE-MRI parameters in predicting disease free and overall survival for breast cancer patients undergoing neoadjuvant chemotherapy

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Pickles, Martin D. [Centre for Magnetic Resonance Investigations, Division of Cancer, Postgraduate Medical School, University of Hull, Hull Royal Infirmary, Anlaby Road, Hull, HU3 2JZ (United Kingdom)], E-mail: m.pickles@hull.ac.uk; Manton, David J. [Centre for Magnetic Resonance Investigations, Division of Cancer, Postgraduate Medical School, University of Hull, Hull Royal Infirmary, Anlaby Road, Hull, HU3 2JZ (United Kingdom)], E-mail: d.j.manton@hull.ac.uk; Lowry, Martin [Centre for Magnetic Resonance Investigations, Division of Cancer, Postgraduate Medical School, University of Hull, Hull Royal Infirmary, Anlaby Road, Hull, HU3 2JZ (United Kingdom)], E-mail: m.lowry@hull.ac.uk; Turnbull, Lindsay W. [Centre for Magnetic Resonance Investigations, Division of Cancer, Postgraduate Medical School, University of Hull, Hull Royal Infirmary, Anlaby Road, Hull, HU3 2JZ (United Kingdom)], E-mail: l.w.turnbull@hull.ac.uk

2009-09-15

The purpose of this study was to investigate whether dynamic contrast enhanced MRI (DCE-MRI) data, both pharmacokinetic and empirical, can predict, prior to neoadjuvant chemotherapy, which patients are likely to have a shorter disease free survival (DFS) and overall survival (OS) interval following surgery. Traditional prognostic parameters were also included in the survival analysis. Consequently, a comparison of the prognostic value could be made between all the parameters studied. MR examinations were conducted on a 1.5 T system in 68 patients prior to the initiation of neoadjuvant chemotherapy. DCE-MRI consisted of a fast spoiled gradient echo sequence acquired over 35 phases with a mean temporal resolution of 11.3 s. Both pharmacokinetic and empirical parameters were derived from the DCE-MRI data. Kaplan-Meier survival plots were generated for each parameter and group comparisons were made utilising logrank tests. The results from the 54 patients entered into the univariate survival analysis demonstrated that traditional prognostic parameters (tumour grade, hormonal status and size), empirical parameters (maximum enhancement index, enhancement index at 30 s, area under the curve and initial slope) and adjuvant therapies demonstrated significant differences in survival intervals. Further multivariate Cox regression survival analysis revealed that empirical enhancement parameters contributed the greatest prediction of both DFS and OS in the resulting models. In conclusion, this study has demonstrated that in patients who exhibit high levels of perfusion and vessel permeability pre-treatment, evidenced by elevated empirical DCE-MRI parameters, a significantly lower disease free survival and overall survival can be expected.

An Easy Tool to Predict Survival in Patients Receiving Radiation Therapy for Painful Bone Metastases

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Westhoff, Paulien G., E-mail: p.g.westhoff@umcutrecht.nl [Department of Radiotherapy, University Medical Center Utrecht, Utrecht (Netherlands); Graeff, Alexander de [Department of Medical Oncology, University Medical Center Utrecht, Utrecht (Netherlands); Monninkhof, Evelyn M. [Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht (Netherlands); Bollen, Laurens; Dijkstra, Sander P. [Department of Orthopedic Surgery, Leiden University Medical Center (Netherlands); Steen-Banasik, Elzbieta M. van der [ARTI Institute for Radiation Oncology Arnhem, Arnhem (Netherlands); Vulpen, Marco van [Department of Radiotherapy, University Medical Center Utrecht, Utrecht (Netherlands); Leer, Jan Willem H. [Department of Radiotherapy, University Medical Center Nijmegen, Nijmegen (Netherlands); Marijnen, Corrie A.; Linden, Yvette M. van der [Department of Clinical Oncology, Leiden University Medical Center, Leiden (Netherlands)

2014-11-15

Purpose: Patients with bone metastases have a widely varying survival. A reliable estimation of survival is needed for appropriate treatment strategies. Our goal was to assess the value of simple prognostic factors, namely, patient and tumor characteristics, Karnofsky performance status (KPS), and patient-reported scores of pain and quality of life, to predict survival in patients with painful bone metastases. Methods and Materials: In the Dutch Bone Metastasis Study, 1157 patients were treated with radiation therapy for painful bone metastases. At randomization, physicians determined the KPS; patients rated general health on a visual analogue scale (VAS-gh), valuation of life on a verbal rating scale (VRS-vl) and pain intensity. To assess the predictive value of the variables, we used multivariate Cox proportional hazard analyses and C-statistics for discriminative value. Of the final model, calibration was assessed. External validation was performed on a dataset of 934 patients who were treated with radiation therapy for vertebral metastases. Results: Patients had mainly breast (39%), prostate (23%), or lung cancer (25%). After a maximum of 142 weeks' follow-up, 74% of patients had died. The best predictive model included sex, primary tumor, visceral metastases, KPS, VAS-gh, and VRS-vl (C-statistic = 0.72, 95% CI = 0.70-0.74). A reduced model, with only KPS and primary tumor, showed comparable discriminative capacity (C-statistic = 0.71, 95% CI = 0.69-0.72). External validation showed a C-statistic of 0.72 (95% CI = 0.70-0.73). Calibration of the derivation and the validation dataset showed underestimation of survival. Conclusion: In predicting survival in patients with painful bone metastases, KPS combined with primary tumor was comparable to a more complex model. Considering the amount of variables in complex models and the additional burden on patients, the simple model is preferred for daily use. In addition, a risk table for survival is

Combining Pathway Identification and Breast Cancer Survival Prediction via Screening-Network Methods

Directory of Open Access Journals (Sweden)

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

Prognostic factors in patients with advanced cancer: use of the patient-generated subjective global assessment in survival prediction.

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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.

Disease-free survival after hepatic resection in hepatocellular carcinoma patients: a prediction approach using artificial neural network.

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Wen-Hsien Ho

Full Text Available BACKGROUND: A database for hepatocellular carcinoma (HCC patients who had received hepatic resection was used to develop prediction models for 1-, 3- and 5-year disease-free survival based on a set of clinical parameters for this patient group. METHODS: The three prediction models included an artificial neural network (ANN model, a logistic regression (LR model, and a decision tree (DT model. Data for 427, 354 and 297 HCC patients with histories of 1-, 3- and 5-year disease-free survival after hepatic resection, respectively, were extracted from the HCC patient database. From each of the three groups, 80% of the cases (342, 283 and 238 cases of 1-, 3- and 5-year disease-free survival, respectively were selected to provide training data for the prediction models. The remaining 20% of cases in each group (85, 71 and 59 cases in the three respective groups were assigned to validation groups for performance comparisons of the three models. Area under receiver operating characteristics curve (AUROC was used as the performance index for evaluating the three models. CONCLUSIONS: The ANN model outperformed the LR and DT models in terms of prediction accuracy. This study demonstrated the feasibility of using ANNs in medical decision support systems for predicting disease-free survival based on clinical databases in HCC patients who have received hepatic resection.

Disease-Free Survival after Hepatic Resection in Hepatocellular Carcinoma Patients: A Prediction Approach Using Artificial Neural Network

Science.gov (United States)

Ho, Wen-Hsien; Lee, King-Teh; Chen, Hong-Yaw; Ho, Te-Wei; Chiu, Herng-Chia

2012-01-01

Background A database for hepatocellular carcinoma (HCC) patients who had received hepatic resection was used to develop prediction models for 1-, 3- and 5-year disease-free survival based on a set of clinical parameters for this patient group. Methods The three prediction models included an artificial neural network (ANN) model, a logistic regression (LR) model, and a decision tree (DT) model. Data for 427, 354 and 297 HCC patients with histories of 1-, 3- and 5-year disease-free survival after hepatic resection, respectively, were extracted from the HCC patient database. From each of the three groups, 80% of the cases (342, 283 and 238 cases of 1-, 3- and 5-year disease-free survival, respectively) were selected to provide training data for the prediction models. The remaining 20% of cases in each group (85, 71 and 59 cases in the three respective groups) were assigned to validation groups for performance comparisons of the three models. Area under receiver operating characteristics curve (AUROC) was used as the performance index for evaluating the three models. Conclusions The ANN model outperformed the LR and DT models in terms of prediction accuracy. This study demonstrated the feasibility of using ANNs in medical decision support systems for predicting disease-free survival based on clinical databases in HCC patients who have received hepatic resection. PMID:22235270

Pretreatment Evaluation of Microcirculation by Dynamic Contrast-Enhanced Magnetic Resonance Imaging Predicts Survival in Primary Rectal Cancer Patients

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DeVries, Alexander Friedrich [Department of Radio-Oncology, Academic Teaching Hospital Feldkirch, Feldkirch (Austria); Piringer, Gudrun, E-mail: gudrun.piringer@hotmail.com [Department of Oncology, Wels-Grieskirchen Medical Hospital, Wels (Austria); Kremser, Christian; Judmaier, Werner [Department of Radiology, Innsbruck Medical University, Innsbruck (Austria); Saely, Christoph Hubert [Department of Medicine and Cardiology, Academic Teaching Hospital Feldkirch, Feldkirch (Austria); Lukas, Peter [Department of Radio-Oncology, Innsbruck Medical University, Innsbruck (Austria); Öfner, Dietmar [Department of Surgery, Paracelsus Medical University, Salzburg (Austria)

2014-12-01

Purpose: To investigate the prognostic value of the perfusion index (PI), a microcirculatory parameter estimated from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which integrates information on both flow and permeability, to predict overall survival and disease-free survival in patients with primary rectal cancer. Methods and Materials: A total of 83 patients with stage cT3 rectal cancer requiring neoadjuvant chemoradiation were investigated with DCE-MRI before start of therapy. Contrast-enhanced dynamic T{sub 1} mapping was obtained, and a simple data analysis strategy based on the calculation of the maximum slope of the tissue concentration–time curve divided by the maximum of the arterial input function was used as a measure of tumor microcirculation (PI), which integrates information on both flow and permeability. Results: In 39 patients (47.0%), T downstaging (ypT0-2) was observed. During a mean (±SD) follow-up period of 71 ± 29 months, 58 patients (69.9%) survived, and disease-free survival was achieved in 45 patients (54.2%). The mean PI (PImean) averaged over the group of nonresponders was significantly higher than for responders. Additionally, higher PImean in age- and gender-adjusted analyses was strongly predictive of therapy nonresponse. Most importantly, PImean strongly and significantly predicted disease-free survival (unadjusted hazard ratio [HR], 1.85 [ 95% confidence interval, 1.35-2.54; P<.001)]; HR adjusted for age and sex, 1.81 [1.30-2.51]; P<.001) as well as overall survival (unadjusted HR 1.42 [1.02-1.99], P=.040; HR adjusted for age and sex, 1.43 [1.03-1.98]; P=.034). Conclusions: This analysis identifies PImean as a novel biomarker that is predictive for therapy response, disease-free survival, and overall survival in patients with primary locally advanced rectal cancer.

Integration of RNA-Seq and RPPA data for survival time prediction in cancer patients.

Science.gov (United States)

Isik, Zerrin; Ercan, Muserref Ece

2017-10-01

Integration of several types of patient data in a computational framework can accelerate the identification of more reliable biomarkers, especially for prognostic purposes. This study aims to identify biomarkers that can successfully predict the potential survival time of a cancer patient by integrating the transcriptomic (RNA-Seq), proteomic (RPPA), and protein-protein interaction (PPI) data. The proposed method -RPBioNet- employs a random walk-based algorithm that works on a PPI network to identify a limited number of protein biomarkers. Later, the method uses gene expression measurements of the selected biomarkers to train a classifier for the survival time prediction of patients. RPBioNet was applied to classify kidney renal clear cell carcinoma (KIRC), glioblastoma multiforme (GBM), and lung squamous cell carcinoma (LUSC) patients based on their survival time classes (long- or short-term). The RPBioNet method correctly identified the survival time classes of patients with between 66% and 78% average accuracy for three data sets. RPBioNet operates with only 20 to 50 biomarkers and can achieve on average 6% higher accuracy compared to the closest alternative method, which uses only RNA-Seq data in the biomarker selection. Further analysis of the most predictive biomarkers highlighted genes that are common for both cancer types, as they may be driver proteins responsible for cancer progression. The novelty of this study is the integration of a PPI network with mRNA and protein expression data to identify more accurate prognostic biomarkers that can be used for clinical purposes in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.

Role of plasma EBV DNA levels in predicting recurrence of nasopharyngeal carcinoma in a western population

International Nuclear Information System (INIS)

Ferrari, Daris; Alterio, Daniela; Foa, Paolo; Codecà, Carla; Bertuzzi, Cecilia; Broggio, Francesca; Crepaldi, Francesca; Luciani, Andrea; Floriani, Irene; Ansarin, Mohssen; Chiesa, Fausto

2012-01-01

Loco-regionally advanced nasopharyngeal carcinomas can be cured by the combination of chemotherapy and radiotherapy. In Eastern countries, plasma levels of viral Epstein-Barr deoxyribonucleic acid (DNA) are accurate in predicting recurrence, but few data are available in Western populations. The aim of this prospective study was to evaluate the relationship between viral Epstein-Barr DNA copy numbers in plasma and the response rate, progression-free survival and overall survival in a cohort of Western patients with stage IIb-IVb nasopharyngeal cancer. We evaluated plasma samples from 36 consecutive patients treated with induction chemotherapy followed by chemoradiation. EBV copy numbers were determined after DNA extraction using real-time quantitative polymerase chain reaction. Survival curves were estimated using the Kaplan–Meier method. Circulating Epstein-Barr virus DNA levels were measured before treatment, at the end of concomitant chemo- and radiotherapy, and during the follow-up period. Pre-treatment levels significantly correlated with the initial stage and probability of relapse. Their increase was 100% specific and 71.3% sensitive in detecting loco-regional or metastatic recurrence (an overall accuracy of 94.4%). Three-year progression-free and overall survival were respectively 78.2% and 97.1%. The results of this study confirm that patients from a Western country affected by loco-regionally advanced nasopharyngeal carcinoma have high plasma Epstein-Barr virus DNA levels at diagnosis. The monitoring of plasma levels is sensitive and highly specific in detecting disease recurrence and metastases

Prediction of survival to discharge following cardiopulmonary resuscitation using classification and regression trees.

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Ebell, Mark H; Afonso, Anna M; Geocadin, Romergryko G

2013-12-01

To predict the likelihood that an inpatient who experiences cardiopulmonary arrest and undergoes cardiopulmonary resuscitation survives to discharge with good neurologic function or with mild deficits (Cerebral Performance Category score = 1). Classification and Regression Trees were used to develop branching algorithms that optimize the ability of a series of tests to correctly classify patients into two or more groups. Data from 2007 to 2008 (n = 38,092) were used to develop candidate Classification and Regression Trees models to predict the outcome of inpatient cardiopulmonary resuscitation episodes and data from 2009 (n = 14,435) to evaluate the accuracy of the models and judge the degree of over fitting. Both supervised and unsupervised approaches to model development were used. 366 hospitals participating in the Get With the Guidelines-Resuscitation registry. Adult inpatients experiencing an index episode of cardiopulmonary arrest and undergoing cardiopulmonary resuscitation in the hospital. The five candidate models had between 8 and 21 nodes and an area under the receiver operating characteristic curve from 0.718 to 0.766 in the derivation group and from 0.683 to 0.746 in the validation group. One of the supervised models had 14 nodes and classified 27.9% of patients as very unlikely to survive neurologically intact or with mild deficits (Tree models that predict survival to discharge with good neurologic function or with mild deficits following in-hospital cardiopulmonary arrest. Models like this can assist physicians and patients who are considering do-not-resuscitate orders.

Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic.

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Wang, Ming; Long, Qi

2016-09-01

Prediction models for disease risk and prognosis play an important role in biomedical research, and evaluating their predictive accuracy in the presence of censored data is of substantial interest. The standard concordance (c) statistic has been extended to provide a summary measure of predictive accuracy for survival models. Motivated by a prostate cancer study, we address several issues associated with evaluating survival prediction models based on c-statistic with a focus on estimators using the technique of inverse probability of censoring weighting (IPCW). Compared to the existing work, we provide complete results on the asymptotic properties of the IPCW estimators under the assumption of coarsening at random (CAR), and propose a sensitivity analysis under the mechanism of noncoarsening at random (NCAR). In addition, we extend the IPCW approach as well as the sensitivity analysis to high-dimensional settings. The predictive accuracy of prediction models for cancer recurrence after prostatectomy is assessed by applying the proposed approaches. We find that the estimated predictive accuracy for the models in consideration is sensitive to NCAR assumption, and thus identify the best predictive model. Finally, we further evaluate the performance of the proposed methods in both settings of low-dimensional and high-dimensional data under CAR and NCAR through simulations. © 2016, The International Biometric Society.

Pre-transplant levels of ficolin-3 are associated with kidney graft survival

DEFF Research Database (Denmark)

Bay, Jakob T; Hein, Estrid; Sørensen, Søren S

2013-01-01

. 97 blood donors served as controls. Ficolin-3, C4 and C3 were measured in pre-transplant as well as in control serum samples. In controls, deposition of ficolin-3, C4, C3 and the terminal complement complex (TCC) was measured in an assay based on acetylated albumin as matrix. The ficolin-3 levels...... correlated with the serum levels of C4 and C3. The serum levels of ficolin-3 correlated with the deposition of ficolin-3, C4, C3 and TCC. Survival analyses showed that high pre-transplant serum levels of ficolin-3 were associated with decreased graft survival. These results suggest an important role...

Effect of initial lactate level on short-term survival in patients with out-of-hospital cardiac arrest

Directory of Open Access Journals (Sweden)

Tuba Sarıaydın, MD

2017-12-01

Full Text Available Purpose: This study evaluated whether serum lactate levels (SLL at admission in patients with cardiac arrest (CA can predict successful return of spontaneous circulation (ROSC or short-term survival, especially within the first 24 h. Materials and methods: This prospective, observational study was conducted in the emergency department (ED of a training and research hospital from April 2015 through February 2016. It included all patients older than 18 years who presented to the ED during the study period with non-traumatic out-of-hospital cardiac arrest (OHCA. The study measured two outcomes: whether ROSC was achieved and whether short-term survival was achieved. ROSC was defined as the presence of spontaneous circulation for the first hour after cardiopulmonary resuscitation (CPR. Survival was defined as having survived for a minimum of 24 h after ROSC. Results: The study included 140 patients who were admitted to the ED with OHCA. ROSC was achieved in 55 patients (39.3%, and survival for 24 h following CA was achieved in 42 patients (30%. The mean SLL in the ROSC (+ and ROSC (- groups were 9.1 ± 3.2 mmol/L and 9.8 ± 2.9 mmol/L, respectively. The mean SLL in the survivor and non-survivor groups were 8.6 ± 2.9 mmol/L and 10 ± 3.1 mmol/L, respectively. These differences were not statistically significant (p = 0.1. A multivariate regression model assessing the factors that predicted both ROSC and 24-h survival showed the odds ratio (OR of initial SLL was 1.3 (95% CI: 1.05–1.6 and 1.1 (95% CI: 0.9–1.3, respectively. Conclusions: This study showed that in OHCA patients, SLL on admission was not associated with increased ROSC achievement or 24-h survival. Keywords: Cardiac arrest, Out-of-hospital cardiac arrest (OHCA, Return of spontaneous circulation (ROSC, Serum lactate, Emergency department

A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound.

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Tadayyon, Hadi; Sannachi, Lakshmanan; Gangeh, Mehrdad J; Kim, Christina; Ghandi, Sonal; Trudeau, Maureen; Pritchard, Kathleen; Tran, William T; Slodkowska, Elzbieta; Sadeghi-Naini, Ali; Czarnota, Gregory J

2017-04-12

Quantitative ultrasound (QUS) can probe tissue structure and analyze tumour characteristics. Using a 6-MHz ultrasound system, radiofrequency data were acquired from 56 locally advanced breast cancer patients prior to their neoadjuvant chemotherapy (NAC) and QUS texture features were computed from regions of interest in tumour cores and their margins as potential predictive and prognostic indicators. Breast tumour molecular features were also collected and used for analysis. A multiparametric QUS model was constructed, which demonstrated a response prediction accuracy of 88% and ability to predict patient 5-year survival rates (p = 0.01). QUS features demonstrated superior performance in comparison to molecular markers and the combination of QUS and molecular markers did not improve response prediction. This study demonstrates, for the first time, that non-invasive QUS features in the core and margin of breast tumours can indicate breast cancer response to neoadjuvant chemotherapy (NAC) and predict five-year recurrence-free survival.

Country-Level Macroeconomic Indicators Predict Early Post-Allogeneic Hematopoietic Cell Transplantation Survival in Acute Lymphoblastic Leukemia: A CIBMTR Analysis.

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Wood, William A; Brazauskas, Ruta; Hu, Zhen-Huan; Abdel-Azim, Hisham; Ahmed, Ibrahim A; Aljurf, Mahmoud; Badawy, Sherif; Beitinjaneh, Amer; George, Biju; Buchbinder, David; Cerny, Jan; Dedeken, Laurence; Diaz, Miguel Angel; Freytes, Cesar O; Ganguly, Siddhartha; Gergis, Usama; Almaguer, David Gomez; Gupta, Ashish; Hale, Gregory; Hashmi, Shahrukh K; Inamoto, Yoshihiro; Kamble, Rammurti T; Adekola, Kehinde; Kindwall-Keller, Tamila; Knight, Jennifer; Kumar, Lalit; Kuwatsuka, Yachiyo; Law, Jason; Lazarus, Hillard M; LeMaistre, Charles; Olsson, Richard F; Pulsipher, Michael A; Savani, Bipin N; Schultz, Kirk R; Saad, Ayman A; Seftel, Matthew; Seo, Sachiko; Shea, Thomas C; Steinberg, Amir; Sullivan, Keith; Szwajcer, David; Wirk, Baldeep; Yared, Jean; Yong, Agnes; Dalal, Jignesh; Hahn, Theresa; Khera, Nandita; Bonfim, Carmem; Atsuta, Yoshiko; Saber, Wael

2018-03-19

For patients with acute lymphoblastic leukemia (ALL), allogeneic hematopoietic cell transplantation (alloHCT) offers a potential cure. Life-threatening complications can arise from alloHCT that require the application of sophisticated health care delivery. The impact of country-level economic conditions on post-transplantation outcomes is not known. Our objective was to assess whether these variables were associated with outcomes for patients transplanted for ALL. Using data from the Center for Blood and Marrow Transplant Research, we included 11,261 patients who received a first alloHCT for ALL from 303 centers across 38 countries between the years of 2005 and 2013. Cox regression models were constructed using the following macroeconomic indicators as main effects: Gross national income per capita, health expenditure per capita, and Human Development Index (HDI). The outcome was overall survival at 100 days following transplantation. In each model, transplants performed within lower resourced environments were associated with inferior overall survival. In the model with the HDI as the main effect, transplants performed in the lowest HDI quartile (n = 697) were associated with increased hazard for mortality (hazard ratio, 2.42; 95% confidence interval, 1.64 to 3.57; P macroeconomic indices were associated with lower survival at 100 days after alloHCT for ALL. The reasons for this disparity require further investigation. Copyright © 2018 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

Amyloid Load in Fat Tissue Reflects Disease Severity and Predicts Survival in Amyloidosis

NARCIS (Netherlands)

Van Gameren, Ingrid I.; Hazenberg, Bouke P. C.; Bijzet, Johan; Haagsma, Elizabeth B.; Vellenga, Edo; Posthumus, Marcel D.; Jager, Pieter L.; Van Rijswijk, Martin H.

Objective. The severity of systemic amyloidosis is thought to be related to the extent of amyloid deposition. We studied whether amyloid load in fat tissue reflects disease severity and predicts survival. Methods. We studied all consecutive patients with systemic amyloidosis seen between January

Survival analysis for predictive factors of delay vaccination in Iranian children

Directory of Open Access Journals (Sweden)

Abolfazl Mohammadbeigi

2015-01-01

Full Text Available Background: Today, beside immunization coverage the age appropriate vaccination is another helpful index in public health. Evidences have shown that high immunization coverage rates do not necessarily imply age-appropriate vaccination status. The current study aimed to show the predictive factors of delayed vaccination by survival models. Methods: A historical cohort study conducted on 3610 children aged between 24 and 47 months who was living in the suburbs of five big cities of Iran. Time of delay in vaccination of first dose of mumps-measles-rubella (MMR was calculated from date of vaccination minus age appropriate time according to vaccine card. Kaplan-Maier and Log rank tests were used for comparison the median of delay time. For controlling of confounding variables, multivariate cox model was used and hazard ratio with 95% confidence interval (95% was reported. Results: The mean ± standard deviation and median interquartile range of delay time was 38.34 ± 73.1 and 16 (11-31 days in delayed group. The Log rank test showed that city of living, nationality, parents′ education, and birth order are related with prolonged delay time in MMR vaccination (P 0.05. Cox regression showed that city of living, mother education, and nationality are the most predictive factors of delay time duration in MMR vaccination. Conclusions: Delay time duration of vaccination increased by faring from capital to the east south. Moreover, concentration of foreign immigrants in big cities and low level of mother education are the most predictors of delayed vaccination. Educational intervention should focus on immigrants and mothers with low education level.

Stimulated monocyte IL-6 secretion predicts survival of patients with head and neck squamous cell carcinoma

International Nuclear Information System (INIS)

Heimdal, John-Helge; Kross, Kenneth; Klementsen, Beate; Olofsson, Jan; Aarstad, Hans Jørgen

2008-01-01

This study was performed in order to determine whether monocyte in vitro function is associated with presence, stage and prognosis of head and neck squamous cell carcinoma (HNSCC) disease. Prospective study describing outcome, after at least five years observation, of patients treated for HNSCC disease in relation to their monocyte function. Sixty-five patients with newly diagnosed HNSCC and eighteen control patients were studied. Monocyte responsiveness was assessed by measuring levels of monocyte in vitro interleukin (IL)-6 and monocyte chemotactic peptide (MCP)-1 secretion after 24 hours of endotoxin stimulation in cultures supplied either with 20% autologous serum (AS) or serum free medium (SFM). Survival, and if relevant, cause of death, was determined at least 5 years following primary diagnosis. All patients, as a group, had higher in vitro monocyte responsiveness in terms of IL-6 (AS) (t = 2.03; p < 0.05) and MCP-1 (SFM) (t = 2.49; p < 0.05) compared to controls. Increased in vitro monocyte IL-6 endotoxin responsiveness under the SFM condition was associated with decreased survival rate (Hazard ratio (HR) = 2.27; Confidence interval (CI) = 1.05–4.88; p < 0.05). The predictive value of monocyte responsiveness, as measured by IL-6, was also retained when adjusted for age, gender and disease stage of patients (HR = 2.67; CI = 1.03–6.92; p < 0.05). With respect to MCP-1, low endotoxin-stimulated responsiveness (AS), analysed by Kaplan-Meier method, predicted decreased survival (χ = 4.0; p < 0.05). In HNSCC patients, changed monocyte in vitro response to endotoxin, as measured by increased IL-6 (SFM) and decreased MCP-1 (AS) responsiveness, are negative prognostic factors

A nomogram to predict the survival of stage IIIA-N2 non-small cell lung cancer after surgery.

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Mao, Qixing; Xia, Wenjie; Dong, Gaochao; Chen, Shuqi; Wang, Anpeng; Jin, Guangfu; Jiang, Feng; Xu, Lin

2018-04-01

Postoperative survival of patients with stage IIIA-N2 non-small cell lung cancer (NSCLC) is highly heterogeneous. Here, we aimed to identify variables associated with postoperative survival and develop a tool for survival prediction. A retrospective review was performed in the Surveillance, Epidemiology, and End Results database from January 2004 to December 2009. Significant variables were selected by use of the backward stepwise method. The nomogram was constructed with multivariable Cox regression. The model's performance was evaluated by concordance index and calibration curve. The model was validated via an independent cohort from the Jiangsu Cancer Hospital Lung Cancer Center. A total of 1809 patients with stage IIIA-N2 NSCLC who underwent surgery were included in the training cohort. Age, sex, grade, histology, tumor size, visceral pleural invasion, positive lymph nodes, lymph nodes examined, and surgery type (lobectomy vs pneumonectomy) were identified as significant prognostic variables using backward stepwise method. A nomogram was developed from the training cohort and validated using an independent Chinese cohort. The concordance index of the model was 0.673 (95% confidence interval, 0.654-0.692) in training cohort and 0.664 in validation cohort (95% confidence interval, 0.614-0.714). The calibration plot showed optimal consistency between nomogram predicted survival and observed survival. Survival analyses demonstrated significant differences between different subgroups stratified by prognostic scores. This nomogram provided the individual survival prediction for patients with stage IIIA-N2 NSCLC after surgery, which might benefit survival counseling for patients and clinicians, clinical trial design and follow-up, as well as postoperative strategy-making. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

L-Dopa decarboxylase (DDC) constitutes an emerging biomarker in predicting patients' survival with stomach adenocarcinomas.

Science.gov (United States)

Florou, Dimitra; Papadopoulos, Iordanis N; Fragoulis, Emmanuel G; Scorilas, Andreas

2013-02-01

Stomach adenocarcinoma represents a major health problem and is regarded as the second commonest cause of cancer-associated mortality, universally, since it is still difficult to be perceived at a curable stage. Several lines of evidence have pointed out that the expression of L-Dopa decarboxylase (DDC) gene and/or protein becomes distinctively modulated in several human neuroendocrine neoplasms as well as adenocarcinomas. In order to elucidate the clinical role of DDC on primary gastric adenocarcinomas, we determined qualitatively and quantitatively the mRNA levels of the gene with regular PCR and real-time PCR by using the comparative threshold cycle method, correspondingly, and detected the expression of DDC protein by immunoblotting in cancerous and normal stomach tissue specimens. A statistically significant association was disclosed between DDC expression and gastric intestinal histotype as well as tumor localization at the distal third part of the stomach (p = 0.025 and p = 0.029, respectively). Univariate and multivariate analyses highlighted the powerful prognostic importance of DDC in relation to disease-free survival and overall survival of gastric cancer patients. According to Kaplan-Meier curves, the relative risk of relapse was found to be decreased in DDC-positive (p = 0.031) patients who, also, exhibited higher overall survival rates (p = 0.016) than those with DDC-negative tumors. This work is the first to shed light on the potential clinical usefulness of DDC, as an efficient tumor biomarker in gastric cancer. The provided evidence underlines the propitious predictive value of DDC expression in the survival of stomach adenocarcinoma patients.

Serum CA125 predicts extrauterine disease and survival in uterine carcinosarcoma

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Huang, Gloria S.; Chiu, Lydia G.; Gebb, Juliana S.; Gunter, Marc J.; Sukumvanich, Paniti; Goldberg, Gary L.; Einstein, Mark H.

2009-01-01

Objective The purpose of this study was to determine the clinical utility of CA125 measurement in patients with uterine carcinosarcoma (CS). Methods Ninety-five consecutive patients treated for CS at a single institution were identified. All 54 patients who underwent preoperative CA125 measurement were included in the study. Data were abstracted from the medical records. Tests of association between preoperative CA125 and previously identified clinicopathologic prognostic factors were performed using Fisher’s exact test and Pearson chi-square test. To evaluate relationship of CA125 elevation and survival, a Cox proportional hazard model was used for multivariate analysis, incorporating all of prognostic factors identified by univariate analysis. Results Preoperative CA125 was significantly associated with the presence of extrauterine disease (P<0.001), deep myometrial invasion (P<0.001), and serous histology of the epithelial component (P=0.005). Using univariate survival analysis, stage (HR=1.808, P=0.004), postoperative CA125 level (HR=9.855, P<0.001), and estrogen receptor positivity (HR=0.314, P=0.029) were significantly associated with survival. In the multivariate model, only postoperative CA125 level remained significantly associated with poor survival (HR=5.725, P=0.009). Conclusion Preoperative CA125 elevation is a marker of extrauterine disease and deep myometrial invasion in patients with uterine CS. Postoperative CA125 elevation is an independent prognostic factor for poor survival. These findings indicate that CA125 may be a clinically useful serum marker in the management of patients with CS. PMID:17935762

High endothelin-converting enzyme-1 expression independently predicts poor survival of patients with esophageal squamous cell carcinoma.

Science.gov (United States)

Wu, Ching-Fang; Lee, Ching-Tai; Kuo, Yao-Hung; Chen, Tzu-Haw; Chang, Chi-Yang; Chang, I-Wei; Wang, Wen-Lun

2017-09-01

Patients with esophageal squamous cell carcinoma have poor survival and high recurrence rate, thus an effective prognostic biomarker is needed. Endothelin-converting enzyme-1 is responsible for biosynthesis of endothelin-1, which promotes growth and invasion of human cancers. The role of endothelin-converting enzyme-1 in esophageal squamous cell carcinoma is still unknown. Therefore, this study investigated the significance of endothelin-converting enzyme-1 expression in esophageal squamous cell carcinoma clinically. We enrolled patients with esophageal squamous cell carcinoma who provided pretreated tumor tissues. Tumor endothelin-converting enzyme-1 expression was evaluated by immunohistochemistry and was defined as either low or high expression. Then we evaluated whether tumor endothelin-converting enzyme-1 expression had any association with clinicopathological findings or predicted survival of patients with esophageal squamous cell carcinoma. Overall, 54 of 99 patients with esophageal squamous cell carcinoma had high tumor endothelin-converting enzyme-1 expression, which was significantly associated with lymph node metastasis ( p = 0.04). In addition, tumor endothelin-converting enzyme-1 expression independently predicted survival of patients with esophageal squamous cell carcinoma, and the 5-year survival was poorer in patients with high tumor endothelin-converting enzyme-1 expression ( p = 0.016). Among patients with locally advanced and potentially resectable esophageal squamous cell carcinoma (stage II and III), 5-year survival was poorer with high tumor endothelin-converting enzyme-1 expression ( p = 0.003). High tumor endothelin-converting enzyme-1 expression also significantly predicted poorer survival of patients in this population. In patients with esophageal squamous cell carcinoma, high tumor endothelin-converting enzyme-1 expression might indicate high tumor invasive property. Therefore, tumor endothelin-converting enzyme-1 expression

Increased tumour ADC value during chemotherapy predicts improved survival in unresectable pancreatic cancer

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Nishiofuku, Hideyuki; Tanaka, Toshihiro; Kichikawa, Kimihiko [Nara Medical University, Department of Radiology and IVR Center, Kashihara-city, Nara (Japan); Marugami, Nagaaki [Nara Medical University, Department of Endoscopy and Ultrasound, Kashihara-city, Nara (Japan); Sho, Masayuki; Akahori, Takahiro; Nakajima, Yoshiyuki [Nara Medical University, Department of Surgery, Kashihara-city, Nara (Japan)

2016-06-15

To investigate whether changes to the apparent diffusion coefficient (ADC) of primary tumour in the early period after starting chemotherapy can predict progression-free survival (PFS) or overall survival (OS) in patients with unresectable pancreatic adenocarcinoma. Subjects comprised 43 patients with histologically confirmed unresectable pancreatic cancer treated with first-line chemotherapy. Minimum ADC values in primary tumour were measured using the selected area ADC (sADC), which excluded cystic and necrotic areas and vessels, and the whole tumour ADC (wADC), which included whole tumour components. Relative changes in ADC were calculated from baseline to 4 weeks after initiation of chemotherapy. Relationships between ADC and both PFS and OS were modelled by Cox proportional hazards regression. Median PFS and OS were 6.1 and 11.0 months, respectively. In multivariate analysis, sADC change was the strongest predictor of PFS (hazard ratio (HR), 4.5; 95 % confidence interval (CI), 1.7-11.9; p = 0.002). Multivariate Cox regression analysis for OS revealed sADC change and CRP as independent predictive markers, with sADC change as the strongest predictive biomarker (HR, 6.7; 95 % CI, 2.7-16.6; p = 0.001). Relative changes in sADC could provide a useful imaging biomarker to predict PFS and OS with chemotherapy for unresectable pancreatic adenocarcinoma. (orig.)

Hemoglobin levels do not predict biochemical outcome for localized prostate cancer treated with neoadjuvant androgen-suppression therapy and external-beam radiotherapy

International Nuclear Information System (INIS)

Pai, Howard Huaihan; Ludgate, Charles; Pickles, Tom; Paltiel, Chuck M.Sc.; Agranovich, Alex; Berthelet, Eric; Duncan, Graeme; Kim-Sing, Charmaine; Kwan, Winkle; Lim, Jan; Liu, Mitchell; Tyldesley, Scott

2006-01-01

Purpose: To investigate whether hemoglobin (Hb) levels affect outcome in men with localized prostate adenocarcinoma (LPA) treated with neoadjuvant androgen-suppression therapy (NAST) and external-beam radiotherapy (EBRT). Methods and Materials: A total of 563 men with LPA treated with NAST (median: 5.3 months) and EBRT who had Hb levels during treatment were retrospectively reviewed. Patient, tumor, and treatment variables, including the following Hb variables, were subjected to univariate and multivariable analyses to identify factors that predict biochemical control (bNED) and overall survival (OS): pre-EBRT Hb, Hb nadir during EBRT, and change in Hb from pre-EBRT to nadir during EBRT. Results: Median PSA follow-up was 4.25 years. Forty-nine percent of men were anemic during EBRT, with a median Hb of 13.4 g/dL, and 68% experienced a decline in Hb from pre-EBRT to during EBRT of median 0.6 g/dL. Five-year Nadir + 2 bNED and OS rates were similar for anemic and nonanemic patients during EBRT. High percent-positive biopsies, PSA and Gleason score, and use of AA monotherapy predicted worse bNED. High stage and age predicted worse OS. Hb variables were not predictive of bNED or OS. Conclusions: Anemia is a common side effect of NAST and is usually mild. Hb levels, however, do not predict biochemical control or survival

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.

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.

A scoring system based on artificial neural network for predicting 10-year survival in stage II A colon cancer patients after radical surgery

Science.gov (United States)

Jiang, Wu; Lu, Shi-Xun; Lu, Zhen-Hai; Li, Pei-Xing; Yun, Jing-Ping; Zhang, Rong-Xin; Pan, Zhi-Zhong; Wan, De-Sen

2016-01-01

Nearly 20% patients with stage II A colon cancer will develop recurrent disease post-operatively. The present study aims to develop a scoring system based on Artificial Neural Network (ANN) model for predicting 10-year survival outcome. The clinical and molecular data of 117 stage II A colon cancer patients from Sun Yat-sen University Cancer Center were used for training set and test set; poor pathological grading (score 49), reduced expression of TGFBR2 (score 33), over-expression of TGF-β (score 45), MAPK (score 32), pin1 (score 100), β-catenin in tumor tissue (score 50) and reduced expression of TGF-β in normal mucosa (score 22) were selected as the prognostic risk predictors. According to the developed scoring system, the patients were divided into 3 subgroups, which were supposed with higher, moderate and lower risk levels. As a result, for the 3 subgroups, the 10-year overall survival (OS) rates were 16.7%, 62.9% and 100% (P < 0.001); and the 10-year disease free survival (DFS) rates were 16.7%, 61.8% and 98.8% (P < 0.001) respectively. It showed that this scoring system for stage II A colon cancer could help to predict long-term survival and screen out high-risk individuals for more vigorous treatment. PMID:27008710

A scoring system based on artificial neural network for predicting 10-year survival in stage II A colon cancer patients after radical surgery.

Science.gov (United States)

Peng, Jian-Hong; Fang, Yu-Jing; Li, Cai-Xia; Ou, Qing-Jian; Jiang, Wu; Lu, Shi-Xun; Lu, Zhen-Hai; Li, Pei-Xing; Yun, Jing-Ping; Zhang, Rong-Xin; Pan, Zhi-Zhong; Wan, De Sen

2016-04-19

Nearly 20% patients with stage II A colon cancer will develop recurrent disease post-operatively. The present study aims to develop a scoring system based on Artificial Neural Network (ANN) model for predicting 10-year survival outcome. The clinical and molecular data of 117 stage II A colon cancer patients from Sun Yat-sen University Cancer Center were used for training set and test set; poor pathological grading (score 49), reduced expression of TGFBR2 (score 33), over-expression of TGF-β (score 45), MAPK (score 32), pin1 (score 100), β-catenin in tumor tissue (score 50) and reduced expression of TGF-β in normal mucosa (score 22) were selected as the prognostic risk predictors. According to the developed scoring system, the patients were divided into 3 subgroups, which were supposed with higher, moderate and lower risk levels. As a result, for the 3 subgroups, the 10-year overall survival (OS) rates were 16.7%, 62.9% and 100% (P < 0.001); and the 10-year disease free survival (DFS) rates were 16.7%, 61.8% and 98.8% (P < 0.001) respectively. It showed that this scoring system for stage II A colon cancer could help to predict long-term survival and screen out high-risk individuals for more vigorous treatment.

[11C]Choline PET/CT predicts survival in hormone-naive prostate cancer patients with biochemical failure after radical prostatectomy

International Nuclear Information System (INIS)

Giovacchini, Giampiero; Incerti, Elena; Mapelli, Paola; Gianolli, Luigi; Picchio, Maria; Kirienko, Margarita; Briganti, Alberto; Gandaglia, Giorgio; Montorsi, Francesco

2015-01-01

Over the last decade, PET/CT with radiolabelled choline has been shown to be useful for restaging patients with prostate cancer (PCa) who develop biochemical failure. The limitations of most clinical studies have been poor validation of [ 11 C]choline PET/CT-positive findings and lack of survival analysis. The aim of this study was to assess whether [ 11 C]choline PET/CT can predict survival in hormone-naive PCa patients with biochemical failure. This retrospective study included 302 hormone-naive PCa patients treated with radical prostatectomy who underwent [ 11 C]choline PET/CT from 1 December 2004 to 31 July 2007 because of biochemical failure (prostate-specific antigen, PSA, >0.2 ng/mL). Median PSA was 1.02 ng/mL. PCa-specific survival was estimated using Kaplan-Meier curves. Cox regression analysis was used to evaluate the association between clinicopathological variables and PCa-specific survival. The coefficients of the covariates included in the Cox regression analysis were used to develop a novel nomogram. Median follow-up was 7.2 years (1.4 - 18.9 years). [ 11 C]Choline PET/CT was positive in 101 of 302 patients (33 %). Median PCa-specific survival after prostatectomy was 14.9 years (95 % CI 9.7 - 20.1 years) in patients with positive [ 11 C]choline PET/CT. Median survival was not achieved in patients with negative [ 11 C]choline PET/CT. The 15-year PCa-specific survival probability was 42.4 % (95 % CI 31.7 - 53.1 %) in patients with positive [ 11 C]choline PET/CT and 95.5 % (95 % CI 93.5 - 97.5 %) in patients with negative [ 11 C]choline PET/CT. In multivariate analysis, [ 11 C]choline PET/CT (hazard ratio 6.36, 95 % CI 2.14 - 18.94, P < 0.001) and Gleason score >7 (hazard ratio 3.11, 95 % CI 1.11 - 8.66, P = 0.030) predicted PCa-specific survival. An internally validated nomogram predicted 15-year PCa-specific survival probability with an accuracy of 80 %. Positive [ 11 C]choline PET/CT after biochemical failure predicts PCa-specific survival in hormone

Pleural Fluid Adenosine Deaminase (ADA) Predicts Survival in Patients with Malignant Pleural Effusion.

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Terra, Ricardo Mingarini; Antonangelo, Leila; Mariani, Alessandro Wasum; de Oliveira, Ricardo Lopes Moraes; Teixeira, Lisete Ribeiro; Pego-Fernandes, Paulo Manuel

2016-08-01

Systemic and local inflammations have been described as relevant prognostic factors in patients with cancer. However, parameters that stand for immune activity in the pleural space have not been tested as predictors of survival in patients with malignant pleural effusion. The objective of this study was to evaluate pleural lymphocytes and Adenosine Deaminase (ADA) as predictors of survival in patients with recurrent malignant pleural effusion. Retrospective cohort study includes patients who underwent pleurodesis for malignant pleural effusion in a tertiary center. Pleural fluid protein concentration, lactate dehydrogenase, glucose, oncotic cytology, cell count, and ADA were collected before pleurodesis and analyzed. Survival analysis was performed considering pleurodesis as time origin, and death as the event. Backwards stepwise Cox regression was used to find predictors of survival. 156 patients (out of 196 potentially eligible) were included in this study. Most were female (72 %) and breast cancer was the most common underlying malignancy (53 %). Pleural fluid ADA level was stratified as low (Pleural fluid cell count and lymphocytes number and percentage did not correlate with survival. Pleural fluid Adenosine Deaminase levels (pleural effusion who undergo pleurodesis.

Development of a predictive model for 6 month survival in patients with venous thromboembolism and solid malignancy requiring IVC filter placement.

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Huang, Steven Y; Odisio, Bruno C; Sabir, Sharjeel H; Ensor, Joe E; Niekamp, Andrew S; Huynh, Tam T; Kroll, Michael; Gupta, Sanjay

2017-07-01

Our purpose was to develop a predictive model for short-term survival (i.e. filter placement in patients with venous thromboembolism (VTE) and solid malignancy. Clinical and laboratory parameters were retrospectively reviewed for patients with solid malignancy who received a filter between January 2009 and December 2011 at a tertiary care cancer center. Multivariate Cox proportional hazards modeling was used to assess variables associated with 6 month survival following filter placement in patients with VTE and solid malignancy. Significant variables were used to generate a predictive model. 397 patients with solid malignancy received a filter during the study period. Three variables were associated with 6 month survival: (1) serum albumin [hazard ratio (HR) 0.496, P filter placement can be predicted from three patient variables. Our predictive model could be used to help physicians decide whether a permanent or retrievable filter may be more appropriate as well as to assess the risks and benefits for filter retrieval within the context of survival longevity in patients with cancer.

Survivin gene levels in the peripheral blood of patients with gastric cancer independently predict survival

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Scalerta Romano

2009-12-01

Full Text Available Abstract Background The detection of circulating tumor cells (CTC is considered a promising tool for improving risk stratification in patients with solid tumors. We investigated on whether the expression of CTC related genes adds any prognostic power to the TNM staging system in patients with gastric carcinoma. Methods Seventy patients with TNM stage I to IV gastric carcinoma were retrospectively enrolled. Peripheral blood samples were tested by means of quantitative real time PCR (qrtPCR for the expression of four CTC related genes: carcinoembryonic antigen (CEA, cytokeratin-19 (CK19, vascular endothelial growth factor (VEGF and Survivin (BIRC5. Results Gene expression of Survivin, CK19, CEA and VEGF was higher than in normal controls in 98.6%, 97.1%, 42.9% and 38.6% of cases, respectively, suggesting a potential diagnostic value of both Survivin and CK19. At multivariable survival analysis, TNM staging and Survivin mRNA levels were retained as independent prognostic factors, demonstrating that Survivin expression in the peripheral blood adds prognostic information to the TNM system. In contrast with previously published data, the transcript abundance of CEA, CK19 and VEGF was not associated with patients' clinical outcome. Conclusions Gene expression levels of Survivin add significant prognostic value to the current TNM staging system. The validation of these findings in larger prospective and multicentric series might lead to the implementation of this biomarker in the routine clinical setting in order to optimize risk stratification and ultimately personalize the therapeutic management of these patients.

Immune-mediated change in the expression of a sexual trait predicts offspring survival in the wild.

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Rémi Chargé

Full Text Available BACKGROUND: The "good genes" theory of sexual selection postulates that females choose mates that will improve their offspring's fitness through the inheritance of paternal genes. In spite of the attention that this hypothesis has given rise to, the empirical evidence remains sparse, mostly because of the difficulties of controlling for the many environmental factors that may covary with both the paternal phenotype and offspring fitness. Here, we tested the hypothesis that offspring sired by males of a preferred phenotype should have better survival in an endangered bird, the houbara bustard (Chlamydotis undulata undulata. METHODOLOGY/PRINCIPAL FINDINGS: We tested if natural and experimentally-induced variation in courtship display (following an inflammatory challenge predicts the survival of offspring. Chicks were produced by artificial insemination of females, ensuring that any effect on survival could only arise from the transfer of paternal genes. One hundred and twenty offspring were equipped with radio transmitters, and their survival monitored in the wild for a year. This allowed assessment of the potential benefits of paternal genes in a natural setting, where birds experience the whole range of environmental hazards. Although natural variation in sire courtship display did not predict offspring survival, sires that withstood the inflammatory insult and maintained their courtship activity sired offspring with the best survival upon release. CONCLUSIONS: This finding is relevant both to enlighten the debate on "good genes" sexual selection and the management of supportive breeding programs.

Bayesian Decision Trees for predicting survival of patients: a study on the US National Trauma Data Bank.

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Schetinin, Vitaly; Jakaite, Livia; Jakaitis, Janis; Krzanowski, Wojtek

2013-09-01

Trauma and Injury Severity Score (TRISS) models have been developed for predicting the survival probability of injured patients the majority of which obtain up to three injuries in six body regions. Practitioners have noted that the accuracy of TRISS predictions is unacceptable for patients with a larger number of injuries. Moreover, the TRISS method is incapable of providing accurate estimates of predictive density of survival, that are required for calculating confidence intervals. In this paper we propose Bayesian inference for estimating the desired predictive density. The inference is based on decision tree models which split data along explanatory variables, that makes these models interpretable. The proposed method has outperformed the TRISS method in terms of accuracy of prediction on the cases recorded in the US National Trauma Data Bank. The developed method has been made available for evaluation purposes as a stand-alone application. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Discrimination measures for survival outcomes: connection between the AUC and the predictiveness curve.

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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.

Can survival prediction be improved by merging gene expression data sets?

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Haleh Yasrebi

Full Text Available BACKGROUND: High-throughput gene expression profiling technologies generating a wealth of data, are increasingly used for characterization of tumor biopsies for clinical trials. By applying machine learning algorithms to such clinically documented data sets, one hopes to improve tumor diagnosis, prognosis, as well as prediction of treatment response. However, the limited number of patients enrolled in a single trial study limits the power of machine learning approaches due to over-fitting. One could partially overcome this limitation by merging data from different studies. Nevertheless, such data sets differ from each other with regard to technical biases, patient selection criteria and follow-up treatment. It is therefore not clear at all whether the advantage of increased sample size outweighs the disadvantage of higher heterogeneity of merged data sets. Here, we present a systematic study to answer this question specifically for breast cancer data sets. We use survival prediction based on Cox regression as an assay to measure the added value of merged data sets. RESULTS: Using time-dependent Receiver Operating Characteristic-Area Under the Curve (ROC-AUC and hazard ratio as performance measures, we see in overall no significant improvement or deterioration of survival prediction with merged data sets as compared to individual data sets. This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets. Surprisingly, we found that the overall best performance was achieved with a single-gene predictor consisting of CYB5D1. CONCLUSIONS: Merging did not deteriorate performance on average despite (a The diversity of microarray platforms used. (b The heterogeneity of patients cohorts. (c The heterogeneity of breast cancer disease. (d Substantial variation of time to death or relapse. (e The reduced number of genes in the merged data

A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis.

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Passamonti, F; Giorgino, T; Mora, B; Guglielmelli, P; Rumi, E; Maffioli, M; Rambaldi, A; Caramella, M; Komrokji, R; Gotlib, J; Kiladjian, J J; Cervantes, F; Devos, T; Palandri, F; De Stefano, V; Ruggeri, M; Silver, R T; Benevolo, G; Albano, F; Caramazza, D; Merli, M; Pietra, D; Casalone, R; Rotunno, G; Barbui, T; Cazzola, M; Vannucchi, A M

2017-12-01

Polycythemia vera (PV) and essential thrombocythemia (ET) are myeloproliferative neoplasms with variable risk of evolution into post-PV and post-ET myelofibrosis, from now on referred to as secondary myelofibrosis (SMF). No specific tools have been defined for risk stratification in SMF. To develop a prognostic model for predicting survival, we studied 685 JAK2, CALR, and MPL annotated patients with SMF. Median survival of the whole cohort was 9.3 years (95% CI: 8-not reached-NR-). Through penalized Cox regressions we identified negative predictors of survival and according to beta risk coefficients we assigned 2 points to hemoglobin level <11 g/dl, to circulating blasts ⩾3%, and to CALR-unmutated genotype, 1 point to platelet count <150 × 10 9 /l and to constitutional symptoms, and 0.15 points to any year of age. Myelofibrosis Secondary to PV and ET-Prognostic Model (MYSEC-PM) allocated SMF patients into four risk categories with different survival (P<0.0001): low (median survival NR; 133 patients), intermediate-1 (9.3 years, 95% CI: 8.1-NR; 245 patients), intermediate-2 (4.4 years, 95% CI: 3.2-7.9; 126 patients), and high risk (2 years, 95% CI: 1.7-3.9; 75 patients). Finally, we found that the MYSEC-PM represents the most appropriate tool for SMF decision-making to be used in clinical and trial settings.

PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

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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.

SU-E-T-131: Artificial Neural Networks Applied to Overall Survival Prediction for Patients with Periampullary Carcinoma

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Gong, Y; Yu, J; Yeung, V; Palmer, J; Yu, Y; Lu, B; Babinsky, L; Burkhart, R; Leiby, B; Siow, V; Lavu, H; Rosato, E; Winter, J; Lewis, N; Sama, A; Mitchell, E; Anne, P; Hurwitz, M; Yeo, C; Bar-Ad, V [Thomas Jefferson University Hospital, Philadelphia, PA (United States); and others

2015-06-15

Purpose: Artificial neural networks (ANN) can be used to discover complex relations within datasets to help with medical decision making. This study aimed to develop an ANN method to predict two-year overall survival of patients with peri-ampullary cancer (PAC) following resection. Methods: Data were collected from 334 patients with PAC following resection treated in our institutional pancreatic tumor registry between 2006 and 2012. The dataset contains 14 variables including age, gender, T-stage, tumor differentiation, positive-lymph-node ratio, positive resection margins, chemotherapy, radiation therapy, and tumor histology.After censoring for two-year survival analysis, 309 patients were left, of which 44 patients (∼15%) were randomly selected to form testing set. The remaining 265 cases were randomly divided into training set (211 cases, ∼80% of 265) and validation set (54 cases, ∼20% of 265) for 20 times to build 20 ANN models. Each ANN has one hidden layer with 5 units. The 20 ANN models were ranked according to their concordance index (c-index) of prediction on validation sets. To further improve prediction, the top 10% of ANN models were selected, and their outputs averaged for prediction on testing set. Results: By random division, 44 cases in testing set and the remaining 265 cases have approximately equal two-year survival rates, 36.4% and 35.5% respectively. The 20 ANN models, which were trained and validated on the 265 cases, yielded mean c-indexes as 0.59 and 0.63 on validation sets and the testing set, respectively. C-index was 0.72 when the two best ANN models (top 10%) were used in prediction on testing set. The c-index of Cox regression analysis was 0.63. Conclusion: ANN improved survival prediction for patients with PAC. More patient data and further analysis of additional factors may be needed for a more robust model, which will help guide physicians in providing optimal post-operative care. This project was supported by PA CURE Grant.

SU-E-T-131: Artificial Neural Networks Applied to Overall Survival Prediction for Patients with Periampullary Carcinoma

International Nuclear Information System (INIS)

Gong, Y; Yu, J; Yeung, V; Palmer, J; Yu, Y; Lu, B; Babinsky, L; Burkhart, R; Leiby, B; Siow, V; Lavu, H; Rosato, E; Winter, J; Lewis, N; Sama, A; Mitchell, E; Anne, P; Hurwitz, M; Yeo, C; Bar-Ad, V

2015-01-01

Purpose: Artificial neural networks (ANN) can be used to discover complex relations within datasets to help with medical decision making. This study aimed to develop an ANN method to predict two-year overall survival of patients with peri-ampullary cancer (PAC) following resection. Methods: Data were collected from 334 patients with PAC following resection treated in our institutional pancreatic tumor registry between 2006 and 2012. The dataset contains 14 variables including age, gender, T-stage, tumor differentiation, positive-lymph-node ratio, positive resection margins, chemotherapy, radiation therapy, and tumor histology.After censoring for two-year survival analysis, 309 patients were left, of which 44 patients (∼15%) were randomly selected to form testing set. The remaining 265 cases were randomly divided into training set (211 cases, ∼80% of 265) and validation set (54 cases, ∼20% of 265) for 20 times to build 20 ANN models. Each ANN has one hidden layer with 5 units. The 20 ANN models were ranked according to their concordance index (c-index) of prediction on validation sets. To further improve prediction, the top 10% of ANN models were selected, and their outputs averaged for prediction on testing set. Results: By random division, 44 cases in testing set and the remaining 265 cases have approximately equal two-year survival rates, 36.4% and 35.5% respectively. The 20 ANN models, which were trained and validated on the 265 cases, yielded mean c-indexes as 0.59 and 0.63 on validation sets and the testing set, respectively. C-index was 0.72 when the two best ANN models (top 10%) were used in prediction on testing set. The c-index of Cox regression analysis was 0.63. Conclusion: ANN improved survival prediction for patients with PAC. More patient data and further analysis of additional factors may be needed for a more robust model, which will help guide physicians in providing optimal post-operative care. This project was supported by PA CURE Grant

Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression

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Shahrbanoo Goli

2016-01-01

Full Text Available The Support Vector Regression (SVR model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature selection methods: combination of SVR and statistical tests, univariate feature selection based on concordance index, and recursive feature elimination. The evaluations are performed using available medical datasets and also a Breast Cancer (BC dataset consisting of 573 patients who visited the Oncology Clinic of Hamadan province in Iran. Results show that, for the BC dataset, survival time can be predicted more accurately by linear SVR than nonlinear SVR. Based on the three feature selection methods, metastasis status, progesterone receptor status, and human epidermal growth factor receptor 2 status are the best features associated to survival. Also, according to the obtained results, performance of linear and nonlinear kernels is comparable. The proposed SVR model performs similar to or slightly better than other models. Also, SVR performs similar to or better than Cox when all features are included in model.

Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer.

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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.

Prediction With Dimension Reduction of Multiple Molecular Data Sources for Patient Survival

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Adam Kaplan

2017-07-01

Full Text Available Predictive modeling from high-dimensional genomic data is often preceded by a dimension reduction step, such as principal component analysis (PCA. However, the application of PCA is not straightforward for multisource data, wherein multiple sources of ‘omics data measure different but related biological components. In this article, we use recent advances in the dimension reduction of multisource data for predictive modeling. In particular, we apply exploratory results from Joint and Individual Variation Explained (JIVE, an extension of PCA for multisource data, for prediction of differing response types. We conduct illustrative simulations to illustrate the practical advantages and interpretability of our approach. As an application example, we consider predicting survival for patients with glioblastoma multiforme from 3 data sources measuring messenger RNA expression, microRNA expression, and DNA methylation. We also introduce a method to estimate JIVE scores for new samples that were not used in the initial dimension reduction and study its theoretical properties; this method is implemented in the R package R.JIVE on CRAN, in the function jive.predict.

SNRFCB: sub-network based random forest classifier for predicting chemotherapy benefit on survival for cancer treatment.

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Shi, Mingguang; He, Jianmin

2016-04-01

Adjuvant chemotherapy (CTX) should be individualized to provide potential survival benefit and avoid potential harm to cancer patients. Our goal was to establish a computational approach for making personalized estimates of the survival benefit from adjuvant CTX. We developed Sub-Network based Random Forest classifier for predicting Chemotherapy Benefit (SNRFCB) based gene expression datasets of lung cancer. The SNRFCB approach was then validated in independent test cohorts for identifying chemotherapy responder cohorts and chemotherapy non-responder cohorts. SNRFCB involved the pre-selection of gene sub-network signatures based on the mutations and on protein-protein interaction data as well as the application of the random forest algorithm to gene expression datasets. Adjuvant CTX was significantly associated with the prolonged overall survival of lung cancer patients in the chemotherapy responder group (P = 0.008), but it was not beneficial to patients in the chemotherapy non-responder group (P = 0.657). Adjuvant CTX was significantly associated with the prolonged overall survival of lung cancer squamous cell carcinoma (SQCC) subtype patients in the chemotherapy responder cohorts (P = 0.024), but it was not beneficial to patients in the chemotherapy non-responder cohorts (P = 0.383). SNRFCB improved prediction performance as compared to the machine learning method, support vector machine (SVM). To test the general applicability of the predictive model, we further applied the SNRFCB approach to human breast cancer datasets and also observed superior performance. SNRFCB could provide recurrent probability for individual patients and identify which patients may benefit from adjuvant CTX in clinical trials.

Diagnostic performance of initial serum albumin level for predicting in-hospital mortality among aspiration pneumonia patients.

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Kim, Hyosun; Jo, Sion; Lee, Jae Baek; Jin, Youngho; Jeong, Taeoh; Yoon, Jaechol; Lee, Jeong Moon; Park, Boyoung

2018-01-01

The predictive value of serum albumin in adult aspiration pneumonia patients remains unknown. Using data collected during a 3-year retrospective cohort of hospitalized adult patients with aspiration pneumonia, we evaluated the predictive value of serum albumin level at ED presentation for in-hospital mortality. 248 Patients were enrolled; of these, 51 cases died (20.6%). The mean serum albumin level was 3.4±0.7g/dL and serum albumin levels were significantly lower in the non-survivor group than in the survivor group (3.0±0.6g/dL vs. 3.5±0.6g/dL). In the multivariable logistic regression model, albumin was associated with in-hospital mortality significantly (adjusted odds ratio 0.30, 95% confidential interval (CI) 0.16-0.57). The area under the receiver operating characteristics (AUROC) for in-hospital survival was 0.72 (95% CI 0.64-0.80). The Youden index was 3.2g/dL and corresponding sensitivity, specificity, positive predictive value, negative predictive value, positive and negative likelihood ratio were 68.6%, 66.5%, 34.7%, 89.1%, 2.05 and 0.47, respectively. High sensitivity (98.0%) was shown at albumin level of 4.0g/dL and high specificity (94.9%) was shown at level of 2.5g/dL. Initial serum albumin levels were independently associated with in-hospital mortality among adult patients hospitalized with aspiration pneumonia and demonstrated fair discriminative performance in the prediction of in-hospital mortality. Copyright © 2017 Elsevier Inc. All rights reserved.

Correlation between preoperative serum alpha-fetoprotein levels and survival with respect to the surgical treatment of hepatocellular carcinoma at a tertiary care hospital in Veracruz, Mexico

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G. Martínez-Mier

2017-10-01

Full Text Available Introduction: Preoperative serum alpha-fetoprotein levels can have predictive value for hepatocellular carcinoma survival. Aim: Our aim was to analyze the correlation between preoperative serum alpha-fetoprotein levels and survival, following the surgical treatment of hepatocellular carcinoma. Methods: Nineteen patients were prospectively followed (07/2005-01/2016. An ROC curve was created to determine the sensitivity and specificity of alpha-fetoprotein in relation to survival (Kaplan-Meier. Results: Of the 19 patients evaluated, 57.9% were men. The mean patient age was 68.1 ± 8.5 years and survival at 1, 3, and 5 years was 89.4, 55.9, and 55.9%. The alpha-fetoprotein cutoff point was 15.1 ng/ml (sensitivity 100%, specificity 99.23%. Preoperative alpha-fetoprotein levels below 15.1, 200, 400, and 463 ng/ml correlated with better 1 and 5-year survival rates than levels above 15.1, 200, 400, and 463 ng/ml (P<.05. Conclusions: Elevated preoperative serum alpha-fetoprotein levels have predictive value for hepatocellular carcinoma survival. Resumen: Introducción: Los niveles séricos de alfafetoproteína (AFP preoperatoria pueden tener valor predictivo para la sobrevida del hepatocarcinoma (HCC. Objetivo: Analizar la correlación entre los niveles séricos de AFP preoperatoria y la sobrevida posterior al tratamiento quirúrgico del HCC. Métodos: Diecinueve pacientes fueron seguidos prospectivamente (julio del 2005-enero del 2016. Se realizó una curva ROC para determinar la sensibilidad y la especificidad de la AFP con relación con la sobrevida (Kaplan-Meier. Resultados: Se evaluó a 19 pacientes, 57.9% hombres, edad media 68.1 ± 8.5 años con sobrevida a 1, 3 y 5 años del 89.4, el 55.9 y el 55.9%. El punto de corte de AFP fue 15.1 ng/ml (sensibilidad 100%, especificidad 99.23%. Los niveles preoperatorios de AFP menores de 15.1, 200, 400 y 463 ng/ml correlacionaron con mejor sobrevida a 1 y 5 años que niveles mayores de AFP (p < 0

Management of hepatocellular carcinoma: Predictive value of immunohistochemical markers for postoperative survival

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Niu, Zhao-Shan; Niu, Xiao-Jun; Wang, Mei

2015-01-01

Hepatocellular carcinoma (HCC) accounts for over 90% of all primary liver cancers. With an ever increasing incidence trend year by year, it has become the third most common cause of death from cancer worldwide. Hepatic resection is generally considered to be one of the most effective therapies for HCC patients, however, there is a high risk of recurrence in postoperative HCC. In clinical practice, there exists an urgent need for valid prognostic markers to identify patients with prognosis, hence the importance of studies on prognostic markers in improving the prediction of HCC prognosis. This review focuses on the most promising immunohistochemical prognostic markers in predicting the postoperative survival of HCC patients. PMID:25624992

Geographic remoteness, area-level socioeconomic disadvantage and inequalities in colorectal cancer survival in Queensland: a multilevel analysis

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2013-01-01

Background To explore the impact of geographical remoteness and area-level socioeconomic disadvantage on colorectal cancer (CRC) survival. Methods Multilevel logistic regression and Markov chain Monte Carlo simulations were used to analyze geographical variations in five-year all-cause and CRC-specific survival across 478 regions in Queensland Australia for 22,727 CRC cases aged 20–84 years diagnosed from 1997–2007. Results Area-level disadvantage and geographic remoteness were independently associated with CRC survival. After full multivariate adjustment (both levels), patients from remote (odds Ratio [OR]: 1.24, 95%CrI: 1.07-1.42) and more disadvantaged quintiles (OR = 1.12, 1.15, 1.20, 1.23 for Quintiles 4, 3, 2 and 1 respectively) had lower CRC-specific survival than major cities and least disadvantaged areas. Similar associations were found for all-cause survival. Area disadvantage accounted for a substantial amount of the all-cause variation between areas. Conclusions We have demonstrated that the area-level inequalities in survival of colorectal cancer patients cannot be explained by the measured individual-level characteristics of the patients or their cancer and remain after adjusting for cancer stage. Further research is urgently needed to clarify the factors that underlie the survival differences, including the importance of geographical differences in clinical management of CRC. PMID:24152961

Correlation of Creatine Kinase Levels with Clinical Features and Survival in Amyotrophic Lateral Sclerosis

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Hongfei Tai

2017-07-01

Full Text Available ObjectiveTo evaluate serum creatine kinase (CK levels of amyotrophic lateral sclerosis (ALS patients and to explore the relationship between CK levels and the clinical characteristics and survival prognosis of ALS patients.MethodsWe analyzed the CK levels of 185 ALS patients who underwent long-term follow-up. The relationship between CK levels and clinical features including sex, age, disease duration, site of onset, body mass index (BMI, serum creatinine (Cr, and spontaneous electromyographic activity was analyzed by univariate analysis and multiple linear regression. Kaplan–Meier and Cox proportional hazards models were used to explore whether CK levels were independently correlated with survival prognosis of ALS.ResultsBaseline serum CK was raised in 43% of participants. The median CK level was 160 U/L (range: 20–2,574 U/L, and 99% of patients had a baseline serum CK level less than 1,000 U/L. CK levels were significantly higher in male patients than in female patients [204 (169 versus 117 (111 U/L, p < 0.001] and in patients with limb onset ALS than with bulbar onset ALS (p < 0.001. CK levels were also correlated with serum Cr (p = 0.011 and the spontaneous potential score of electromyography (EMG (p = 0.037 but not correlated with age (p = 0.883, disease duration (p = 0.116, or BMI (p = 0.481. Log CK was independently correlated with survival of ALS patients (HR = 0.457, 95% confidence interval 0.221–0.947, p = 0.035 after adjusting for age, sex, site of onset, serum Cr, and BMI.ConclusionSerum CK levels of ALS patients were correlated with sex, site of onsite, serum Cr, and spontaneous activity in EMG. Serum CK could be an independent prognostic factor for survival of ALS patients.

Young patients with colorectal cancer have poor survival in the first twenty months after operation and predictable survival in the medium and long-term: Analysis of survival and prognostic markers

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Wickramarachchi RE

2010-09-01

Full Text Available Abstract Objectives This study compares clinico-pathological features in young (50 years with colorectal cancer, survival in the young and the influence of pre-operative clinical and histological factors on survival. Materials and methods A twelve year prospective database of colorectal cancer was analysed. Fifty-three young patients were compared with forty seven consecutive older patients over fifty years old. An analysis of survival was undertaken in young patients using Kaplan Meier graphs, non parametric methods, Cox's Proportional Hazard Ratios and Weibull Hazard models. Results Young patients comprised 13.4 percent of 397 with colorectal cancer. Duration of symptoms and presentation in the young was similar to older patients (median, range; young patients; 6 months, 2 weeks to 2 years, older patients; 4 months, 4 weeks to 3 years, p > 0.05. In both groups, the majority presented without bowel obstruction (young - 81%, older - 94%. Cancer proximal to the splenic flexure was present more in young than in older patients. Synchronous cancers were found exclusively in the young. Mucinous tumours were seen in 16% of young and 4% of older patients (p Conclusion If patients, who are less than 40 years old with colorectal cancer, survive twenty months after operation, the prognosis improves and their survival becomes predictable.

Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival.

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Megchelenbrink, Wout; Katzir, Rotem; Lu, Xiaowen; Ruppin, Eytan; Notebaart, Richard A

2015-09-29

Synthetic dosage lethality (SDL) denotes a genetic interaction between two genes whereby the underexpression of gene A combined with the overexpression of gene B is lethal. SDLs offer a promising way to kill cancer cells by inhibiting the activity of SDL partners of activated oncogenes in tumors, which are often difficult to target directly. As experimental genome-wide SDL screens are still scarce, here we introduce a network-level computational modeling framework that quantitatively predicts human SDLs in metabolism. For each enzyme pair (A, B) we systematically knock out the flux through A combined with a stepwise flux increase through B and search for pairs that reduce cellular growth more than when either enzyme is perturbed individually. The predictive signal of the emerging network of 12,000 SDLs is demonstrated in five different ways. (i) It can be successfully used to predict gene essentiality in shRNA cancer cell line screens. Moving to clinical tumors, we show that (ii) SDLs are significantly underrepresented in tumors. Furthermore, breast cancer tumors with SDLs active (iii) have smaller sizes and (iv) result in increased patient survival, indicating that activation of SDLs increases cancer vulnerability. Finally, (v) patient survival improves when multiple SDLs are present, pointing to a cumulative effect. This study lays the basis for quantitative identification of cancer SDLs in a model-based mechanistic manner. The approach presented can be used to identify SDLs in species and cell types in which "omics" data necessary for data-driven identification are missing.

Stathmin protein level, a potential predictive marker for taxane treatment response in endometrial cancer.

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Henrica M J Werner

Full Text Available Stathmin is a prognostic marker in many cancers, including endometrial cancer. Preclinical studies, predominantly in breast cancer, have suggested that stathmin may additionally be a predictive marker for response to paclitaxel. We first evaluated the response to paclitaxel in endometrial cancer cell lines before and after stathmin knock-down. Subsequently we investigated the clinical response to paclitaxel containing chemotherapy in metastatic endometrial cancer in relation to stathmin protein level in tumors. Stathmin level was also determined in metastatic lesions, analyzing changes in biomarker status on disease progression. Knock-down of stathmin improved sensitivity to paclitaxel in endometrial carcinoma cell lines with both naturally higher and lower sensitivity to paclitaxel. In clinical samples, high stathmin level was demonstrated to be associated with poor response to paclitaxel containing chemotherapy and to reduced disease specific survival only in patients treated with such combination. Stathmin level increased significantly from primary to metastatic lesions. This study suggests, supported by both preclinical and clinical data, that stathmin could be a predictive biomarker for response to paclitaxel treatment in endometrial cancer. Re-assessment of stathmin level in metastatic lesions prior to treatment start may be relevant. Also, validation in a randomized clinical trial will be important.

Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries.

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Jochems, Arthur; Deist, Timo M; El Naqa, Issam; Kessler, Marc; Mayo, Chuck; Reeves, Jackson; Jolly, Shruti; Matuszak, Martha; Ten Haken, Randall; van Soest, Johan; Oberije, Cary; Faivre-Finn, Corinne; Price, Gareth; de Ruysscher, Dirk; Lambin, Philippe; Dekker, Andre

2017-10-01

Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on a large volume of historical patient data and serves as a proof of concept to demonstrate the distributed learning approach. Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation or radiation therapy alone, were collected and stored at 2 different cancer institutes (559 patients at Maastro clinic (Netherlands) and 139 at Michigan university [United States]). The model was further validated on 196 patients originating from The Christie (United Kingdon). A Bayesian network model was adapted for distributed learning (the animation can be viewed at https://www.youtube.com/watch?v=ZDJFOxpwqEA). Two-year posttreatment survival was chosen as the endpoint. The Maastro clinic cohort data are publicly available at https://www.cancerdata.org/publication/developing-and-validating-survival-prediction-model-nsclc-patients-through-distributed, and the developed models can be found at www.predictcancer.org. Variables included in the final model were T and N category, age, performance status, and total tumor dose. The model has an area under the curve (AUC) of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross validation. A model based on the T and N category performed with an AUC of 0.47 on the validation set, significantly worse than our model (PLearning the model in a centralized or distributed fashion yields a minor difference on the probabilities of the conditional probability tables (0.6%); the discriminative performance of the models on the validation set is similar (P=.26). Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data-sharing barriers. We believe that

PIAS3 expression in squamous cell lung cancer is low and predicts overall survival

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Abbas, Rime; McColl, Karen S; Kresak, Adam; Yang, Michael; Chen, Yanwen; Fu, Pingfu; Wildey, Gary; Dowlati, Afshin

2015-01-01

Unlike lung adenocarcinoma, little progress has been made in the treatment of squamous cell lung carcinoma (SCC). The Cancer Genome Atlas (TCGA) has recently reported that receptor tyrosine kinase signaling pathways are altered in 26% of SCC tumors, validating the importance of downstream Signal Transducers and Activators of Transcription 3 (STAT3) activity as a prime therapeutic target in this cancer. In the present report we examine the status of an endogenous inhibitor of STAT3, called Protein Inhibitor of Activated STAT3 (PIAS3), in SCC and its potential role in this disease. We examine PIAS3 expression in SCC tumors and cell lines by immunohistochemistry of a tissue microarray and western blotting. PIAS3 mRNA expression and survival data are analyzed in the TCGA data set. SCC cell lines are treated with curcumin to regulate PIAS3 expression and cell growth. PIAS3 protein expression is decreased in a majority of lung SCC tumors and cell lines. Analysis of PIAS3 mRNA transcript levels demonstrated that low PIAS3 levels predicted poor survival; Cox regression analysis revealed a hazard ratio of 0.57 (95% CI: 0.37–0.87), indicating a decrease in the risk of death by 43% for every unit elevation in PIAS3 gene expression. Curcumin treatment increased endogenous PIAS3 expression and decreased cell growth and viability in Calu-1 cells, a model of SCC. Our results implicate PIAS3 loss in the pathology of lung SCC and raise the therapeutic possibility of upregulating PIAS3 expression as a single target that can suppress signaling from the multiple receptor tyrosine kinase receptors found to be amplified in SCC

Zone-size nonuniformity of 18F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer.

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Cheng, Nai-Ming; Fang, Yu-Hua Dean; Lee, Li-yu; Chang, Joseph Tung-Chieh; Tsan, Din-Li; Ng, Shu-Hang; Wang, Hung-Ming; Liao, Chun-Ta; Yang, Lan-Yan; Hsu, Ching-Han; Yen, Tzu-Chen

2015-03-01

The question as to whether the regional textural features extracted from PET images predict prognosis in oropharyngeal squamous cell carcinoma (OPSCC) remains open. In this study, we investigated the prognostic impact of regional heterogeneity in patients with T3/T4 OPSCC. We retrospectively reviewed the records of 88 patients with T3 or T4 OPSCC who had completed primary therapy. Progression-free survival (PFS) and disease-specific survival (DSS) were the main outcome measures. In an exploratory analysis, a standardized uptake value of 2.5 (SUV 2.5) was taken as the cut-off value for the detection of tumour boundaries. A fixed threshold at 42 % of the maximum SUV (SUVmax 42 %) and an adaptive threshold method were then used for validation. Regional textural features were extracted from pretreatment (18)F-FDG PET/CT images using the grey-level run length encoding method and grey-level size zone matrix. The prognostic significance of PET textural features was examined using receiver operating characteristic (ROC) curves and Cox regression analysis. Zone-size nonuniformity (ZSNU) was identified as an independent predictor of PFS and DSS. Its prognostic impact was confirmed using both the SUVmax 42 % and the adaptive threshold segmentation methods. Based on (1) total lesion glycolysis, (2) uniformity (a local scale texture parameter), and (3) ZSNU, we devised a prognostic stratification system that allowed the identification of four distinct risk groups. The model combining the three prognostic parameters showed a higher predictive value than each variable alone. ZSNU is an independent predictor of outcome in patients with advanced T-stage OPSCC, and may improve their prognostic stratification.

Plasma Riboflavin Level is Associated with Risk, Relapse, and Survival of Esophageal Squamous Cell Carcinoma.

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Li, Shan-Shan; Xu, Yi-Wei; Wu, Jian-Yi; Tan, Hua-Zhen; Wu, Zhi-Yong; Xue, Yu-Jie; Zhang, Jian-Jun; Li, En-Min; Xu, Li-Yan

2017-01-01

Riboflavin is an essential micronutrient for normal cellular activity, and deficiency may result in disease, such as cancer. We performed a case-control study to explore the association of riboflavin levels with risk and prognosis of esophageal squamous cell carcinoma (ESCC). Plasma riboflavin levels, as measured by enzyme-linked immunosorbent assay (ELISA), in ESCC patients were significantly lower than in those of healthy controls (7.04 ± 6.34 ng/ml vs. 9.32 ± 12.40 ng/ml; P riboflavin level and risk of ESCC (odds ratio (OR) = 0.97, 95% confidence interval (CI) = 0.95-0.99, P =  0.02). The 5-year relapse-free and overall survival rates were significantly lower when riboflavin levels were ≤0.8 ng/ml than >0.8 ng/ml (relapse-free survival rate: 29.4% vs. 54.8%; overall survival rate: 28.6% vs. 55.6%). Plasma riboflavin level was an independent protective factor for both relapse-free (hazard ratio (HR) = 0.325, 95% CI = 0.161-0.657, P = 0.002) and overall survival of ESCC patients (HR = 0.382, 95% CI = 0.190-0.768, P = 0.007). In conclusion, plasma riboflavin levels are significantly related to risk and prognosis of ESCC patients, suggesting that moderate supplementation of riboflavin will decrease risk and prevent recurrence of ESCC and also improve prognosis of ESCC patients.

Scoring system predictive of survival for patients undergoing stereotactic body radiation therapy for liver tumors

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Kress Marie-Adele S

2012-09-01

Full Text Available Abstract Background Stereotactic body radiation therapy (SBRT is an emerging treatment option for liver tumors. This study evaluated outcomes after SBRT to identify prognostic variables and to develop a novel scoring system predictive of survival. Methods The medical records of 52 patients with a total of 85 liver lesions treated with SBRT from 2003 to 2010 were retrospectively reviewed. Twenty-four patients had 1 lesion; 27 had 2 or more. Thirteen lesions were primary tumors; 72 were metastases. Fiducials were placed in all patients prior to SBRT. The median prescribed dose was 30 Gy (range, 16 – 50 Gy in a median of 3 fractions (range, 1–5. Results With median follow-up of 11.3 months, median overall survival (OS was 12.5 months, and 1 year OS was 50.8%. In 42 patients with radiographic follow up, 1 year local control was 74.8%. On univariate analysis, number of lesions (p = 0.0243 and active extralesional disease (p  Conclusions SBRT offers a safe and feasible treatment option for liver tumors. A prognostic scoring system based on the number of liver lesions, activity of extralesional disease, and KPS predicts survival following SBRT and can be used as a guide for prospective validation and ultimately for treatment decision-making.

γ-amino butyric acid (GABA) level as an overall survival risk factor in breast cancer.

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Brzozowska, Anna; Burdan, Franciszek; Duma, Dariusz; Solski, Janusz; Mazurkiewicz, Maria

2017-09-21

The γ-amino butyric acid (GABA) plays important role in the proliferation and migration of cancer cells. The aim of the study was to evaluate the level of GABA in breast cancer, in relation to clinical and epidemiological data. The study was conducted on 89 patients with breast cancer in stage I-II. GABA level was assessed using spectrofluorometric method in tumour homogenates. Immunoexpression of E-cadherin was evaluated histologically on paraffin fixed specimens. Overall and disease-free survival was assessed for a 15-year interval period. Median overall survival was significantly longer (127.2 months) in patients with a high level of GABA (>89.3 μg/1), compared with a group with a low level of the amino acid (106.4 months). Disease-free survival was insignificantly different - 99 and 109 months, respectively. A significantly longer overall survival (131.2 months) was seen among patients with a high level of GABA and positive E-cadherin immunoexpression, compared with a group characterized by a low level of GABA and lack of E-cadherin immunorectivity (98.1 months). The co-existence of negative immunoexpression of E-cadherin and low GABA concentration resulted in a six-fold increase in the risk of death (HR=6.03). GABA has a significant prognostic value in breast cancer. Co-existence of a low level of GABA and loss of E-cadherin immune-expression seems to be a new, independent, and negative prognostic marker of the neoplasm.

The expression level of HJURP has an independent prognostic impact and predicts the sensitivity to radiotherapy in breast cancer

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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

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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

Volume of high-risk intratumoral subregions at multi-parametric MR imaging predicts overall survival and complements molecular analysis of glioblastoma

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Cui, Yi; Li, Ruijiang [Stanford University, Department of Radiation Oncology, Palo Alto, CA (United States); Hokkaido University, Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, Hokkaido (Japan); Ren, Shangjie [Tianjin University, School of Electrical Engineering and Automation, Tianjin Shi (China); Tha, Khin Khin; Shirato, Hiroki [Hokkaido University, Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, Hokkaido (Japan); Hokkaido University, Department of Radiology and Nuclear Medicine, Hokkaido (Japan); Wu, Jia [Stanford University, Department of Radiation Oncology, Palo Alto, CA (United States)

2017-09-15

To develop and validate a volume-based, quantitative imaging marker by integrating multi-parametric MR images for predicting glioblastoma survival, and to investigate its relationship and synergy with molecular characteristics. We retrospectively analysed 108 patients with primary glioblastoma. The discovery cohort consisted of 62 patients from the cancer genome atlas (TCGA). Another 46 patients comprising 30 from TCGA and 16 internally were used for independent validation. Based on integrated analyses of T1-weighted contrast-enhanced (T1-c) and diffusion-weighted MR images, we identified an intratumoral subregion with both high T1-c and low ADC, and accordingly defined a high-risk volume (HRV). We evaluated its prognostic value and biological significance with genomic data. On both discovery and validation cohorts, HRV predicted overall survival (OS) (concordance index: 0.642 and 0.653, P < 0.001 and P = 0.038, respectively). HRV stratified patients within the proneural molecular subtype (log-rank P = 0.040, hazard ratio = 2.787). We observed different OS among patients depending on their MGMT methylation status and HRV (log-rank P = 0.011). Patients with unmethylated MGMT and high HRV had significantly shorter survival (median survival: 9.3 vs. 18.4 months, log-rank P = 0.002). Volume of the high-risk intratumoral subregion identified on multi-parametric MRI predicts glioblastoma survival, and may provide complementary value to genomic information. (orig.)

Low expression levels of hepsin and TMPRSS3 are associated with poor breast cancer survival

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Pelkonen, Mikko; Luostari, Kaisa; Tengström, Maria; Ahonen, Hermanni; Berdel, Bozena; Kataja, Vesa; Soini, Ylermi; Kosma, Veli-Matti; Mannermaa, Arto

2015-01-01

Hepsin, (also called TMPRSS1) and TMPRSS3 are type II transmembrane serine proteases (TTSPs) that are involved in cancer progression. TTSPs can remodel extracellular matrix (ECM) and, when dysregulated, promote tumor progression and metastasis by inducing defects in basement membrane and ECM molecules. This study investigated whether the gene and protein expression levels of these TTSPs were associated with breast cancer characteristics or survival. Immunohistochemical staining was used to evaluate hepsin levels in 372 breast cancer samples and TMPRSS3 levels in 373 samples. TMPRSS1 mRNA expression was determined in 125 invasive and 16 benign breast tumor samples, and TMPRSS3 mRNA expression was determined in 167 invasive and 23 benign breast tumor samples. The gene and protein expression levels were analyzed for associations with breast cancer-specific survival and clinicopathological parameters. Low TMPRSS1 and TMPRSS3 mRNA expression levels were independent prognostic factors for poor breast cancer survival during the 20-year follow-up (TMPRSS1, P = 0.023; HR, 2.065; 95 % CI, 1.106–3.856; TMPRSS3, P = 0.013; HR, 2.106; 95 % CI, 1.167–3.800). Low expression of the two genes at the mRNA and protein levels associated with poorer survival compared to high levels (log rank P-values 0.015–0.042). Low TMPRSS1 mRNA expression was also an independent marker of poor breast cancer prognosis in patients treated with radiotherapy (P = 0.034; HR, 2.344; 95 % CI, 1.065–5.160). Grade III tumors, large tumor size, and metastasis were associated with low mRNA and protein expression levels. The results suggest that the TTSPs hepsin and TMPRSS3 may have similar biological functions in the molecular pathology of breast cancer. Low mRNA and protein expression levels of the studied TTSPs were prognostic markers of poor survival in breast cancer. The online version of this article (doi:10.1186/s12885-015-1440-5) contains supplementary material, which is available to authorized

Living donor risk model for predicting kidney allograft and patient survival in an emerging economy.

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Zafar, Mirza Naqi; Wong, Germaine; Aziz, Tahir; Abbas, Khawar; Adibul Hasan Rizvi, S

2018-03-01

Living donor kidney is the main source of donor organs in low to middle income countries. We aimed to develop a living donor risk model that predicts graft and patient survival in an emerging economy. We used data from the Sindh Institute of Urology and Transplantation (SIUT) database (n = 2283 recipients and n = 2283 living kidney donors, transplanted between 1993 and 2009) and conducted Cox proportional hazard analyses to develop a composite score that predicts graft and patient survivals. Donor factors age, creatinine clearance, nephron dose (estimated by donor/recipient body weight ratio) and human leukocyte antigen (HLA) match were included in the living donor risk model. The adjusted hazard ratios (HRs) for graft failures among those who received a kidney with living donor scores (reference to donor score of zero) of 1, 2, 3 and 4 were 1.14 (95%CI: 0.94-1.39), 1.24 (95%CI:1.03-1.49), 1.25 (95%CI:1.03-1.51) and 1.36 (95%CI:1.08-1.72) (P-value for trend =0.05). Similar findings were observed for patient survival. Similar to findings in high income countries, our study suggests that donor characteristics such as age, nephron dose, creatinine clearance and HLA match are important factors that determine the long-term patient and graft survival in low income countries. However, other crucial but undefined factors may play a role in determining the overall risk of graft failure and mortality in living kidney donor transplant recipients. © 2016 Asian Pacific Society of Nephrology.

Optimizing survivability of multi-state systems with multi-level protection by multi-processor genetic algorithm

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Levitin, Gregory; Dai Yuanshun; Xie Min; Leng Poh, Kim

2003-01-01

In this paper we consider vulnerable systems which can have different states corresponding to different combinations of available elements composing the system. Each state can be characterized by a performance rate, which is the quantitative measure of a system's ability to perform its task. Both the impact of external factors (stress) and internal causes (failures) affect system survivability, which is determined as probability of meeting a given demand. In order to increase the survivability of the system, a multi-level protection is applied to its subsystems. This means that a subsystem and its inner level of protection are in their turn protected by the protection of an outer level. This double-protected subsystem has its outer protection and so forth. In such systems, the protected subsystems can be destroyed only if all of the levels of their protection are destroyed. Each level of protection can be destroyed only if all of the outer levels of protection are destroyed. We formulate the problem of finding the structure of series-parallel multi-state system (including choice of system elements, choice of structure of multi-level protection and choice of protection methods) in order to achieve a desired level of system survivability by the minimal cost. An algorithm based on the universal generating function method is used for determination of the system survivability. A multi-processor version of genetic algorithm is used as optimization tool in order to solve the structure optimization problem. An application example is presented to illustrate the procedure presented in this paper

Effects of natal departure and water level on survival of juvenile snail kites (Rostrhamus sociabilis) in Florida

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Dreitz, V.J.; Kitchens, W.M.; DeAngelis, D.L.

2004-01-01

Survival rate from fledging to breeding, or juvenile survival, is an important source of variation in lifetime reproductive success in birds. Therefore, determining the relationship between juvenile survival and environmental factors is essential to understanding fitness consequences of reproduction in many populations. With increases in density of individuals and depletion of food resources, quality of most habitats deteriorates during the breeding season. Individuals respond by dispersing in search of food resources. Therefore, to understand the influence of environmental factors on juvenile survival, it is also necessary to know how natal dispersal influences survival of juveniles. We examined effects of various environmental factors and natal dispersal behavior on juvenile survival of endangered Snail Kites (Rostrhamus sociabilis) in central and southern Florida, using a generalized estimating equations (GEEs) approach and model selection criteria. Our results suggested yearly effects and an influence of age and monthly minimum hydrologic levels on juvenile Snail Kite survival. Yearly variation in juvenile survival has been reported by other studies, and other reproductive components of Snail Kites also exhibit such variation. Age differences in juvenile survival have also been seen in other species during the juvenile period. Our results demonstrate a positive relationship between water levels and juvenile survival. We suggest that this is not a direct linear relationship, such that higher water means higher juvenile survival. The juvenile period is concurrent with onset of the wet season in the ecosystem we studied, and rainfall increases as juveniles age. For management purposes, we believe that inferences suggesting increasing water levels during the fledging period will increase juvenile survival may have short-term benefits but lead to long-term declines in prey abundance and possibly wetland vegetation structure.

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.

Sentence-Level Attachment Prediction

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Albakour, M.-Dyaa; Kruschwitz, Udo; Lucas, Simon

Attachment prediction is the task of automatically identifying email messages that should contain an attachment. This can be useful to tackle the problem of sending out emails but forgetting to include the relevant attachment (something that happens all too often). A common Information Retrieval (IR) approach in analyzing documents such as emails is to treat the entire document as a bag of words. Here we propose a finer-grained analysis to address the problem. We aim at identifying individual sentences within an email that refer to an attachment. If we detect any such sentence, we predict that the email should have an attachment. Using part of the Enron corpus for evaluation we find that our finer-grained approach outperforms previously reported document-level attachment prediction in similar evaluation settings.

Membrane expression of MRP-1, but not MRP-1 splicing or Pgp expression, predicts survival in patients with ESFT.

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Roundhill, E; Burchill, S

2013-07-09

Primary Ewing's sarcoma family of tumours (ESFTs) may respond to chemotherapy, although many patients experience subsequent disease recurrence and relapse. The survival of ESFT cells following chemotherapy has been attributed to the development of resistant disease, possibly through the expression of ABC transporter proteins. MRP-1 and Pgp mRNA and protein expression in primary ESFTs was determined by quantitative reverse-transcriptase PCR (RT-qPCR) and immunohistochemistry, respectively, and alternative splicing of MRP-1 by RT-PCR. We observed MRP-1 protein expression in 92% (43 out of 47) of primary ESFTs, and cell membrane MRP-1 was highly predictive of both overall survival (PMRP-1 was detected in primary ESFTs, although the pattern of splicing variants was not predictive of patient outcome, with the exception of loss of exon 9 in six patients, which predicted relapse (P=0.041). Pgp protein was detected in 6% (38 out of 44) of primary ESFTs and was not associated with patient survival. For the first time we have established that cell membrane expression of MRP-1 or loss of exon 9 is predictive of outcome but not the number of splicing events or expression of Pgp, and both may be valuable factors for the stratification of patients for more intensive therapy.

A new scoring system for predicting survival in patients with non-small cell lung cancer

International Nuclear Information System (INIS)

Schild, Steven E; Tan, Angelina D; Wampfler, Jason A; Ross, Helen J; Yang, Ping; Sloan, Jeff A

2015-01-01

This analysis was performed to create a scoring system to estimate the survival of patients with non-small cell lung cancer (NSCLC). Data from 1274 NSCLC patients were analyzed to create and validate a scoring system. Univariate (UV) and multivariate (MV) Cox models were used to evaluate the prognostic importance of each baseline factor. Prognostic factors that were significant on both UV and MV analyses were used to develop the score. These included quality of life, age, performance status, primary tumor diameter, nodal status, distant metastases, and smoking cessation. The score for each factor was determined by dividing the 5-year survival rate (%) by 10 and summing these scores to form a total score. MV models and the score were validated using bootstrapping with 1000 iterations from the original samples. The score for each prognostic factor ranged from 1 to 7 points with higher scores reflective of better survival. Total scores (sum of the scores from each independent prognostic factor) of 32–37 correlated with a 5-year survival of 8.3% (95% CI = 0–17.1%), 38–43 correlated with a 5-year survival of 20% (95% CI = 13–27%), 44–47 correlated with a 5-year survival of 48.3% (95% CI = 41.5–55.2%), 48–49 correlated to a 5-year survival of 72.1% (95% CI = 65.6–78.6%), and 50–52 correlated to a 5-year survival of 84.7% (95% CI = 79.6–89.8%). The bootstrap method confirmed the reliability of the score. Prognostic factors significantly associated with survival on both UV and MV analyses were used to construct a valid scoring system that can be used to predict survival of NSCLC patients. Optimally, this score could be used when counseling patients, and designing future trials

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.

Prognostic Value of Serum Caspase-Cleaved Cytokeratin-18 Levels before Liver Transplantation for One-Year Survival of Patients with Hepatocellular Carcinoma

Directory of Open Access Journals (Sweden)

Leonardo Lorente

2016-09-01

Full Text Available Cytokeratin (CK-18 is the major intermediate filament protein in the liver and during hepatocyte apoptosis is cleaved by the action of caspases; the resulting fragments are released into the blood as caspase-cleaved cytokeratin (CCCK-18. Higher circulating levels of CCCK-18 have been found in patients with hepatocellular carcinoma (HCC than in healthy controls and than in cirrhotic patients. However, it is unknown whether serum CCCK-18 levels before liver transplantation (LT in patients with HCC could be used as a prognostic biomarker of one-year survival, and this was the objective of our study with 135 patients. At one year after LT, non-survivors showed higher serum CCCK-18 levels than survivors (p = 0.001. On binary logistic regression analysis, serum CCCK-18 levels >384 U/L were associated with death at one year (odds ratio = 19.801; 95% confidence interval = 5.301–73.972; p < 0.001 after controlling for deceased donor age. The area under the receiver operating characteristic (ROC curve of serum CCCK-18 levels to predict death at one year was 77% (95% CI = 69%–84%; p < 0.001. The new finding of our study was that serum levels of CCCK-18 before LT in patients with HCC could be used as prognostic biomarker of survival.

Prognostic Value of Serum Caspase-Cleaved Cytokeratin-18 Levels before Liver Transplantation for One-Year Survival of Patients with Hepatocellular Carcinoma

Science.gov (United States)

Lorente, Leonardo; Rodriguez, Sergio T.; Sanz, Pablo; Pérez-Cejas, Antonia; Padilla, Javier; Díaz, Dácil; González, Antonio; Martín, María M.; Jiménez, Alejandro; Barrera, Manuel A.

2016-01-01

Cytokeratin (CK)-18 is the major intermediate filament protein in the liver and during hepatocyte apoptosis is cleaved by the action of caspases; the resulting fragments are released into the blood as caspase-cleaved cytokeratin (CCCK)-18. Higher circulating levels of CCCK-18 have been found in patients with hepatocellular carcinoma (HCC) than in healthy controls and than in cirrhotic patients. However, it is unknown whether serum CCCK-18 levels before liver transplantation (LT) in patients with HCC could be used as a prognostic biomarker of one-year survival, and this was the objective of our study with 135 patients. At one year after LT, non-survivors showed higher serum CCCK-18 levels than survivors (p = 0.001). On binary logistic regression analysis, serum CCCK-18 levels >384 U/L were associated with death at one year (odds ratio = 19.801; 95% confidence interval = 5.301–73.972; p < 0.001) after controlling for deceased donor age. The area under the receiver operating characteristic (ROC) curve of serum CCCK-18 levels to predict death at one year was 77% (95% CI = 69%–84%; p < 0.001). The new finding of our study was that serum levels of CCCK-18 before LT in patients with HCC could be used as prognostic biomarker of survival. PMID:27618033

EMX2 gene expression predicts liver metastasis and survival in colorectal cancer.

Science.gov (United States)

Aykut, Berk; Ochs, Markus; Radhakrishnan, Praveen; Brill, Adrian; Höcker, Hermine; Schwarz, Sandra; Weissinger, Daniel; Kehm, Roland; Kulu, Yakup; Ulrich, Alexis; Schneider, Martin

2017-08-22

The Empty Spiracles Homeobox (EMX-) 2 gene has been associated with regulation of growth and differentiation in neuronal development. While recent studies provide evidence that EMX2 regulates tumorigenesis of various solid tumors, its role in colorectal cancer remains unknown. We aimed to assess the prognostic significance of EMX2 expression in stage III colorectal adenocarcinoma. Expression levels of EMX2 in human colorectal cancer and adjacent mucosa were assessed by qRT-PCR technology, and results were correlated with clinical and survival data. siRNA-mediated knockdown and adenoviral delivery-mediated overexpression of EMX2 were performed in order to investigate its effects on the migration of colorectal cancer cells in vitro. Compared to corresponding healthy mucosa, colorectal tumor samples had decreased EMX2 expression levels. Furthermore, EMX2 down-regulation in colorectal cancer tissue was associated with distant metastasis (M1) and impaired overall patient survival. In vitro knockdown of EMX2 resulted in increased tumor cell migration. Conversely, overexpression of EMX2 led to an inhibition of tumor cell migration. EMX2 is frequently down-regulated in human colorectal cancer, and down-regulation of EMX2 is a prognostic marker for disease-free and overall survival. EMX2 might thus represent a promising therapeutic target in colorectal cancer.

Predicting water main failures using Bayesian model averaging and survival modelling approach

International Nuclear Information System (INIS)

Kabir, Golam; Tesfamariam, Solomon; Sadiq, Rehan

2015-01-01

To develop an effective preventive or proactive repair and replacement action plan, water utilities often rely on water main failure prediction models. However, in predicting the failure of water mains, uncertainty is inherent regardless of the quality and quantity of data used in the model. To improve the understanding of water main failure, a Bayesian framework is developed for predicting the failure of water mains considering uncertainties. In this study, Bayesian model averaging method (BMA) is presented to identify the influential pipe-dependent and time-dependent covariates considering model uncertainties whereas Bayesian Weibull Proportional Hazard Model (BWPHM) is applied to develop the survival curves and to predict the failure rates of water mains. To accredit the proposed framework, it is implemented to predict the failure of cast iron (CI) and ductile iron (DI) pipes of the water distribution network of the City of Calgary, Alberta, Canada. Results indicate that the predicted 95% uncertainty bounds of the proposed BWPHMs capture effectively the observed breaks for both CI and DI water mains. Moreover, the performance of the proposed BWPHMs are better compare to the Cox-Proportional Hazard Model (Cox-PHM) for considering Weibull distribution for the baseline hazard function and model uncertainties. - Highlights: • Prioritize rehabilitation and replacements (R/R) strategies of water mains. • Consider the uncertainties for the failure prediction. • Improve the prediction capability of the water mains failure models. • Identify the influential and appropriate covariates for different models. • Determine the effects of the covariates on failure

Deformable image registration as a tool to improve survival prediction after neoadjuvant chemotherapy for breast cancer: results from the ACRIN 6657/I-SPY-1 trial

Science.gov (United States)

Jahani, Nariman; Cohen, Eric; Hsieh, Meng-Kang; Weinstein, Susan P.; Pantalone, Lauren; Davatzikos, Christos; Kontos, Despina

2018-02-01

We examined the ability of DCE-MRI longitudinal features to give early prediction of recurrence-free survival (RFS) in women undergoing neoadjuvant chemotherapy for breast cancer, in a retrospective analysis of 106 women from the ISPY 1 cohort. These features were based on the voxel-wise changes seen in registered images taken before treatment and after the first round of chemotherapy. We computed the transformation field using a robust deformable image registration technique to match breast images from these two visits. Using the deformation field, parametric response maps (PRM) — a voxel-based feature analysis of longitudinal changes in images between visits — was computed for maps of four kinetic features (signal enhancement ratio, peak enhancement, and wash-in/wash-out slopes). A two-level discrete wavelet transform was applied to these PRMs to extract heterogeneity information about tumor change between visits. To estimate survival, a Cox proportional hazard model was applied with the C statistic as the measure of success in predicting RFS. The best PRM feature (as determined by C statistic in univariable analysis) was determined for each of the four kinetic features. The baseline model, incorporating functional tumor volume, age, race, and hormone response status, had a C statistic of 0.70 in predicting RFS. The model augmented with the four PRM features had a C statistic of 0.76. Thus, our results suggest that adding information on the texture of voxel-level changes in tumor kinetic response between registered images of first and second visits could improve early RFS prediction in breast cancer after neoadjuvant chemotherapy.

Zone-size nonuniformity of {sup 18}F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer

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Cheng, Nai-Ming [Chang Gung Memorial Hospital and Chang Gung University, Departments of Nuclear Medicine, Taiyuan (China); Chang Gung Memorial Hospital, Department of Nuclear Medicine, Keelung (China); National Tsing Hua University, Department of Biomedical Engineering and Environmental Sciences, Hsinchu (China); Fang, Yu-Hua Dean [Chang Gung University, Department of Electrical Engineering, Taiyuan (China); Lee, Li-yu [Chang Gung University College of Medicine, Department of Pathology, Chang Gung Memorial Hospital, Taoyuan (China); Chang, Joseph Tung-Chieh; Tsan, Din-Li [Chang Gung University College of Medicine, Department of Radiation Oncology, Chang Gung Memorial Hospital, Taoyuan (China); Ng, Shu-Hang [Chang Gung University College of Medicine, Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Taoyuan (China); Wang, Hung-Ming [Chang Gung University College of Medicine, Division of Hematology/Oncology, Department of Internal Medicine, Chang Gung Memorial Hospital, Taoyuan (China); Liao, Chun-Ta [Chang Gung University College of Medicine, Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Taoyuan (China); Yang, Lan-Yan [Chang Gung Memorial Hospital, Biostatistics Unit, Clinical Trial Center, Taoyuan (China); Hsu, Ching-Han [National Tsing Hua University, Department of Biomedical Engineering and Environmental Sciences, Hsinchu (China); Yen, Tzu-Chen [Chang Gung Memorial Hospital and Chang Gung University, Departments of Nuclear Medicine, Taiyuan (China); Chang Gung University College of Medicine, Department of Nuclear Medicine and Molecular Imaging Center, Chang Gung Memorial Hospital, Taipei (China)

2014-10-23

The question as to whether the regional textural features extracted from PET images predict prognosis in oropharyngeal squamous cell carcinoma (OPSCC) remains open. In this study, we investigated the prognostic impact of regional heterogeneity in patients with T3/T4 OPSCC. We retrospectively reviewed the records of 88 patients with T3 or T4 OPSCC who had completed primary therapy. Progression-free survival (PFS) and disease-specific survival (DSS) were the main outcome measures. In an exploratory analysis, a standardized uptake value of 2.5 (SUV 2.5) was taken as the cut-off value for the detection of tumour boundaries. A fixed threshold at 42 % of the maximum SUV (SUV{sub max} 42 %) and an adaptive threshold method were then used for validation. Regional textural features were extracted from pretreatment {sup 18}F-FDG PET/CT images using the grey-level run length encoding method and grey-level size zone matrix. The prognostic significance of PET textural features was examined using receiver operating characteristic (ROC) curves and Cox regression analysis. Zone-size nonuniformity (ZSNU) was identified as an independent predictor of PFS and DSS. Its prognostic impact was confirmed using both the SUV{sub max} 42 % and the adaptive threshold segmentation methods. Based on (1) total lesion glycolysis, (2) uniformity (a local scale texture parameter), and (3) ZSNU, we devised a prognostic stratification system that allowed the identification of four distinct risk groups. The model combining the three prognostic parameters showed a higher predictive value than each variable alone. ZSNU is an independent predictor of outcome in patients with advanced T-stage OPSCC, and may improve their prognostic stratification. (orig.)

Predictive value of the Status Epilepticus Severity Score (STESS) and its components for long-term survival

DEFF Research Database (Denmark)

Aukland, Preben; Lando, Martin; Vilholm, Ole

2016-01-01

BACKGROUND: The "Status Epilepticus Severity Score" (STESS) is the most important clinical score to predict in-hospital mortality of patients with status epilepticus (SE), but its prognostic relevance for long-term survival is unknown. This study therefore examined if STESS and its components...

Stomatin-like protein 2 is overexpressed in epithelial ovarian cancer and predicts poor patient survival

International Nuclear Information System (INIS)

Sun, Fei; Ding, Wen; He, Jie-Hua; Wang, Xiao-Jing; Ma, Ze-Biao; Li, Yan-Fang

2015-01-01

Stomatin-like protein 2 (SLP-2, also known as STOML2) is a stomatin homologue of uncertain function. SLP-2 overexpression has been suggested to be associated with cancer progression, resulting in adverse clinical outcomes in patients. Our study aim to investigate SLP-2 expression in epithelial ovarian cancer cells and its correlation with patient survival. SLP-2 mRNA and protein expression levels were analysed in five epithelial ovarian cancer cell lines and normal ovarian epithelial cells using real-time PCR and western blotting analysis. SLP-2 expression was investigated in eight matched-pair samples of epithelial ovarian cancer and adjacent noncancerous tissues from the same patients. Using immunohistochemistry, we examined the protein expression of paraffin-embedded specimens from 140 patients with epithelial ovarian cancer, 20 cases with borderline ovarian tumours, 20 cases with benign ovarian tumours, and 20 cases with normal ovarian tissues. Statistical analyses were applied to evaluate the clinicopathological significance of SLP-2 expression. SLP-2 mRNA and protein expression levels were significantly up-regulated in epithelial ovarian cancer cell lines and cancer tissues compared with normal ovarian epithelial cells and adjacent noncancerous ovarian tissues. Immunohistochemistry analysis revealed that the relative overexpression of SLP-2 was detected in 73.6 % (103/140) of the epithelial ovarian cancer specimens, 45.0 % (9/20) of the borderline ovarian specimens, 30.0 % (6/20) of the benign ovarian specimens and none of the normal ovarian specimens. SLP-2 protein expression in epithelial ovarian cancer was significantly correlated with the tumour stage (P < 0.001). Epithelial ovarian cancer patients with higher SLP-2 protein expression levels had shorter progress free survival and overall survival times compared to patients with lower SLP-2 protein expression levels. Multivariate analyses showed that SLP-2 expression levels were an independent prognostic

Elevated C-reactive protein and hypoalbuminemia measured before resection of colorectal liver metastases predict postoperative survival.

Science.gov (United States)

Kobayashi, Takashi; Teruya, Masanori; Kishiki, Tomokazu; Endo, Daisuke; Takenaka, Yoshiharu; Miki, Kenji; Kobayashi, Kaoru; Morita, Koji

2010-01-01

Few studies have investigated whether the Glasgow Prognostic Score (GPS), an inflammation-based prognostic score measured before resection of colorectal liver metastasis (CRLM), can predict postoperative survival. Sixty-three consecutive patients who underwent curative resection for CRLM were investigated. GPS was calculated on the basis of admission data as follows: patients with both an elevated C-reactive protein (>10 mg/l) and hypoalbuminemia (l) were allocated a GPS score of 2. Patients in whom only one of these biochemical abnormalities was present were allocated a GPS score of 1, and patients with a normal C-reactive protein and albumin were allocated a score of 0. Significant factors concerning survival were the number of liver metastases (p = 0.0044), carcinoembryonic antigen level (p = 0.0191), GPS (p = 0.0029), grade of liver metastasis (p = 0.0033), and the number of lymph node metastases around the primary cancer (p = 0.0087). Multivariate analysis showed the two independent prognostic variables: liver metastases > or =3 (relative risk 2.83) and GPS1/2 (relative risk 3.07). GPS measured before operation and the number of liver metastases may be used as novel predictors of postoperative outcomes in patients who underwent curative resection for CRLM. Copyright 2010 S. Karger AG, Basel.

Association between Pre-Transplant Serum Malondialdehyde Levels and Survival One Year after Liver Transplantation for Hepatocellular Carcinoma

Directory of Open Access Journals (Sweden)

Leonardo Lorente

2016-04-01

Full Text Available Previous studies have found higher levels of serum malondialdehyde (MDA in hepatocellular carcinoma (HCC patients compared to healthy controls and higher MDA concentrations in tumoral tissue of HCC patients than in non-tumoral tissue. However, the association between pre-transplant serum levels of MDA and survival in HCC patients after liver transplantation (LT has not been described, and the aim of the present study was to determine whether such an association exists. In this observational study we measured serum MDA levels in 127 patients before LT. We found higher pre-LT serum MDA levels in 15 non-surviving than in 112 surviving patients one year after LT (p = 0.02. Exact binary logistic regression analysis revealed that pre-LT serum levels of MDA over 3.37 nmol/mL were associated with mortality after one year of LT (Odds ratio = 5.38; 95% confidence interval (CI = from 1.580 to infinite; p = 0.007 adjusting for age of the deceased donor. The main finding of our study was that there is an association between serum MDA levels before LT for HCC and 1-year survival after LT.

Association between Pre-Transplant Serum Malondialdehyde Levels and Survival One Year after Liver Transplantation for Hepatocellular Carcinoma

Science.gov (United States)

Lorente, Leonardo; Rodriguez, Sergio T.; Sanz, Pablo; Abreu-González, Pedro; Díaz, Dácil; Moreno, Antonia M.; Borja, Elisa; Martín, María M.; Jiménez, Alejandro; Barrera, Manuel A.

2016-01-01

Previous studies have found higher levels of serum malondialdehyde (MDA) in hepatocellular carcinoma (HCC) patients compared to healthy controls and higher MDA concentrations in tumoral tissue of HCC patients than in non-tumoral tissue. However, the association between pre-transplant serum levels of MDA and survival in HCC patients after liver transplantation (LT) has not been described, and the aim of the present study was to determine whether such an association exists. In this observational study we measured serum MDA levels in 127 patients before LT. We found higher pre-LT serum MDA levels in 15 non-surviving than in 112 surviving patients one year after LT (p = 0.02). Exact binary logistic regression analysis revealed that pre-LT serum levels of MDA over 3.37 nmol/mL were associated with mortality after one year of LT (Odds ratio = 5.38; 95% confidence interval (CI) = from 1.580 to infinite; p = 0.007) adjusting for age of the deceased donor. The main finding of our study was that there is an association between serum MDA levels before LT for HCC and 1-year survival after LT. PMID:27058525

Inflammatory markers in blood and serum tumor markers predict survival in patients with epithelial appendiceal neoplasms undergoing surgical cytoreduction and intraperitoneal chemotherapy.

Science.gov (United States)

Chua, Terence C; Chong, Chanel H; Liauw, Winston; Zhao, Jing; Morris, David L

2012-08-01

The study examines the role inflammatory and tumor markers as biomarkers to preoperatively predict outcome in patients with epithelial appendiceal neoplasm undergoing cytoreduction and intraperitoneal chemotherapy. Associations between baseline variables, tumor markers [CEA (carcinoembyronic antigen], CA125, CA199), inflammatory markers including neutrophils-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and C-reactive protein (CRP) with progression-free survival (PFS) and overall survival (OS) were examined in patients undergoing surgical cytoreduction and intraperitoneal chemotherapy for epithelial appendiceal neoplasm. A total of 174 patients with epithelial appendiceal neoplasm (low-grade pseudomyxoma, n = 117; appendiceal cancer, n = 57) underwent cytoreduction. On univariate analysis, all 3 inflammatory and tumor markers predicted for both PFS and OS, respectively; NLR ≤ 2.6 (P = 0.01, P = 0.002), PLR ≤ 166 (P = 0.006, P = 0.016), CRP ≤ 12.5 (P = 0.001, P = 0.008), CEA (P 37 (P = 0.003), and a CRP > 12.5 (P = 0.013). A higher peritoneal cancer index (PCI > 24) was associated with elevation in CEA > 12, CA125 > 39, CA199 > 37, PLR > 166 and CRP > 12. The tumor histologic subtype was associated with CA 199 levels. The results from this investigation suggest that preoperative inflammatory markers in blood and serologic tumor markers may predict outcomes and are associated with tumor biology in patients with epithelial appendiceal neoplasm undergoing cytoreduction and intraperitoneal chemotherapy treatment.

High CRP values predict poor survival in patients with penile cancer

International Nuclear Information System (INIS)

Steffens, Sandra; Kuczyk, Markus A; Schrader, Andres J; Al Ghazal, Andreas; Steinestel, Julie; Lehmann, Rieke; Wegener, Gerd; Schnoeller, Thomas J; Cronauer, Marcus V; Jentzmik, Florian; Schrader, Mark

2013-01-01

High levels of circulating C-reactive protein (CRP) have recently been linked to poor clinical outcome in various malignancies. The aim of this study was to evaluate the prognostic significance of the preoperative serum CRP level in patients with squamous cell carcinoma (SCC) of the penis. This retrospective analysis included 79 penile cancer patients with information about their serum CRP value prior to surgery who underwent either radical or partial penectomy at two German high-volume centers (Ulm University Medical Center and Hannover Medical School) between 1990 and 2010. They had a median (mean) follow-up of 23 (32) months. A significantly elevated CRP level (>15 vs. ≤ 15 mg/l) was found more often in patients with an advanced tumor stage (≥pT2) (38.9 vs. 11.6%, p=0.007) and in those with nodal disease at diagnosis (50.0 vs. 14.6%, p=0.007). However, high CRP levels were not associated with tumor differentiation (p=0.53). The Kaplan-Meier 5-year cancer-specific survival (CSS) rate was 38.9% for patients with preoperative CRP levels above 15 mg/l and 84.3% for those with lower levels (p=0.001). Applying multivariate analysis and focusing on the subgroup of patients without metastasis at the time of penile surgery, both advanced local tumor stage (≥pT2; HR 8.8, p=0.041) and an elevated CRP value (>15 mg/l; HR 3.3, p=0.043) were identified as independent predictors of poor clinical outcome in patients with penile cancer. A high preoperative serum CRP level was associated with poor survival in patients with penile cancer. If larger patient populations confirm its prognostic value, its routine use could enable better risk stratification and risk-adjusted follow-up of patients with SCC of the penis

Lean body mass predicts long-term survival in Chinese patients on peritoneal dialysis.

Directory of Open Access Journals (Sweden)

Jenq-Wen Huang

Full Text Available BACKGROUND: Reduced lean body mass (LBM is one of the main indicators in malnutrition inflammation syndrome among patients on dialysis. However, the influence of LBM on peritoneal dialysis (PD patients' outcomes and the factors related to increasing LBM are seldom reported. METHODS: We enrolled 103 incident PD patients between 2002 and 2003, and followed them until December 2011. Clinical characteristics, PD-associated parameters, residual renal function, and serum chemistry profiles of each patient were collected at 1 month and 1 year after initiating PD. LBM was estimated using creatinine index corrected with body weight. Multiple linear regression analysis, Kaplan-Meier survival analysis, and Cox regression proportional hazard analysis were used to define independent variables and compare survival between groups. RESULTS: Using the median LBM value (70% for men and 64% for women, patients were divided into group 1 (n = 52; low LBM and group 2 (n = 51; high LBM. Group 1 patients had higher rates of peritonitis (1.6 vs. 1.1/100 patient months; p<0.05 and hospitalization (14.6 vs. 9.7/100 patient months; p<0.05. Group 1 patients also had shorter overall survival and technique survival (p<0.01. Each percentage point increase in LBM reduced the hazard ratio for mortality by 8% after adjustment for diabetes, age, sex, and body mass index (BMI. Changes in residual renal function and protein catabolic rate were independently associated with changes in LBM in the first year of PD. CONCLUSIONS: LBM serves as a good parameter in addition to BMI to predict the survival of patients on PD. Preserving residual renal function and increasing protein intake can increase LBM.

Chest computed tomography scores are predictive of survival in patients with cystic fibrosis awaiting lung transplantation

DEFF Research Database (Denmark)

Loeve, Martine; Hop, Wim C. J.; de Bruijne, Marleen

2012-01-01

Rationale: Up to a third of cystic fibrosis (CF) patients awaiting lung transplantation (LTX) die while waiting. Inclusion of computed tomography (CT) scores may improve survival prediction models such as the lung allocation score (LAS). Objectives: This study investigated the association between...... CT and survival in CF patients screened for LTX. Methods: Clinical data and chest CTs of 411 CF patients screened for LTX between 1990 and 2005 were collected from 17 centers. CTs were scored with the Severe Advanced Lung Disease (SALD) 4-category scoring system, including the components "infection....../inflammation" (INF), air trapping/hypoperfusion (AT), normal/hyperperfusion (NOR) and bulla/cysts (BUL). The volume of each component was computed using semi-automated software. Survival analysis included Kaplan-Meier curves, and Cox-regression models. Measurements and main results: 366 (186 males) out of 411...

Survival Prediction in Patients Undergoing Open-Heart Mitral Valve Operation After Previous Failed MitraClip Procedures.

Science.gov (United States)

Geidel, Stephan; Wohlmuth, Peter; Schmoeckel, Michael

2016-03-01

The objective of this study was to analyze the results of open heart mitral valve operations for survival prediction in patients with previously unsuccessful MitraClip procedures. Thirty-three consecutive patients who underwent mitral valve surgery in our institution were studied. At a median of 41 days, they had previously undergone one to five futile MitraClip implantations. At the time of their operations, patients were 72.6 ± 10.3 years old, and the calculated risk, using the European System for Cardiac Operative Risk Evaluation (EuroSCORE) II, was a median of 26.5%. Individual outcomes were recorded, and all patients were monitored postoperatively. Thirty-day mortality was 9.1%, and the overall survival at 2.2 years was 60.6%. Seven cardiac-related and six noncardiac deaths occurred. Univariate survival regression models demonstrated a significant influence of the following variables on survival: EuroSCORE II (p = 0.0022), preoperative left ventricular end-diastolic dimension (p = 0.0052), left ventricular ejection fraction (p = 0.0249), coronary artery disease (p = 0.0385), and severe pulmonary hypertension (p = 0.0431). Survivors showed considerable improvements in their New York Heart Association class (p < 0.0001), left ventricular ejection fraction (p = 0.0080), grade of mitral regurgitation (p = 0.0350), and mitral valve area (p = 0.0486). Survival after mitral repair was not superior to survival after replacement. Indications for surgery after failed MitraClip procedures must be considered with the greatest of care. Variables predicting postoperative survival should be taken into account regarding the difficult decision as to whether to operate or not. Our data suggest that replacement of the pretreated mitral valve is probably the more reasonable concept rather than complex repairs. When the EuroSCORE II at the time of surgery exceeds 30%, conservative therapy is advisable. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc

Evaluation and comparison of predictive individual-level general surrogates.

Science.gov (United States)

Gabriel, Erin E; Sachs, Michael C; Halloran, M Elizabeth

2018-07-01

An intermediate response measure that accurately predicts efficacy in a new setting at the individual level could be used both for prediction and personalized medical decisions. In this article, we define a predictive individual-level general surrogate (PIGS), which is an individual-level intermediate response that can be used to accurately predict individual efficacy in a new setting. While methods for evaluating trial-level general surrogates, which are predictors of trial-level efficacy, have been developed previously, few, if any, methods have been developed to evaluate individual-level general surrogates, and no methods have formalized the use of cross-validation to quantify the expected prediction error. Our proposed method uses existing methods of individual-level surrogate evaluation within a given clinical trial setting in combination with cross-validation over a set of clinical trials to evaluate surrogate quality and to estimate the absolute prediction error that is expected in a new trial setting when using a PIGS. Simulations show that our method performs well across a variety of scenarios. We use our method to evaluate and to compare candidate individual-level general surrogates over a set of multi-national trials of a pentavalent rotavirus vaccine.

Failure to Achieve a PSA Level ≤1 ng/mL After Neoadjuvant LHRHA Therapy Predicts for Lower Biochemical Control Rate and Overall Survival in Localized Prostate Cancer Treated With Radiotherapy

International Nuclear Information System (INIS)

Mitchell, Darren M.; McAleese, Jonathan; Park, Richard M.; Stewart, David P.; Stranex, Stephen; Eakin, Ruth L.; Houston, Russell F.; O'Sullivan, Joe M.

2007-01-01

Purpose: To investigate whether failure to suppress the prostate-specific antigen (PSA) level to ≤1 ng/mL after ≥2 months of neoadjuvant luteinizing hormone-releasing hormone agonist therapy in patients scheduled to undergo external beam radiotherapy for localized prostate carcinoma is associated with reduced biochemical failure-free survival. Methods and Materials: A retrospective case note review of consecutive patients with intermediate- or high-risk localized prostate cancer treated between January 2001 and December 2002 with neoadjuvant hormonal deprivation therapy, followed by concurrent hormonal therapy and radiotherapy was performed. Patient data were divided for analysis according to whether the PSA level in Week 1 of radiotherapy was ≤1.0 ng/mL. Biochemical failure was determined using the American Society for Therapeutic Radiology and Oncology (Phoenix) definition. Results: A total of 119 patients were identified. The PSA level after neoadjuvant hormonal deprivation therapy was ≤1 ng/mL in 67 patients and >1 ng/mL in 52. At a median follow-up of 49 months, the 4-year actuarial biochemical failure-free survival rate was 84% vs. 60% (p = 0.0016) in favor of the patients with a PSA level after neoadjuvant hormonal deprivation therapy of ≤1 ng/mL. The overall survival rate was 94% vs. 77.5% (p = 0.0045), and the disease-specific survival rate at 4 years was 98.5% vs. 82.5%. Conclusions: The results of our study have shown that patients with a PSA level >1 ng/mL at the beginning of external beam radiotherapy after ≥2 months of neoadjuvant luteinizing hormone-releasing hormone agonist therapy have a significantly greater rate of biochemical failure and lower survival rate compared with those with a PSA level of ≤1 ng/mL. Patients without adequate PSA suppression should be considered a higher risk group and considered for dose escalation or the use of novel treatments

Predicting Structure-Function Relations and Survival following Surgical and Bronchoscopic Lung Volume Reduction Treatment of Emphysema.

Science.gov (United States)

Mondoñedo, Jarred R; Suki, Béla

2017-02-01

Lung volume reduction surgery (LVRS) and bronchoscopic lung volume reduction (bLVR) are palliative treatments aimed at reducing hyperinflation in advanced emphysema. Previous work has evaluated functional improvements and survival advantage for these techniques, although their effects on the micromechanical environment in the lung have yet to be determined. Here, we introduce a computational model to simulate a force-based destruction of elastic networks representing emphysema progression, which we use to track the response to lung volume reduction via LVRS and bLVR. We find that (1) LVRS efficacy can be predicted based on pre-surgical network structure; (2) macroscopic functional improvements following bLVR are related to microscopic changes in mechanical force heterogeneity; and (3) both techniques improve aspects of survival and quality of life influenced by lung compliance, albeit while accelerating disease progression. Our model predictions yield unique insights into the microscopic origins underlying emphysema progression before and after lung volume reduction.

Basal HIF-1a expression levels are not predictive for radiosensitivity of human cancer cell lines

International Nuclear Information System (INIS)

Schilling, D.; Multhoff, G.; Helmholtz Center Munich, CCG - Innate Immunity in Tumor Biology, Munich; Bayer, C.; Emmerich, K.; Molls, M.; Vaupel, P.; Huber, R.M.

2012-01-01

High levels of hypoxia inducible factor (HIF)-1a in tumors are reported to be associated with tumor progression and resistance to therapy. To examine the impact of HIF-1a on radioresistance under normoxia, the sensitivity towards irradiation was measured in human tumor cell lines that differ significantly in their basal HIF-1a levels. HIF-1a levels were quantified in lysates of H1339, EPLC-272H, A549, SAS, XF354, FaDu, BHY, and CX- tumor cell lines by ELISA. Protein levels of HIF-1a, HIF-2a, carbonic anhydrase IX (CA IX), and GAPDH were assessed by Western blot analysis. Knock-down experiments were performed using HIF-1a siRNA. Clonogenic survival after irradiation was determined by the colony forming assay. According to their basal HIF-1a status, the tumor cell lines were divided into low (SAS, XF354, FaDu, A549, CX-), intermediate (EPLC-272H, BHY), and high (H1339) HIF-1a expressors. The functionality of the high basal HIF-1a expression in H1339 cells was proven by reduced CA IX expression after knocking-down HIF-1a. Linear regression analysis revealed no correlation between basal HIF-1a levels and the survival fraction at either 2 or 4 Gy in all tumor cell lines investigated. Our data suggest that basal HIF-1a levels in human tumor cell lines do not predict their radiosensitivity under normoxia. (orig.)

PCI is Not Predictive of Survival After Complete CRS/HIPEC in Peritoneal Dissemination from High-Grade Appendiceal Primaries.

Science.gov (United States)

Votanopoulos, Konstantinos Ioannis; Bartlett, David; Moran, Brendan; Haroon, Choudry M; Russell, Greg; Pingpank, James F; Ramalingam, Lekshmi; Kandiah, Chandrakumaran; Chouliaras, Konstantinos; Shen, Perry; Levine, Edward A

2018-03-01

Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) is a treatment option in patients with carcinomatosis from high-grade appendiceal (HGA) primaries. It is unknown if there is a Peritoneal Carcinomatosis Index (PCI) upper limit above which a complete CRS/HIPEC does not assure long-term survival. Retrospective analysis from three centers was performed. The PCI was used to grade volume of of disease. Survival in relation to PCI was studied on patients with complete cytoreduction. Overall, 521 HGA patients underwent CRS/HIPEC from 1993 to 2015, with complete CRS being achieved in 50% (260/622). Mean PCI was 14.8 (standard deviation 8.7, range 0-36). Median survival for the complete CRS cohort was 6.1 years, while 5- and 10-year survival was 51.7% (standard error [SE] 4.6) and 36.1% (SE 6.3), respectively. Arbitrary cut-off PCI limits with 5-point splits (p = 0.63) were not predictive of a detrimental effect on survival as long as a complete CRS was achieved. A linear effect of the PCI on survival (p = 0.62) was not observed, and single-point PCI cohort splits within a PCI range of  10 were not predictive of survival for complete CRS patients. The PCI correlated with the ability to achieve a complete CRS, with a mean PCI of 14.7 (8.7) for completeness of cytoreduction (CC)0, 22.3 (7.8) for CC1 and 26.1 (9.5) for CC2/3 resections (p = 0.0001, hazard ratio 1.12, 95% confidence interval 1.09), with an HR of 1.15 for each 1-unit increase in the PCI score. Only 21% of the cohort achieved a complete CRS with a PCI ≥ 21. The PCI correlates with the ability to achieve a complete CRS in carcinomatosis from HGA. PCI is not associated with survival as long as a complete CRS can be achieved.

High Genomic Instability Predicts Survival in Metastatic High-Risk Neuroblastoma

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Sara Stigliani

2012-09-01

Full Text Available We aimed to identify novel molecular prognostic markers to better predict relapse risk estimate for children with high-risk (HR metastatic neuroblastoma (NB. We performed genome- and/or transcriptome-wide analyses of 129 stage 4 HR NBs. Children older than 1 year of age were categorized as “short survivors” (dead of disease within 5 years from diagnosis and “long survivors” (alive with an overall survival time ≥ 5 years. We reported that patients with less than three segmental copy number aberrations in their tumor represent a molecularly defined subgroup with a high survival probability within the current HR group of patients. The complex genomic pattern is a prognostic marker independent of NB-associated chromosomal aberrations, i.e., MYCN amplification, 1p and 11q losses, and 17q gain. Integrative analysis of genomic and expression signatures demonstrated that fatal outcome is mainly associated with loss of cell cycle control and deregulation of Rho guanosine triphosphates (GTPases functioning in neuritogenesis. Tumors with MYCN amplification show a lower chromosome instability compared to MYCN single-copy NBs (P = .0008, dominated by 17q gain and 1p loss. Moreover, our results suggest that the MYCN amplification mainly drives disruption of neuronal differentiation and reduction of cell adhesion process involved in tumor invasion and metastasis. Further validation studies are warranted to establish this as a risk stratification for patients.

Visceral fat area predicts survival in patients with advanced hepatocellular carcinoma treated with tyrosine kinase inhibitors.

Science.gov (United States)

Nault, Jean-Charles; Pigneur, Frédéric; Nelson, Anaïs Charles; Costentin, Charlotte; Tselikas, Lambros; Katsahian, Sandrine; Diao, Guoqing; Laurent, Alexis; Mallat, Ariane; Duvoux, Christophe; Luciani, Alain; Decaens, Thomas

2015-10-01

Anthropometric measurements have been linked to resistance to anti-angiogenic treatment and survival. Patients with advanced hepatocellular carcinoma treated with sorafenib or brivanib in 2008-2011 were included in this retrospective study. Anthropometric measurements were assessed using computed tomography and were correlated with drug toxicity, radiological response, and overall survival. 52 patients were included, Barcelona Clinic Liver Classification B (38%) and C (62%), with a mean value of α-fetoprotein of 29,554±85,654 ng/mL, with a median overall survival of 10.5 months. Sarcopenia was associated with a greater rate of hand-foot syndrome (P=0.049). Modified Response Evaluation Criteria In Solid Tumours (mRECIST) and Choi criteria were significantly associated with survival, but RECIST criteria were not. An absence of hand-foot syndrome and high-visceral fat area were associated with progressive disease as assessed by RECIST and mRECIST criteria. In multivariate analyses, high visceral fat area (HR=3.6; P=0.002), low lean body mass (HR=2.4; P=0.015), and presence of hand-foot syndrome (HR=1.8; P=0.004) were significantly associated with overall survival. In time-dependent multivariate analyses; only high visceral fat area was associated with survival. Visceral fat area is associated with survival and seems to be a predictive marker for primary resistance to tyrosine kinase inhibitors in patients with advanced hepatocellular carcinoma. Copyright © 2015 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Modelling survival: exposure pattern, species sensitivity and uncertainty.

Science.gov (United States)

Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G

2016-07-06

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Erratic tacrolimus exposure, assessed using the standard deviation of trough blood levels, predicts chronic lung allograft dysfunction and survival.

Science.gov (United States)

Gallagher, Harry M; Sarwar, Ghulam; Tse, Tracy; Sladden, Timothy M; Hii, Esmond; Yerkovich, Stephanie T; Hopkins, Peter M; Chambers, Daniel C

2015-11-01

Erratic tacrolimus blood levels are associated with liver and kidney graft failure. We hypothesized that erratic tacrolimus exposure would similarly compromise lung transplant outcomes. This study assessed the effect of tacrolimus mean and standard deviation (SD) levels on the risk of chronic lung allograft dysfunction (CLAD) and death after lung transplantation. We retrospectively reviewed 110 lung transplant recipients who received tacrolimus-based immunosuppression. Cox proportional hazard modeling was used to investigate the effect of tacrolimus mean and SD levels on survival and CLAD. At census, 48 patients (44%) had developed CLAD and 37 (34%) had died. Tacrolimus SD was highest for the first 6 post-transplant months (median, 4.01; interquartile range [IQR], 3.04-4.98 months) before stabilizing at 2.84 μg/liter (IQR, 2.16-4.13 μg/liter) between 6 and 12 months. The SD then remained the same (median, 2.85; IQR, 2.00-3.77 μg/liter) between 12 and 24 months. A high mean tacrolimus level 6 to 12 months post-transplant independently reduced the risk of CLAD (hazard ratio [HR], 0.74; 95% confidence interval [CI], 0.63-0.86; p < 0.001) but not death (HR, 0.96; 95% CI, 0.83-1.12; p = 0.65). In contrast, a high tacrolimus SD between 6 and 12 months independently increased the risk of CLAD (HR, 1.46; 95% CI, 1.23-1.73; p < 0.001) and death (HR, 1.27; 95% CI, 1.08-1.51; p = 0.005). Erratic tacrolimus levels are a risk factor for poor lung transplant outcomes. Identifying and modifying factors that contribute to this variability may significantly improve outcomes. Copyright © 2015 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Radiobilogical cell survival models

International Nuclear Information System (INIS)

Zackrisson, B.

1992-01-01

A central issue in clinical radiobiological research is the prediction of responses to different radiation qualities. The choice of cell survival and dose-response model greatly influences the results. In this context the relationship between theory and model is emphasized. Generally, the interpretations of experimental data depend on the model. Cell survival models are systematized with respect to their relations to radiobiological theories of cell kill. The growing knowlegde of biological, physical, and chemical mechanisms is reflected in the formulation of new models. The present overview shows that recent modelling has been more oriented towards the stochastic fluctuations connected to radiation energy deposition. This implies that the traditional cell surivival models ought to be complemented by models of stochastic energy deposition processes and repair processes at the intracellular level. (orig.)

A 4-miRNA signature to predict survival in glioblastomas

DEFF Research Database (Denmark)

Hermansen, Simon K; Sørensen, Mia D; Hansen, Anker

2017-01-01

multiple genes representing an additional level of gene regulation possibly more prognostically powerful than a single gene. The aim of the study was to identify a novel miRNA signature with the ability to separate patients into prognostic subgroups. Samples from 40 glioblastoma patients were included...... association to survival in univariate (HR 8.50; 95% CI 3.06-23.62; psignature of miR-107 and miR-331 (miR sum score), which were the only miRNAs available...

Development of a Summarized Health Index (SHI) for Use in Predicting Survival in Sea Turtles

Science.gov (United States)

Li, Tsung-Hsien; Chang, Chao-Chin; Cheng, I-Jiunn; Lin, Suen-Chuain

2015-01-01

Veterinary care plays an influential role in sea turtle rehabilitation, especially in endangered species. Physiological characteristics, hematological and plasma biochemistry profiles, are useful references for clinical management in animals, especially when animals are during the convalescence period. In this study, these factors associated with sea turtle surviving were analyzed. The blood samples were collected when sea turtles remained alive, and then animals were followed up for surviving status. The results indicated that significantly negative correlation was found between buoyancy disorders (BD) and sea turtle surviving (p turtles had significantly higher levels of aspartate aminotranspherase (AST), creatinine kinase (CK), creatinine and uric acid (UA) than surviving sea turtles (all p turtles and to improve veterinary care at rehabilitation facilities. PMID:25803431

The impact of hemoglobin levels on patient and graft survival in renal transplant recipients.

LENUS (Irish Health Repository)

Moore, Jason

2008-08-27

It remains unclear whether low hemoglobin levels are associated with increased mortality or graft loss after renal transplantation. This study assessed the relationship of hemoglobin levels with patient and graft survival in 3859 patients with functioning renal transplants more than 6-months posttransplantation.

Tumor Response and Survival Predicted by Post-Therapy FDG-PET/CT in Anal Cancer

International Nuclear Information System (INIS)

Schwarz, Julie K.; Siegel, Barry A.; Dehdashti, Farrokh; Myerson, Robert J.; Fleshman, James W.; Grigsby, Perry W.

2008-01-01

Purpose: To evaluate the response to therapy for anal carcinoma using post-therapy imaging with positron emission tomography (PET)/computed tomography and F-18 fluorodeoxyglucose (FDG) and to compare the metabolic response with patient outcome. Patients and Methods: This was a prospective cohort study of 53 consecutive patients with anal cancer. All patients underwent pre- and post-treatment whole-body FDG-PET/computed tomography. Patients had been treated with external beam radiotherapy and concurrent chemotherapy. Whole-body FDG-PET was performed 0.9-5.4 months (mean, 2.1) after therapy completion. Results: The post-therapy PET scan did not show any abnormal FDG uptake (complete metabolic response) in 44 patients. Persistent abnormal FDG uptake (partial metabolic response) was found in the anal tumor in 9 patients. The 2-year cause-specific survival rate was 94% for patients with a complete vs. 39% for patients with a partial metabolic response in the anal tumor (p = 0.0008). The 2-year progression-free survival rate was 95% for patients with a complete vs. 22% for patients with a partial metabolic response in the anal tumor (p < 0.0001). A Cox proportional hazards model of survival outcome indicated that a complete metabolic response was the most significant predictor of progression-free survival in our patient population (p = 0.0003). Conclusions: A partial metabolic response in the anal tumor as determined by post-therapy FDG-PET is predictive of significantly decreased progression-free and cause-specific survival after chemoradiotherapy for anal cancer

Identification of potential prognostic microRNA biomarkers for predicting survival in patients with hepatocellular carcinoma

Directory of Open Access Journals (Sweden)

Liao X

2018-04-01

Full Text Available Xiwen Liao,1 Guangzhi Zhu,1 Rui Huang,2 Chengkun Yang,1 Xiangkun Wang,1 Ketuan Huang,1 Tingdong Yu,1 Chuangye Han,1 Hao Su,1 Tao Peng1 1Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China Background: The aim of the present study was to identify potential prognostic microRNA (miRNA biomarkers for hepatocellular carcinoma (HCC prognosis prediction based on a dataset from The Cancer Genome Atlas (TCGA. Materials and methods: A miRNA sequencing dataset and corresponding clinical parameters of HCC were obtained from TCGA. Genome-wide univariate Cox regression analysis was used to screen prognostic differentially expressed miRNAs (DEMs, and multivariable Cox regression analysis was used for prognostic signature construction. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Results: Five miRNAs were regarded as prognostic DEMs and used for prognostic signature construction. The five-DEM prognostic signature performed well in prognosis prediction (adjusted P < 0.0001, adjusted hazard ratio = 2.249, 95% confidence interval =1.491–3.394, and time-dependent receiver–operating characteristic (ROC analysis showed an area under the curve (AUC of 0.765, 0.745, 0.725, and 0.687 for 1-, 2-, 3-, and 5-year HCC overall survival (OS prediction, respectively. Comprehensive survival analysis of the prognostic signature suggests that the risk score model could serve as an independent factor of HCC and perform better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of hsa-mir-139 and hsa-mir-5003 indicates that they were significantly enriched in multiple biological processes and pathways, including cell proliferation and cell migration

Molecular profiling of short-term and long-term surviving patients identifies CD34 mRNA level as prognostic for glioblastoma survival

DEFF Research Database (Denmark)

Michaelsen, Signe Regner; Urup, Thomas; Olsen, Lars Rønn

2018-01-01

Despite extensive treatment, overall survival (OS) for glioblastoma (GBM) remains poor. A small proportion of patients present long survival over 3 years, but the underlying molecular background separating these long-term survivors (LTS) from short-term survivors (STS) are insufficiently understood....... Accordingly, study aim was to identify independent prognostic biomarkers for survival. Study cohort consisted of 93 primary GBM patients treated with radiation-, chemo- and bevacizumab therapy, among which 14 STS (OS ≤ 12 months) and 6 LTS (OS ≥ 36 months) were identified, all confirmed being IDH wild......-type. RNA expression levels in diagnostic tumor specimen for 792 genes were analyzed by NanoString technology. While no differences were found with regard to GBM subtype between LTS versus STS, comparative analysis of individual genes identified 14 significantly differently expressed candidate genes...

Hemoglobin and hematocrit levels in the prediction of complicated Crohn's disease behavior--a cohort study.

Science.gov (United States)

Rieder, Florian; Paul, Gisela; Schnoy, Elisabeth; Schleder, Stephan; Wolf, Alexandra; Kamm, Florian; Dirmeier, Andrea; Strauch, Ulrike; Obermeier, Florian; Lopez, Rocio; Achkar, Jean-Paul; Rogler, Gerhard; Klebl, Frank

2014-01-01

Markers that predict the occurrence of a complicated disease behavior in patients with Crohn's disease (CD) can permit a more aggressive therapeutic regimen for patients at risk. The aim of this cohort study was to test the blood levels of hemoglobin (Hgb) and hematocrit (Hct) for the prediction of complicated CD behavior and CD related surgery in an adult patient population. Blood samples of 62 CD patients of the German Inflammatory Bowel Disease-network "Kompetenznetz CED" were tested for the levels of Hgb and Hct prior to the occurrence of complicated disease behavior or CD related surgery. The relation of these markers and clinical events was studied using Kaplan-Meier survival analysis and adjusted COX-proportional hazard regression models. The median follow-up time was 55.8 months. Of the 62 CD patients without any previous complication or surgery 34% developed a complication and/or underwent CD related surgery. Low Hgb or Hct levels were independent predictors of a shorter time to occurrence of the first complication or CD related surgery. This was true for early as well as late occurring complications. Stable low Hgb or Hct during serial follow-up measurements had a higher frequency of complications compared to patients with a stable normal Hgb or Hct, respectively. Determination of Hgb or Hct in complication and surgery naïve CD patients might serve as an additional tool for the prediction of complicated disease behavior.

Survival with 98% methemoglobin levels in a school-aged child during the "festival of colors".

Science.gov (United States)

Sankar, Jhuma; Devangare, Shashikant; Dubey, N K

2013-10-01

Methemoglobin levels more than 70% have almost always been reported to have been fatal. The case of a 4-year-old boy who survived with methemoglobin levels of 98% is presented here. He was brought to the emergency department with complaints of vomiting, pain abdomen, and altered sensorium following accidental ingestion of paint thinner mixed with "Holi" colors. On examination, the child was in altered sensorium, cyanosed with saturations of 55%, who did not respond despite positive pressure ventilation with 100% oxygen. A possibility of toxic methemoglobinemia was considered and confirmed by finding of elevated methemoglobin levels of 98%. The child survived with definitive therapy with methylene blue and aggressive goal-directed approach.

Comparison of continuous versus categorical tumor measurement-based metrics to predict overall survival in cancer treatment trials

Science.gov (United States)

An, Ming-Wen; Mandrekar, Sumithra J.; Branda, Megan E.; Hillman, Shauna L.; Adjei, Alex A.; Pitot, Henry; Goldberg, Richard M.; Sargent, Daniel J.

2011-01-01

Purpose The categorical definition of response assessed via the Response Evaluation Criteria in Solid Tumors has documented limitations. We sought to identify alternative metrics for tumor response that improve prediction of overall survival. Experimental Design Individual patient data from three North Central Cancer Treatment Group trials (N0026, n=117; N9741, n=1109; N9841, n=332) were used. Continuous metrics of tumor size based on longitudinal tumor measurements were considered in addition to a trichotomized response (TriTR: Response vs. Stable vs. Progression). Cox proportional hazards models, adjusted for treatment arm and baseline tumor burden, were used to assess the impact of the metrics on subsequent overall survival, using a landmark analysis approach at 12-, 16- and 24-weeks post baseline. Model discrimination was evaluated using the concordance (c) index. Results The overall best response rates for the three trials were 26%, 45%, and 25% respectively. While nearly all metrics were statistically significantly associated with overall survival at the different landmark time points, the c-indices for the traditional response metrics ranged from 0.59-0.65; for the continuous metrics from 0.60-0.66 and for the TriTR metrics from 0.64-0.69. The c-indices for TriTR at 12-weeks were comparable to those at 16- and 24-weeks. Conclusions Continuous tumor-measurement-based metrics provided no predictive improvement over traditional response based metrics or TriTR; TriTR had better predictive ability than best TriTR or confirmed response. If confirmed, TriTR represents a promising endpoint for future Phase II trials. PMID:21880789

Lung Shunt Fraction prior to Yttrium-90 Radioembolization Predicts Survival in Patients with Neuroendocrine Liver Metastases: Single-Center Prospective Analysis

Energy Technology Data Exchange (ETDEWEB)

Ludwig, Johannes M. [Yale University, Division of Interventional Radiology, Department of Radiology and Biomedical Imaging (United States); Ambinder, Emily McIntosh [John Hopkins University School of Medicine, Department of Diagnostic Radiology (United States); Ghodadra, Anish [University of Pittsburgh School of Medicine, Interventional Radiology, Department of Radiology (United States); Xing, Minzhi [Yale University, Division of Interventional Radiology, Department of Radiology and Biomedical Imaging (United States); Prajapati, Hasmukh J. [The University of Tennessee Health Science Center, Division of Interventional Radiology, Department of Radiology (United States); Kim, Hyun S., E-mail: kevin.kim@yale.edu [Yale University, Division of Interventional Radiology, Department of Radiology and Biomedical Imaging (United States)

2016-07-15

ObjectiveTo investigate survival outcomes following radioembolization with Yttrium-90 (Y90) for neuroendocrine tumor liver metastases (NETLMs). This study was designed to assess the efficacy of Y90 radioembolization and to evaluate lung shunt fraction (LSF) as a predictor for survival.MethodsA single-center, prospective study of 44 consecutive patients (median age: 58.5 years, 29.5 % male) diagnosed with pancreatic (52.3 %) or carcinoid (47.7 %) NETLMs from 2006 to 2012 who underwent Y90 radioembolization was performed. Patients’ baseline characteristics, including LSF and median overall survival (OS) from first Y90 radioembolization, were recorded and compared between patients with high (≥10 %) and low (<10 %) LSF. Baseline comparisons were performed using Fisher’s exact tests for categorical and Mann–Whitney U test for continuous variables. Survival was calculated using the Kaplan–Meier method. Univariate (Wilcoxon rank-sum test) and multivariate analyses (Cox Proportional Hazard Model) for risk factor analysis were performed.ResultsThere was no statistically significant difference in age, gender, race, tumor properties, or previous treatments between patients with high (n = 15) and low (n = 29) LSF. The median OS was 27.4 months (95 %CI 12.73–55.23), with 4.77 months (95 %CI 2.87–26.73) for high and 42.77 months (95 %CI 18.47–59.73) for low LSF (p = 0.003). Multivariate analysis identified high LSF (p = 0.001), total serum bilirubin >1.2 mg (p = 0.016), and lack of pretreatment with octreotide (p = 0.01) as independent prognostic factors for poorer survival. Tumor type and total radiation dose did not predict survival.ConclusionsLSF ≥10 %, elevated bilirubin levels, and lack of pretreatment with octreotide were found to be independent prognostic factors for poorer survival in patients with NETLMs.

Multi-level predictive maintenance for multi-component systems

International Nuclear Information System (INIS)

Nguyen, Kim-Anh; Do, Phuc; Grall, Antoine

2015-01-01

In this paper, a novel predictive maintenance policy with multi-level decision-making is proposed for multi-component system with complex structure. The main idea is to propose a decision-making process considered on two levels: system level and component one. The goal of the decision rules at the system level is to address if preventive maintenance actions are needed regarding the predictive reliability of the system. At component level the decision rules aim at identifying optimally a group of several components to be preventively maintained when preventive maintenance is trigged due to the system level decision. Selecting optimal components is based on a cost-based group improvement factor taking into account the predictive reliability of the components, the economic dependencies as well as the location of the components in the system. Moreover, a cost model is developed to find the optimal maintenance decision variables. A 14-component system is finally introduced to illustrate the use and the performance of the proposed predictive maintenance policy. Different sensitivity analysis are also investigated and discussed. Indeed, the proposed policy provides more flexibility in maintenance decision-making for complex structure systems, hence leading to significant profits in terms of maintenance cost when compared with existing policies. - Highlights: • A predictive maintenance policy for complex structure systems is proposed. • Multi-level decision process based on prognostic results is proposed. • A cost-based group importance measure is introduced for decision-making. • Both positive and negative dependencies between components are investigated. • A cost model and Monte Carlo simulation are developed for optimization process.

Prediction of survival in patients with Stage IV kidney cancer

Directory of Open Access Journals (Sweden)

L. V. Mirilenko

2015-01-01

Full Text Available The efficiency of treatment was evaluated and the predictors of adjusted survival (AS were identified in patients with disseminated kidney cancer treated at the Republican Research and Practical Center for Oncology and Medical Radiology in 1999 to 2011 (A.E. Okeanov, P.I. Moiseev, L.F. Levin. Malignant tumors in Belarus, 2001–2012. Edited by O.G. Sukonko. Seven factors (regional lymph node metastases; distant bone metastases; a high-grade tumor; sarcomatous tumor differentiation; hemoglobin levels of < 125 g/l in women and < 150 g/l in men; an erythrocyte sedimentation rate of 40 mm/h; palliative surgery were found to have an independent, unfavorable impact on AS. A multidimensional model was built to define what risk group low (no more than 2 poor factors, moderate (3–4 poor factors, and high (more than 4 poor factors the patients with Stage IV kidney cancer belonged to. In these groups, the median survival was 34.7, 17.2, and 4.0 months and 3-year AS rates were 48.6, 24.6, and 3.2 %, respectively. 

Predicting survival in oldest old people

NARCIS (Netherlands)

Taekema, Diana G.; Gussekloo, J.; Westendorp, Rudi G J; De Craen, Anton J M; Maier, Andrea B.

2012-01-01

Objective: Measures of physical performance are regarded as useful objective clinical tools to estimate survival in elderly people. However, oldest old people, aged 85 years or more, are underrepresented in earlier studies and frequently unable to perform functional tests. We studied the association

{sup 18}F-FDG PET/CT predicts survival after {sup 90}Y transarterial radioembolization in unresectable hepatocellular carcinoma

Energy Technology Data Exchange (ETDEWEB)

Jreige, Mario; Mitsakis, Periklis; Gucht, Axel van der; Pomoni, Anastasia; Silva-Monteiro, Marina; Boubaker, Ariane; Nicod-Lalonde, Marie; Prior, John O.; Schaefer, Niklaus [Lausanne University Hospital, Department of Nuclear Medicine and Molecular Imaging, Lausanne (Switzerland); Gnesin, Silvano [Lausanne University Hospital, Institute of Radiation Physics, Lausanne (Switzerland); Duran, Rafael; Denys, Alban [Lausanne University Hospital, Department of Radiodiagnostic and Interventional Radiology, Lausanne (Switzerland)

2017-07-15

To compare the value of pretreatment functional and morphological imaging parameters for predicting survival in patients undergoing transarterial radioembolization using yttrium-90 ({sup 90}Y-TARE) for unresectable hepatocellular carcinoma (uHCC). We analysed data from 48 patients in our prospective database undergoing {sup 90}Y-TARE treatment for uHCC (31 resin, 17 glass). All patients underwent {sup 18}F-FDG PET/CT and morphological imaging (CT and MRI scans) as part of a pretherapeutic work-up. Patients did not receive any treatment between these imaging procedures and {sup 90}Y-TARE. Kaplan-Meier estimates of progression-free survival (PFS) and overall survival (OS) were used to assess the prognostic value of {sup 18}F-FDG PET/CT metabolic parameters, including SUV{sub max}, tumour-to-liver (T/L) uptake ratio and SUV{sub mean} of healthy liver, and morphological data, including number and size of lesions, portal-venous infiltration (PVI). Relevant prognostic factors for HCC including Child-Pugh class, Barcelona Clinic Liver Cancer (BCLC) stage, tumour size, PVI and serum AFP level were compared with metabolic parameters in univariate and multivariate analyses. The median follow-up in living patients was 16.2 months (range 11.4-50.1 months). Relapse occurred in 34 patients (70.8%) at a median of 7.4 months (range 1.4-27.9 months) after {sup 90}Y-TARE, and relapse occurred in 24 of 34 patients (70.8%) who died from their disease at a median of 8.1 months (range 2.2-35.2 months). Significant prognostic markers for PFS were the mean and median lesion SUV{sub max} (both P = 0.01; median PFS 10.2 vs. 7.4 months), and significant prognostic markers for OS were the first quarter (Q1) cut-off values for lesion SUV{sub max} and T/L uptake ratio (both P = 0.02; median OS 30.9 vs. 9 months). The multivariate analysis confirmed that lesion SUV{sub max} and T/L uptake ratio were independent negative predictors of PFS (hazard ratio, HR, 2.7, 95% CI 1.2-6.1, P = 0.02, for mean

Demisability and survivability sensitivity to design-for-demise techniques

Science.gov (United States)

Trisolini, Mirko; Lewis, Hugh G.; Colombo, Camilla

2018-04-01

The paper is concerned with examining the effects that design-for-demise solutions can have not only on the demisability of components, but also on their survivability that is their capability to withstand impacts from space debris. First two models are introduced. A demisability model to predict the behaviour of spacecraft components during the atmospheric re-entry and a survivability model to assess the vulnerability of spacecraft structures against space debris impacts. Two indices that evaluate the level of demisability and survivability are also proposed. The two models are then used to study the sensitivity of the demisability and of the survivability indices as a function of typical design-for-demise options. The demisability and the survivability can in fact be influenced by the same design parameters in a competing fashion that is while the demisability is improved, the survivability is worsened and vice versa. The analysis shows how the design-for-demise solutions influence the demisability and the survivability independently. In addition, the effect that a solution has simultaneously on the two criteria is assessed. Results shows which, among the design-for-demise parameters mostly influence the demisability and the survivability. For such design parameters maps are presented, describing their influence on the demisability and survivability indices. These maps represent a useful tool to quickly assess the level of demisability and survivability that can be expected from a component, when specific design parameters are changed.

Lack of retroperitoneal lymphadenopathy predicts survival of patients with metastatic renal cell carcinoma.

Science.gov (United States)

Vasselli, J R; Yang, J C; Linehan, W M; White, D E; Rosenberg, S A; Walther, M M

2001-07-01

Patients with metastatic renal cell carcinoma have a reported 5-year survival of 0% to 20%. The ability to predict which patients would benefit from nephrectomy and interleukin-2 (IL-2) therapy before any treatment is initiated would be useful for maximizing the advantage of therapy and improving the quality of life. A retrospective analysis of the x-rays and charts of patients treated at the National Institutes of Health Surgery Branch between 1985 and 1996, who presented with metastatic renal cancer beyond the locoregional area and the primary tumor in place, was performed. Preoperative computerized tomography or magnetic resonance imaging, or radiological reports if no scans were available, were used to obtain an estimate of the volume of retroperitoneal lymphadenopathy. Operative notes were used to evaluate whether all lymphadenopathy was resected or disease left in situ, or if any extrarenal resection, including venacavotomy, was performed. Mean survival rate was calculated from the time of nephrectomy to the time of death or last clinical followup. If patients received IL-2 therapy, the response to treatment was recorded. Mean survival and response rate for IL-2 were compared among patients in 3 separate analyses. Patients without preoperatively detected lymphadenopathy were compared with those with at least 1 cm.3 retroperitoneal lymphadenopathy. Also, the patients who had detectable lymphadenopathy were divided into subgroups consisting of all resected, incompletely resected, unresectable and unknown if all disease was resected. Each subgroup was compared with patients without detectable preoperative lymphadenopathy. Patients with less than were compared to those with greater than 50 cm.3 retroperitoneal lymphadenopathy. Patients undergoing extrarenal resection at nephrectomy (complex surgery) due to direct invasion of the tumor into another intra-abdominal organ were compared with those undergoing radical nephrectomy alone, regardless of lymph node status

Expression of nerve growth factor and heme oxygenase-1 predict poor survival of breast carcinoma patients

International Nuclear Information System (INIS)

Noh, Sang Jae; Chung, Myoung Ja; Moon, Woo Sung; Kang, Myoung Jae; Jang, Kyu Yun; Bae, Jun Sang; Jamiyandorj, Urangoo; Park, Ho Sung; Kwon, Keun Sang; Jung, Sung Hoo; Youn, Hyun Jo; Lee, Ho; Park, Byung-Hyun

2013-01-01

Nerve growth factor (NGF) is a neurotrophin and has been suggested to induce heme oxygenase-1 (HO1) expression. Although the role of HO1 in tumorigenesis remains controversial, recent evidence suggests NGF and HO1 as tumor-progressing factors. However, the correlative role of NGF and HO1 and their prognostic impact in breast carcinoma is unknown. We investigated the expression and prognostic significance of the expression of NGF and HO1 in 145 cases of breast carcinoma. Immunohistochemical expression of NGF and HO1 was observed in 31% and 49% of breast carcinoma, respectively. The expression of NGF and HO1 significantly associated with each other, and both have a significant association with histologic grade, HER2 expression, and latent distant metastasis. The expression of NGF and HO1 predicted shorter overall survival of breast carcinoma by univariate and multivariate analysis. NGF expression was an independent prognostic indicator for relapse-free survival by multivariate analysis. The combined expression pattern of NGF and HO1 was also an independent prognostic indicator of overall survival and relapse-free survival. The patients with tumors expressing NGF had the shortest survival and the patients with tumor, which did not express NGF or HO1 showed the longest survival time. This study has demonstrated that individual expression of NGF or HO1, and the combined NGF/HO1 expression pattern could be prognostic indicators for breast carcinoma patients

The Glasgow Prognostic Score. An useful tool to predict survival in patients with advanced esophageal squamous cell carcinoma.

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Henry, Maria Aparecida Coelho de Arruda; Lerco, Mauro Masson; de Oliveira, Walmar Kerche; Guerra, Anderson Roberto; Rodrigues, Maria Aparecida Marchesan

2015-08-01

To evaluate the usefulness of the Glasgow Prognostic Score (GPS) in patients with esophageal carcinoma (EC). A total of 50 patients with EC were analyzed for GPS, nutritional and clinicopathologic parameters. Patients with CRP ≤ 1.0mg/L and albumin ≥ 3.5mg/L were considered as GPS = 0. Patients with only CRP increased or albumin decreased were classified as GPS = 1 and patients with CRP > 1.0mg/L and albumin L were considered as GPS = 2. GPS of 0, 1 and 2 were observed in seven, 23 and 20 patients, respectively. A significant inverse relationship was observed between GPS scores and the survival rate. The survival rate was greatest in patients with GPS = 0 and significantly higher than those from patients with GPS = 1 and GPS = 2. Minimum 12-month survival was observed in 71% patients with GPS = 0 and in 30% patients with GPS = 1. None of the patients with GPS = 2 survived for 12 months. A significant relationship between CRP or albumin individually and the survival rate was observed. No significant relationship among nutritional, clinic pathological parameters and survival was found. Glasgow Prognostic Score is an useful tool to predict survival in patients with esophageal carcinoma.

Albumin-Bilirubin and Platelet-Albumin-Bilirubin Grades Accurately Predict Overall Survival in High-Risk Patients Undergoing Conventional Transarterial Chemoembolization for Hepatocellular Carcinoma.

Science.gov (United States)

Hansmann, Jan; Evers, Maximilian J; Bui, James T; Lokken, R Peter; Lipnik, Andrew J; Gaba, Ron C; Ray, Charles E

2017-09-01

To evaluate albumin-bilirubin (ALBI) and platelet-albumin-bilirubin (PALBI) grades in predicting overall survival in high-risk patients undergoing conventional transarterial chemoembolization for hepatocellular carcinoma (HCC). This single-center retrospective study included 180 high-risk patients (142 men, 59 y ± 9) between April 2007 and January 2015. Patients were considered high-risk based on laboratory abnormalities before the procedure (bilirubin > 2.0 mg/dL, albumin 1.2 mg/dL); presence of ascites, encephalopathy, portal vein thrombus, or transjugular intrahepatic portosystemic shunt; or Model for End-Stage Liver Disease score > 15. Serum albumin, bilirubin, and platelet values were used to determine ALBI and PALBI grades. Overall survival was stratified by ALBI and PALBI grades with substratification by Child-Pugh class (CPC) and Barcelona Liver Clinic Cancer (BCLC) stage using Kaplan-Meier analysis. C-index was used to determine discriminatory ability and survival prediction accuracy. Median survival for 79 ALBI grade 2 patients and 101 ALBI grade 3 patients was 20.3 and 10.7 months, respectively (P  .05). ALBI and PALBI grades are accurate survival metrics in high-risk patients undergoing conventional transarterial chemoembolization for HCC. Use of these scores allows for more refined survival stratification within CPC and BCLC stage. Copyright © 2017 SIR. Published by Elsevier Inc. All rights reserved.

Impact of preoperative levels of hemoglobin and albumin on the survival of pancreatic carcinoma.

Science.gov (United States)

Ruiz-Tovar, J; Martín-Pérez, E; Fernández-Contreras, M E; Reguero-Callejas, M E; Gamallo-Amat, C

2010-11-01

Pancreatic cancer presents the worst survival rates of all neoplasms. Surgical resection is the only potentially curative treatment, but is associated with high complication rates and outcome is bad even in those resected cases. Therefore, candidates amenable for resection must be carefully selected. Identification of prognostic factors preoperatively may help to improve the treatment of these patients, focusing on individually management based on the expected response. We perform a retrospective study of 59 patients with histological diagnosis of pancreatic carcinoma between 1999 and 2003, looking for possible prognostic factors. We analyze 59 patients, 32 males and 27 females with a mean age of 63.8 years. All the patients were operated, performing palliative surgery in 32% and tumoral resection in 68%, including pancreaticoduodenectomies in 51% and distal pancreatectomy in 17%. Median global survival was 14 months (Range 1-110).We observed that preoperative levels of hemoglobin under 12 g/dl (p = 0.0006) and serum albumina under 2.8 g/dl (p = 0.021) are associated with worse survival. Preoperative levels of hemoglobin and serum albumina may be prognostic indicators in pancreatic cancer.

TH-E-BRF-05: Comparison of Survival-Time Prediction Models After Radiotherapy for High-Grade Glioma Patients Based On Clinical and DVH Features

International Nuclear Information System (INIS)

Magome, T; Haga, A; Igaki, H; Sekiya, N; Masutani, Y; Sakumi, A; Mukasa, A; Nakagawa, K

2014-01-01

Purpose: Although many outcome prediction models based on dose-volume information have been proposed, it is well known that the prognosis may be affected also by multiple clinical factors. The purpose of this study is to predict the survival time after radiotherapy for high-grade glioma patients based on features including clinical and dose-volume histogram (DVH) information. Methods: A total of 35 patients with high-grade glioma (oligodendroglioma: 2, anaplastic astrocytoma: 3, glioblastoma: 30) were selected in this study. All patients were treated with prescribed dose of 30–80 Gy after surgical resection or biopsy from 2006 to 2013 at The University of Tokyo Hospital. All cases were randomly separated into training dataset (30 cases) and test dataset (5 cases). The survival time after radiotherapy was predicted based on a multiple linear regression analysis and artificial neural network (ANN) by using 204 candidate features. The candidate features included the 12 clinical features (tumor location, extent of surgical resection, treatment duration of radiotherapy, etc.), and the 192 DVH features (maximum dose, minimum dose, D95, V60, etc.). The effective features for the prediction were selected according to a step-wise method by using 30 training cases. The prediction accuracy was evaluated by a coefficient of determination (R 2 ) between the predicted and actual survival time for the training and test dataset. Results: In the multiple regression analysis, the value of R 2 between the predicted and actual survival time was 0.460 for the training dataset and 0.375 for the test dataset. On the other hand, in the ANN analysis, the value of R 2 was 0.806 for the training dataset and 0.811 for the test dataset. Conclusion: Although a large number of patients would be needed for more accurate and robust prediction, our preliminary Result showed the potential to predict the outcome in the patients with high-grade glioma. This work was partly supported by the JSPS Core

SU-F-J-207: Non-Small Cell Lung Cancer Patient Survival Prediction with Quantitative Tumor Textures Analysis in Baseline CT

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Wu, Y; Zou, J; Murillo, P; Nosher, J; Amorosa, J; Bramwit, M; Yue, N; Jabbour, S; Foran, D [Rutgers University, New Brunswick, NJ (United States)

2016-06-15

Purpose: Chemo-radiation therapy (CRT) is widely used in treating patients with locally advanced non-small cell lung cancer (NSCLC). Determination of the likelihood of patient response to treatment and optimization of treatment regime is of clinical significance. Up to date, no imaging biomarker has reliably correlated to NSCLC patient survival rate. This pilot study is to extract CT texture information from tumor regions for patient survival prediction. Methods: Thirteen patients with stage II-III NSCLC were treated using CRT with a median dose of 6210 cGy. Non-contrast-enhanced CT images were acquired for treatment planning and retrospectively collected for this study. Texture analysis was applied in segmented tumor regions using the Local Binary Pattern method (LBP). By comparing its HU with neighboring voxels, the LBPs of a voxel were measured in multiple scales with different group radiuses and numbers of neighbors. The LBP histograms formed a multi-dimensional texture vector for each patient, which was then used to establish and test a Support Vector Machine (SVM) model to predict patients’ one year survival. The leave-one-out cross validation strategy was used recursively to enlarge the training set and derive a reliable predictor. The predictions were compared with the true clinical outcomes. Results: A 10-dimensional LBP histogram was extracted from 3D segmented tumor region for each of the 13 patients. Using the SVM model with the leave-one-out strategy, only 1 out of 13 patients was misclassified. The experiments showed an accuracy of 93%, sensitivity of 100%, and specificity of 86%. Conclusion: Within the framework of a Support Vector Machine based model, the Local Binary Pattern method is able to extract a quantitative imaging biomarker in the prediction of NSCLC patient survival. More patients are to be included in the study.

SU-F-J-207: Non-Small Cell Lung Cancer Patient Survival Prediction with Quantitative Tumor Textures Analysis in Baseline CT

International Nuclear Information System (INIS)

Wu, Y; Zou, J; Murillo, P; Nosher, J; Amorosa, J; Bramwit, M; Yue, N; Jabbour, S; Foran, D

2016-01-01

Purpose: Chemo-radiation therapy (CRT) is widely used in treating patients with locally advanced non-small cell lung cancer (NSCLC). Determination of the likelihood of patient response to treatment and optimization of treatment regime is of clinical significance. Up to date, no imaging biomarker has reliably correlated to NSCLC patient survival rate. This pilot study is to extract CT texture information from tumor regions for patient survival prediction. Methods: Thirteen patients with stage II-III NSCLC were treated using CRT with a median dose of 6210 cGy. Non-contrast-enhanced CT images were acquired for treatment planning and retrospectively collected for this study. Texture analysis was applied in segmented tumor regions using the Local Binary Pattern method (LBP). By comparing its HU with neighboring voxels, the LBPs of a voxel were measured in multiple scales with different group radiuses and numbers of neighbors. The LBP histograms formed a multi-dimensional texture vector for each patient, which was then used to establish and test a Support Vector Machine (SVM) model to predict patients’ one year survival. The leave-one-out cross validation strategy was used recursively to enlarge the training set and derive a reliable predictor. The predictions were compared with the true clinical outcomes. Results: A 10-dimensional LBP histogram was extracted from 3D segmented tumor region for each of the 13 patients. Using the SVM model with the leave-one-out strategy, only 1 out of 13 patients was misclassified. The experiments showed an accuracy of 93%, sensitivity of 100%, and specificity of 86%. Conclusion: Within the framework of a Support Vector Machine based model, the Local Binary Pattern method is able to extract a quantitative imaging biomarker in the prediction of NSCLC patient survival. More patients are to be included in the study.

Volumetric FDG-PET predicts overall and progression- free survival after 14 days of targeted therapy in metastatic renal cell carcinoma

International Nuclear Information System (INIS)

Farnebo, Jacob; Grybäck, Per; Harmenberg, Ulrika; Laurell, Anna; Wersäll, Peter; Blomqvist, Lennart K; Ullén, Anders; Sandström, Per

2014-01-01

To determine whether changes in the metabolism of metastatic renal cell carcinoma (mRCC) assessed by F18-FDG-PET after 14 and 28 days of treatment with tyrosine kinase inhibitors can predict overall and progression- free patient survival. Thirty-nine consecutive patients with mRCC were included prospectively and underwent PET examinations prior to and after 14 and 28 days of standard treatment with sunitinib (n = 18), sorafenib (n = 19) or pazopanib (n = 2). The PET response was analyzed in terms of SUVmax, SULpeak, and total lesion glycolysis and a positive response (defined as a 30% reduction) compared to overall and progression- free survival. Thirty-five patients with at least one metabolically active metastatic lesion prior to treatment underwent additional FDG-PET examinations after 14 (n = 32) and/or 28 days (n = 30) of treatment. Changes in either SULpeak or total lesion glycolysis were correlated to both progression-free and overall survival (for TLG2.5 responders, HR = 0.38 (95% CI: 0.18-0.83) and 0.22 (95% CI: 0.09-0.53), and for TLG50 responders, HR = 0.25 (0.10-0.62) and 0.25 (95% CI: 0.11-0.57) and for SULpeak responders, HR = 0.39 (95% CI: 0.17-0.91) and 0.38 (95% CI: 0.15-0.93), respectively). In contrast SUVmax response did not predict progression- free or overall survival (HR = 0.43 (95% CI: 0.18-1.01) and 0.50 (95% CI: 0.21-1.19), respectively). Assessment of early changes in SULpeak and total lesion glycolysis undergoing treatment with tyrosine kinase inhibitors by FDG-PET can possibly predict progression- free and overall survival in patients with mRCC

Expression of phosphorylated raf kinase inhibitor protein (pRKIP) is a predictor of lung cancer survival

International Nuclear Information System (INIS)

Huerta-Yepez, Sara; Chia, David; Bonavida, Benjamin; Goodglick, Lee; Yoon, Nam K; Hernandez-Cueto, Angeles; Mah, Vei; Rivera-Pazos, Clara M; Chatterjee, Devasis; Vega, Mario I; Maresh, Erin L; Horvath, Steve

2011-01-01

Raf-1 kinase inhibitor protein (RKIP) has been reported to negatively regulate signal kinases of major survival pathways. RKIP activity is modulated in part by phosphorylation on Serine 153 by protein kinase C, which leads to dissociation of RKIP from Raf-1. RKIP expression is low in many human cancers and represents an indicator of poor prognosis and/or induction of metastasis. The prognostic power has typically been based on total RKIP expression and has not considered the significance of phospho-RKIP. The present study examined the expression levels of both RKIP and phospho-RKIP in human lung cancer tissue microarray proteomics technology. Total RKIP and phospho-RKIP expression levels were similar in normal and cancerous tissues. phospho-RKIP levels slightly decreased in metastatic lesions. However, the expression levels of phospho-RKIP, in contrast to total RKIP, displayed significant predictive power for outcome with normal expression of phospho-RKIP predicting a more favorable survival compared to lower levels (P = 0.0118); this was even more pronounced in more senior individuals and in those with early stage lung cancer. This study examines for the first time, the expression profile of RKIP and phospho-RKIP in lung cancer. Significantly, we found that phospho-RKIP was a predictive indicator of survival

Circulating CD147 predicts mortality in advanced hepatocellular carcinoma.

Science.gov (United States)

Lee, Aimei; Rode, Anthony; Nicoll, Amanda; Maczurek, Annette E; Lim, Lucy; Lim, Seok; Angus, Peter; Kronborg, Ian; Arachchi, Niranjan; Gorelik, Alexandra; Liew, Danny; Warner, Fiona J; McCaughan, Geoffrey W; McLennan, Susan V; Shackel, Nicholas A

2016-02-01

The glycoprotein CD147 has a role in tumor progression, is readily detectable in the circulation, and is abundantly expressed in hepatocellular carcinoma (HCC). Advanced HCC patients are a heterogeneous group with some individuals having dismal survival. The aim of this study was to examine circulating soluble CD147 levels as a prognostic marker in HCC patients. CD147 was measured in 277 patients (110 HCC, 115 chronic liver disease, and 52 non-liver disease). Clinical data included etiology, tumor progression, Barcelona Clinic Liver Cancer (BCLC) stage, and treatment response. Patients with HCC were stratified into two groups based upon the 75th percentile of CD147 levels (24 ng/mL). CD147 in HCC correlated inversely with poor survival (P = 0.031). Increased CD147 predicted poor survival in BCLC stages C and D (P = 0.045), and CD147 levels >24 ng/mL predicted a significantly diminished 90-day and 180-day survival time (hazard ratio [HR] = 6.1; 95% confidence interval [CI]: 2.1-63.2; P = 0.0045 and HR = 2.8; 95% CI: 1.2-12.6; P = 0.028, respectively). In BCLC stage C, CD147 predicted prognosis; levels >24 ng/mL were associated with a median survival of 1.5 months compared with 6.5 months with CD147 levels ≤24 ng/mL (P = 0.03). CD147 also identified patients with a poor prognosis independent from treatment frequency, modality, and tumor size. Circulating CD147 is an independent marker of survival in advanced HCC. CD147 requires further evaluation as a potential new prognostic measure in HCC to identify patients with advanced disease who have a poor prognosis. © 2015 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

PD-L1 expression as a predictive biomarker in advanced non-small-cell lung cancer: updated survival data.

Science.gov (United States)

Aguiar, Pedro N; De Mello, Ramon Andrade; Hall, Peter; Tadokoro, Hakaru; Lima Lopes, Gilberto de

2017-05-01

The treatment of non-small-cell lung cancer has changed after the development of the immune checkpoint inhibitors. Although the most studied biomarker is PD-L1 expression, its clinical significance is still debatable. In this article, we show the updated survival analysis of all published data. We searched in network and conference data sources for relevant clinical studies of immunotherapy for non-small-cell lung cancer that assessed the PD-L1 expression even as an exploratory analysis. The updated survival hazard ratios (HR) were included in the analysis. 14 studies with 2857 patients were included (2019 treated with immunotherapy). The response rate was as higher among PD-L1-positive patients (RR: 2.19, 95% CI: 1.63-2.94). PD-L1 expression was also related to better progression-free survival (HR: 0.69, 95% CI: 0.57-0.85) and better overall survival (HR: 0.77, 95% CI: 0.67-0.89). PD-L1 overexpression predicts activity as well as better survival for patients treated with immune checkpoint inhibitors.

{sup 18}F-FDG PET independently predicts survival in patients with cholangiocellular carcinoma treated with {sup 90}Y microspheres

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Haug, Alexander R. [Ludwig-Maximilians-University, Department of Nuclear Medicine, Munich (Germany); Klinikum Grosshadern, Department of Nuclear Medicine, Munich (Germany); Heinemann, Volker [Ludwig-Maximilians-University, Department of Internal Medicine III, Munich (Germany); Bruns, Christiane J. [Ludwig-Maximilians-University, Department of Surgery, Munich (Germany); Hoffmann, Ralf; Jakobs, Tobias [Ludwig-Maximilians-University, Institute of Clinical Radiology, Munich (Germany); Bartenstein, Peter; Hacker, Marcus [Ludwig-Maximilians-University, Department of Nuclear Medicine, Munich (Germany)

2011-06-15

{sup 90}Y radioembolization has emerged as a valuable therapy for intrahepatic cholangiocellular carcinomas (ICC). We aimed to evaluate the prognostic power of FDG PET/CT and that of pretherapeutic scintigraphy with {sup 99m}Tc-labelled macroagglutinated albumin (MAA), an index of tumour vascularization. The study group comprised 26 consecutive patients suffering from nonresectable ICC. Before treatment with radioembolization, all patients underwent MRI of the liver, as well as MAA scintigraphy, which was followed immediately by SPECT(/CT) to quantify the liver-lung shunt fraction. Using image fusion, regions of interest were drawn around the tumours and the entire liver, and the tumour-to-liver quotient was calculated. In addition, FDG PET/CT was performed at baseline and 3 months after radioembolization, and the percentage changes in peak ({delta}SUV{sub max}) and mean ({delta}SUV{sub mean}) FDG uptake and in metabolic tumour volume ({delta}Vol{sub 2SD}) relative to baseline were calculated. Treatment response at 3 months was also assessed using contrast-enhanced MRI and CT on the basis of standard criteria. Of 23 patients in whom follow-up MRI was available, 5 (22%) showed a partial response, 15 (65%) stable disease and 3 (13%) progressive disease. The change in all FDG values significantly predicted survival by Kaplan-Meier analysis after radioembolization; {delta}Vol{sub 2SD} responders had a median survival of 97 weeks versus 30 weeks in nonresponders (P = 0.02), whereas {delta}SUV{sub max} and {delta}SUV{sub mean} responders had a median survival of 114 weeks (responder) versus 19 weeks (nonresponder) and 69 weeks in patients with stable disease (P < 0.05). Pretherapeutic MAA scintigraphy or MRI did not predict survival, nor did the presence of extrahepatic metastases, or prior therapies. Only {delta}Vol{sub 2SD} was significantly associated with survival by univariate analysis (hazard ratio 0.25; P = 0.04) and multivariate analysis (hazard ratio 0.20, P = 0

A neighborhood statistics model for predicting stream pathogen indicator levels.

Science.gov (United States)

Pandey, Pramod K; Pasternack, Gregory B; Majumder, Mahbubul; Soupir, Michelle L; Kaiser, Mark S

2015-03-01

Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale.

Circulating C3 levels predict renal and global outcome in patients with renal vasculitis.

Science.gov (United States)

Villacorta, Javier; Diaz-Crespo, Francisco; Acevedo, Mercedes; Cavero, Teresa; Guerrero, Carmen; Praga, Manuel; Fernandez-Juarez, Gema

2016-11-01

Several studies have demonstrated the crucial role of complement activation in the pathogenesis of ANCA-associated vasculitis. We aimed to assess the association between baseline serum C3 (sC3) levels and long-term outcomes in patients with renal vasculitis. This retrospective study included 111 patients with renal vasculitis from three hospitals who underwent a renal biopsy between 1997 and 2014. Serum levels of C3 were measured at the onset and the study population was divided into three tertiles according to sC3 concentrations (tertile 1 128 mg/dl). Patients with lower sC3 (tertile 1) were compared with those having higher levels of sC3 (tertile 2 and tertile 3). Histological, clinical, and laboratory data were recorded for analysis. The primary end point was the composite of end-stage renal disease (ESRD) and death from any cause. Lower sC3 levels were associated with a higher need for dialysis and lower response rate to treatment (p = 0.04 and p = 0.007, respectively). Renal and global survival at 1 and 5 years was 53 and 46 % in patients with lower sC3 (tertile 1) compared with 72 and 65 % in patients with higher sC3 (upper two tertiles) (p = 0.04). In a multivariate Cox-regression model, when adjusted by renal function and histopatholologic categories, lower sC3 remained as an independent predictor of ESRD and death (HR, 1.9; 95 % CI, 1.1 to 3.4; p = 0.02). Baseline serum C3 levels have an independent prognostic value in predicting long-term renal and global survival in patients with renal vasculitis.

Predicting the Performance and Survival of Islamic Banks in Malaysia to Achieve Growth Sustainability

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Mazuin Sapuan Noraina

2017-01-01

Full Text Available In Malaysia, the growth of the Islamic financial industry has increased tremendously in line with the Government’s ambition to make Malaysia as an international hub for Islamic finance since 2010. With the increasing number of foreign players in this industry plus with the increasing demand from domestic and foreign customers would further enhance the possibility for Malaysia to achieve this ambition. Currently, according to the Economic Transformation Programme, 2012 Malaysia is the world’s third largest market for Shariah assets that cover Islamic banks, Takaful, and sukuk. Malaysia as one of the main contributors to the global Islamic financial assets with Islamic assets in Malaysia grew by 23.8% in 2011 from RM350.8bil to RM434.6bil. The issues of predicting the performance and the survival of Islamic Banks in Malaysia become amongst crucial issues in academic research. By employing multi – layer perceptron neural network and pooled regression, we found that total assets/ size of the Islamic banks (GROWTH have high weightage and significantly influence in predicting the performance and the survival of Islamic banks in Malaysia. With the increasing number of Islamic banking institutions in Malaysia, this study can give insight on the sustainability of the Islamic banking system in Malaysia for the benefit of the investors, shareholder and depositors.

Novel biomarker-based model for the prediction of sorafenib response and overall survival in advanced hepatocellular carcinoma: a prospective cohort study.

Science.gov (United States)

Kim, Hwi Young; Lee, Dong Hyeon; Lee, Jeong-Hoon; Cho, Young Youn; Cho, Eun Ju; Yu, Su Jong; Kim, Yoon Jun; Yoon, Jung-Hwan

2018-03-20

Prediction of the outcome of sorafenib therapy using biomarkers is an unmet clinical need in patients with advanced hepatocellular carcinoma (HCC). The aim was to develop and validate a biomarker-based model for predicting sorafenib response and overall survival (OS). This prospective cohort study included 124 consecutive HCC patients (44 with disease control, 80 with progression) with Child-Pugh class A liver function, who received sorafenib. Potential serum biomarkers (namely, hepatocyte growth factor [HGF], fibroblast growth factor [FGF], vascular endothelial growth factor receptor-1, CD117, and angiopoietin-2) were tested. After identifying independent predictors of tumor response, a risk scoring system for predicting OS was developed and 3-fold internal validation was conducted. A risk scoring system was developed with six covariates: etiology, platelet count, Barcelona Clinic Liver Cancer stage, protein induced by vitamin K absence-II, HGF, and FGF. When patients were stratified into low-risk (score ≤ 5), intermediate-risk (score 6), and high-risk (score ≥ 7) groups, the model provided good discriminant functions on tumor response (concordance [c]-index, 0.884) and 12-month survival (area under the curve [AUC], 0.825). The median OS was 19.0, 11.2, and 6.1 months in the low-, intermediate-, and high-risk group, respectively (P functions on tumor response (c-index, 0.825) and 12-month survival (AUC, 0.803), and good calibration functions (all P > 0.05 between expected and observed values). This new model including serum FGF and HGF showed good performance in predicting the response to sorafenib and survival in patients with advanced HCC.

FORECASTING OF SURVIVAL OF CHILDREN WITH THE PRENATALLY DIAGNOSED PATHOLOGY OF THE CARDIOVASCULAR SYSTEM

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Анна Валериевна Дубовая

2018-05-01

Full Text Available The development of effective methods for the analysis and prognosis of the survival of newborns with prenatally diagnosed congenital malformations of the cardiovascular system are the urgent task of modern medicine. Objective – a neural network model for predicting the survival of children with prenatally diagnosed congenital malformations of the cardiovascular system was developed. Materials and methods. To create the artificial neural networks, the method of constructing multifactor mathematical prediction models in the software package Statistica 6.0 was used. The significance level of the factors influencing the survival of children with prenatally diagnosed congenital malformations of the cardiovascular system was determined using Wald statistics. When checking statistical hypotheses, the critical level of significance was assumed to be 0,05. Results. A neural network model for the determination of the probability of survival of a child with prenatally diagnosed congenital malformations of the cardiovascular system, which has a high prognostic ability of 0,88, sensitivity of the model was 77,6 %, specificity 86,4 %. The value of prognostic survival probability is in the range from 0 to 100 %. With an indicator value of more than 80 %, the probability of survival of a child with prenatally diagnosed congenital malformations of the cardiovascular system is estimated as high, ranging from 20 % to 80 % – as an average and less than 20 % – as low. Conclusion. In the algorithm for predicting the survival of children with prenatally diagnosed congenital malformations of the cardiovascular system it is necessary to include a combination with other pathology of cardiovascular system, with other organs and systems, with chromosomal abnormalities, with microdeletion and monogenic syndromes.

Vitamin D Levels Predict Multiple Sclerosis Progression

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... Research Matters NIH Research Matters February 3, 2014 Vitamin D Levels Predict Multiple Sclerosis Progression Among people ... sclerosis (MS), those with higher blood levels of vitamin D had better outcomes during 5 years of ...

Impact of County-Level Socioeconomic Status on Oropharyngeal Cancer Survival in the United States.

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Megwalu, Uchechukwu C

2017-04-01

Objective To evaluate the impact of county-level socioeconomic status on survival in patients with oropharyngeal cancer in the United States. Study Design Retrospective cohort study via a large population-based cancer database. Methods Data were extracted from the SEER 18 database (Surveillance, Epidemiology, and End Results) of the National Cancer Institute. The study cohort included 18,791 patients diagnosed with oropharyngeal squamous cell carcinoma between 2004 and 2012. Results Patients residing in counties with a low socioeconomic status index had worse overall survival (56.5% vs 63.0%, P socioeconomic status index. On multivariable analysis, residing in a county with a low socioeconomic status index was associated with worse overall survival (hazard ratio, 1.21; 95% CI, 1.14-1.29; P status, year of diagnosis, site, American Joint Committee on Cancer stage group, presence of distant metastasis, presence of unresectable tumor, histologic grade, surgical resection of primary site, treatment with neck dissection, and radiation therapy. Conclusion Residing in a county with a low socioeconomic status index is associated with worse survival. Further research is needed to elucidate the mechanism by which socioeconomic status affects survival in oropharyngeal cancer.

The inflammation-based Glasgow Prognostic Score predicts survival in patients with cervical cancer.

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Polterauer, Stephan; Grimm, Christoph; Seebacher, Veronika; Rahhal, Jasmin; Tempfer, Clemens; Reinthaller, Alexander; Hefler, Lukas

2010-08-01

The Glasgow Prognostic Score (GPS) is known to reflect the degree of tumor-associated cachexia and inflammation and is associated with survival in various malignancies. We investigated the value of the GPS in patients with cervical cancer. We included 244 consecutive patients with cervical cancer in our study. The pretherapeutic GPS was calculated as follows: patients with elevated C-reactive protein serum levels (>10 mg/L) and hypoalbuminemia (L) were allocated a score of 2, and patients with 1 or no abnormal value were allocated a score of 1 or 0, respectively. The association between GPS and survival was evaluated by univariate log-rank tests and multivariate Cox regression models. The GPS was correlated with clinicopathologic parameters as shown by performing chi2 tests. In univariate analyses, GPS (P GPS (P = 0.03, P = 0.04), FIGO stage (P = 0.006, P = 0.006), and lymph node involvement (P = 0.003, P = 0.002), but not patients' age (P = 0.5, P = 0.5), histological grade (P = 0.7, P = 0.6), and histological type (P = 0.4, P = 0.6) were associated with disease-free and overall survival, respectively. The GPS was associated with FIGO stage (P GPS can be used as an inflammation-based predictor for survival in patients with cervical cancer.

CA 19-9 as a Marker of Survival and a Predictor of Metastization in Cholangiocarcinoma

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Rosa Coelho

2017-02-01

Full Text Available Background: Cholangiocarcinoma is the second most frequent primitive liver malignancy and is responsible for 3% of the malignant gastrointestinal neoplasms. The aims of this study were to determine the association of serum levels of CA 19-9 at diagnosis with other clinical data and serum liver function tests and to identify possible factors that influence the survival rates during follow-up. Methods: Retrospective observational study of 89 patients with a diagnosis of cholangiocarcinoma followed at the Department of Gastroenterology during 5 years. Statistical analyses were performed using SPSS version 20.0. Results: Patients were followed up for a median time of 127 days (IQR: 48-564, and the median age at diagnosis was 71.0 years (IQR: 62.0-77.5. The median survival rate was 14.0 months (IQR: 4.3-23.7, and the mortality rate was 79%. Patients with CA 19-9 levels ≥103 U/L had lower albumin levels and higher levels of alanine aminotransferase and γ-glutamyltransferase. CA 19-9 levels ≥103 U/L were associated with a higher probability of metastization (p = 0.001 and lower rates of treatment with curative intent (p = 0.024. In a multivariate analysis, CA 19-9 levels Conclusion: Predictive factors for overall survival were identified, namely presence of metastasis, surgery, and chemotherapy. CA 19-9 levels ≥103 U/L were predictive factors for survival and metastization.

SU-E-T-427: Cell Surviving Fractions Derived From Tumor-Volume Variation During Radiotherapy for Non-Small Cell Lung Cancer: Comparison with Predictive Assays

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Chvetsov, A; Schwartz, J; Mayr, N [University of Washington, Seattle, WA (United States); Yartsev, S [London Health Sciences Centre, London, Ontario (Canada)

2014-06-01

Purpose: To show that a distribution of cell surviving fractions S{sub 2} in a heterogeneous group of patients can be derived from tumor-volume variation curves during radiotherapy for non-small cell lung cancer. Methods: Our analysis was based on two data sets of tumor-volume variation curves for heterogeneous groups of 17 patients treated for nonsmall cell lung cancer with conventional dose fractionation. The data sets were obtained previously at two independent institutions by using megavoltage (MV) computed tomography (CT). Statistical distributions of cell surviving fractions S{sup 2} and cell clearance half-lives of lethally damaged cells T1/2 have been reconstructed in each patient group by using a version of the two-level cell population tumor response model and a simulated annealing algorithm. The reconstructed statistical distributions of the cell surviving fractions have been compared to the distributions measured using predictive assays in vitro. Results: Non-small cell lung cancer presents certain difficulties for modeling surviving fractions using tumor-volume variation curves because of relatively large fractional hypoxic volume, low gradient of tumor-volume response, and possible uncertainties due to breathing motion. Despite these difficulties, cell surviving fractions S{sub 2} for non-small cell lung cancer derived from tumor-volume variation measured at different institutions have similar probability density functions (PDFs) with mean values of 0.30 and 0.43 and standard deviations of 0.13 and 0.18, respectively. The PDFs for cell surviving fractions S{sup 2} reconstructed from tumor volume variation agree with the PDF measured in vitro. Comparison of the reconstructed cell surviving fractions with patient survival data shows that the patient survival time decreases as the cell surviving fraction increases. Conclusion: The data obtained in this work suggests that the cell surviving fractions S{sub 2} can be reconstructed from the tumor volume

SU-E-T-427: Cell Surviving Fractions Derived From Tumor-Volume Variation During Radiotherapy for Non-Small Cell Lung Cancer: Comparison with Predictive Assays

International Nuclear Information System (INIS)

Chvetsov, A; Schwartz, J; Mayr, N; Yartsev, S

2014-01-01

Purpose: To show that a distribution of cell surviving fractions S 2 in a heterogeneous group of patients can be derived from tumor-volume variation curves during radiotherapy for non-small cell lung cancer. Methods: Our analysis was based on two data sets of tumor-volume variation curves for heterogeneous groups of 17 patients treated for nonsmall cell lung cancer with conventional dose fractionation. The data sets were obtained previously at two independent institutions by using megavoltage (MV) computed tomography (CT). Statistical distributions of cell surviving fractions S 2 and cell clearance half-lives of lethally damaged cells T1/2 have been reconstructed in each patient group by using a version of the two-level cell population tumor response model and a simulated annealing algorithm. The reconstructed statistical distributions of the cell surviving fractions have been compared to the distributions measured using predictive assays in vitro. Results: Non-small cell lung cancer presents certain difficulties for modeling surviving fractions using tumor-volume variation curves because of relatively large fractional hypoxic volume, low gradient of tumor-volume response, and possible uncertainties due to breathing motion. Despite these difficulties, cell surviving fractions S 2 for non-small cell lung cancer derived from tumor-volume variation measured at different institutions have similar probability density functions (PDFs) with mean values of 0.30 and 0.43 and standard deviations of 0.13 and 0.18, respectively. The PDFs for cell surviving fractions S 2 reconstructed from tumor volume variation agree with the PDF measured in vitro. Comparison of the reconstructed cell surviving fractions with patient survival data shows that the patient survival time decreases as the cell surviving fraction increases. Conclusion: The data obtained in this work suggests that the cell surviving fractions S 2 can be reconstructed from the tumor volume variation curves measured

Increased serum levels of tumour-associated trypsin inhibitor independently predict a poor prognosis in colorectal cancer patients

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Gaber Alexander

2010-09-01

Full Text Available Abstract Background There is an insufficient number of reliable prognostic and response predictive biomarkers in colorectal cancer (CRC management. In a previous study, we found that high tumour tissue expression of tumour-associated trypsin inhibitor (TATI correlated with liver metastasis and an impaired prognosis in CRC. The aim of this study was to investigate the prognostic validity of serum TATI (s-TATI in CRC. We further assessed the prognostic value of carcino-embryonic antigen in serum (s-CEA and the interrelationship between s-TATI and TATI in tissue (t-TATI. Methods Using an immunofluorometric assay, s-TATI levels were analysed in 334 preoperatively collected serum samples from patients with CRC. Spearman's Rho and Chi-square test were used for analysis of correlations between s-TATI and clinicopathological parameters, s-CEA and t-TATI. Kaplan-Meier analysis and Cox uni- and multivariate regression analysis were used to estimate disease free survival (DFS and overall survival (OS according to quartiles of s-TATI and cut-offs derived from ROC-analysis of s-TATI and s-CEA. Results Increased levels of s-TATI were associated with a reduced DFS (HR = 2.00; 95% CI 1.40-2.84, P P P = 0.034 for DFS and HR = 1.78; 95% CI 1.25-2.53, P = 0.001 for OS. There was no significant association between s-TATI and t-TATI. The prognostic value of s-CEA was also evident, but somewhat weaker than for s-TATI. Conclusions High preoperative s-TATI levels predict a poor prognosis in patients with CRC, and the prognostic value is independent of established prognostic parameters and t-TATI expression. These data suggest that s-TATI might be a useful marker for prognostic stratification in CRC.

Foxp3 overexpression in tumor cells predicts poor survival in oral squamous cell carcinoma

International Nuclear Information System (INIS)

Song, Jing-Jing; Zhao, Si-Jia; Fang, Juan; Ma, Da; Liu, Xiang-Qi; Chen, Xiao-Bing; Wang, Yun; Cheng, Bin; Wang, Zhi

2016-01-01

Forkhead Box P3 (Foxp3) is a regulatory T cells marker, and its expression correlates with prognosis in a number of malignancies. The aim of this study is to determine the relationship of Foxp3 expression with clinicopathological parameters and prognosis in oral squamous cell carcinoma (OSCC). Foxp3 expression was examined using immunohistochemistry (IHC) in paraffin-embedded tissue samples from 273 OSCC patients. Statistical analysis was performed to evaluate the associations between Foxp3 expression, the clinicopathologic characteristics and prognostic factors in OSCC. Foxp3 protein expression was significantly associated with lymph node metastasis (P <0.01). Both univariate and multivariate analyses revealed that Foxp3 was an independent factor for both 5 years overall survival (OS) and relapse-free survival (RFS) (both P <0.01). Patients with Foxp3 overexpression had shorter OS and RFS. Our results determined that elevated Foxp3 protein expression was a predictive factor of outcome in OSCC and could act as a promising therapeutic target

Development and internal validation of a prognostic model to predict recurrence free survival in patients with adult granulosa cell tumors of the ovary

NARCIS (Netherlands)

van Meurs, Hannah S.; Schuit, Ewoud; Horlings, Hugo M.; van der Velden, Jacobus; van Driel, Willemien J.; Mol, Ben Willem J.; Kenter, Gemma G.; Buist, Marrije R.

2014-01-01

Models to predict the probability of recurrence free survival exist for various types of malignancies, but a model for recurrence free survival in individuals with an adult granulosa cell tumor (GCT) of the ovary is lacking. We aimed to develop and internally validate such a prognostic model. We

Clinical Predictors of Survival for Patients with Stage IV Cancer Referred to Radiation Oncology.

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Johnny Kao

Full Text Available There is an urgent need for a robust, clinically useful predictive model for survival in a heterogeneous group of patients with metastatic cancer referred to radiation oncology.From May 2012 to August 2013, 143 consecutive patients with stage IV cancer were prospectively evaluated by a single radiation oncologist. We retrospectively analyzed the effect of 29 patient, laboratory and tumor-related prognostic factors on overall survival using univariate analysis. Variables that were statistically significant on univariate analysis were entered into a multivariable Cox regression to identify independent predictors of overall survival.The median overall survival was 5.5 months. Four prognostic factors significantly predicted survival on multivariable analysis including ECOG performance status (0-1 vs. 2 vs. 3-4, number of active tumors (1 to 5 vs. ≥ 6, albumin levels (≥ 3.4 vs. 2.4 to 3.3 vs. 31.4 months for very low risk patients compared to 14.5 months for low risk, 4.1 months for intermediate risk and 1.2 months for high risk (p < 0.001.These data suggest that a model that considers performance status, extent of disease, primary tumor site and serum albumin represents a simple model to accurately predict survival for patients with stage IV cancer who are potential candidates for radiation therapy.

Serum levels of IGF-1 and IGF-BP3 are associated with event-free survival in adult Ewing sarcoma patients treated with chemotherapy

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de Groot S

2017-06-01

Full Text Available Stefanie de Groot,1 Hans Gelderblom,1 Marta Fiocco,2,3 Judith VMG Bovée,4 Jacobus JM van der Hoeven,1 Hanno Pijl,5 Judith R Kroep1 1Department of Medical Oncology, 2Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, 3Mathematical Department, Leiden University, 4Department of Pathology, 5Department of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands Background: Activation of the insulin-like growth factor 1 (IGF-1 pathway is involved in cell growth and proliferation and is associated with tumorigenesis, tumor progression, and therapy resistance in solid tumors. We examined whether variability in serum levels of IGF-1, IGF-2, and IGF-binding protein 3 (IGF-BP3 can predict event-free survival (EFS and overall survival (OS in Ewing sarcoma patients treated with chemotherapy.Patients and methods: Serum levels of IGF-1, IGF-2, and IGF-BP3 of 22 patients with localized or metastasized Ewing sarcoma treated with six cycles of vincristine/ifosfamide/doxorubicin/etoposide (VIDE chemotherapy were recorded. Baseline levels were compared with presixth cycle levels using paired t-tests and were tested for associations with EFS and OS. Continuous variables were dichotomized according to the Contal and O’Quigley procedure. Survival analyses were performed using Cox regression analysis.Results: High baseline IGF-1 and IGF-BP3 serum levels were associated with EFS (hazard ratio [HR] 0.075, 95% confidence interval [CI] 0.009–0.602 and HR 0.090, 95% CI 0.011–0.712, respectively in univariate and multivariate analyses (HR 0.063, 95% CI 0.007–0.590 and HR 0.057, 95% CI 0.005–0.585, respectively. OS was improved, but this was not statistically significant. IGF-BP3 and IGF-2 serum levels increased during treatment with VIDE chemotherapy (P=0.055 and P=0.023, respectively.Conclusion: High circulating serum levels of IGF-1 and IGF-BP3 and the molar ratio of IGF-1:IGF-BP3 serum levels were associated

The multidimensional behavioural hypervolumes of two interacting species predict their space use and survival.

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Lichtenstein, James L L; Wright, Colin M; McEwen, Brendan; Pinter-Wollman, Noa; Pruitt, Jonathan N

2017-10-01

Individual animals differ consistently in their behaviour, thus impacting a wide variety of ecological outcomes. Recent advances in animal personality research have established the ecological importance of the multidimensional behavioural volume occupied by individuals and by multispecies communities. Here, we examine the degree to which the multidimensional behavioural volume of a group predicts the outcome of both intra- and interspecific interactions. In particular, we test the hypothesis that a population of conspecifics will experience low intraspecific competition when the population occupies a large volume in behavioural space. We further hypothesize that populations of interacting species will exhibit greater interspecific competition when one or both species occupy large volumes in behavioural space. We evaluate these hypotheses by studying groups of katydids ( Scudderia nymphs) and froghoppers ( Philaenus spumarius ), which compete for food and space on their shared host plant, Solidago canadensis . We found that individuals in single-species groups of katydids positioned themselves closer to one another, suggesting reduced competition, when groups occupied a large behavioural volume. When both species were placed together, we found that the survival of froghoppers was greatest when both froghoppers and katydids occupied a small volume in behavioural space, particularly at high froghopper densities. These results suggest that groups that occupy large behavioural volumes can have low intraspecific competition but high interspecific competition. Thus, behavioural hypervolumes appear to have ecological consequences at both the level of the population and the community and may help to predict the intensity of competition both within and across species.

Pretreatment tumor SUV{sub max} predicts disease-specific and overall survival in patients with head and neck soft tissue sarcoma

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Ha, Seung Cheol; Roh, Jong-Lyel; Choi, Seung-Ho; Nam, Soon Yuhl; Kim, Sang Yoon [University of Ulsan College of Medicine, Departments of Otolaryngology, Asan Medical Center, Songpa-gu, Seoul (Korea, Republic of); Oh, Jungsu S.; Moon, Hyojeong; Kim, Jae Seung [University of Ulsan College of Medicine, Departments of Nuclear Medicine, Asan Medical Center, Seoul (Korea, Republic of); Cho, Kyung-Ja [University of Ulsan College of Medicine, Departments of Pathology, Asan Medical Center, Seoul (Korea, Republic of)

2017-01-15

Head and neck soft tissue sarcoma (HNSTS) is a rare type of tumor with various histological presentations and clinical behaviors. {sup 18}F-FDG PET/CT is being increasingly used for staging, grading, and predicting treatment outcomes in various types of human cancers, although this modality has been rarely studied in the survival prediction of HNSTS. Here we examined the prognostic value of tumor metabolic parameters measured using {sup 18}F-FDG PET/CT in patients with HNSTS. This study included 36 consecutive patients with HNSTS who underwent {sup 18}F-FDG PET/CT scanning prior to treatment at our institution. Tumor gross total volume (GTV) was measured from pretreatment contrast-enhanced CT scans, and maximum standardized uptake value (SUV{sub max}), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured using pretreatment {sup 18}F-FDG PET/CT scans. Univariate and multivariate Cox proportional hazard regression analyses were used to identify associations between imaging parameters and disease-specific survival (DSS) or overall survival (OS). Univariate analyses showed that SUV{sub max}, MTV, and TLG, but not GTV, were significantly associated with DSS and OS (all P < 0.05). After controlling for clinicopathological factors, SUV{sub max}, MTV, and TLG were significantly associated with DSS and OS (all P < 0.05). Patients with a tumor SUV{sub max} value of >7.0 experienced an approximately fivefold increase in mortality in terms of DSS and OS relative to those with a tumor SUV{sub max} <7.0. Quantitative metabolic measurements on pretreatment {sup 18}F-FDG PET/CT can yield values that are significantly predictive of survival after treatment for HNSTS. (orig.)

Predicting treatment effect from surrogate endpoints and historical trials: an extrapolation involving probabilities of a binary outcome or survival to a specific time.

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Baker, Stuart G; Sargent, Daniel J; Buyse, Marc; Burzykowski, Tomasz

2012-03-01

Using multiple historical trials with surrogate and true endpoints, we consider various models to predict the effect of treatment on a true endpoint in a target trial in which only a surrogate endpoint is observed. This predicted result is computed using (1) a prediction model (mixture, linear, or principal stratification) estimated from historical trials and the surrogate endpoint of the target trial and (2) a random extrapolation error estimated from successively leaving out each trial among the historical trials. The method applies to either binary outcomes or survival to a particular time that is computed from censored survival data. We compute a 95% confidence interval for the predicted result and validate its coverage using simulation. To summarize the additional uncertainty from using a predicted instead of true result for the estimated treatment effect, we compute its multiplier of standard error. Software is available for download. © 2011, The International Biometric Society No claim to original US government works.

Physical activity increases survival after heart valve surgery

DEFF Research Database (Denmark)

Lund, K.; Sibilitz, Kirstine Lærum; Kikkenborg Berg, Selina

2016-01-01

physical activity levels 6-12 months after heart valve surgery and (1) survival, (2) hospital readmission 18-24 months after surgery and (3) participation in exercise-based cardiac rehabilitation. METHODS: Prospective cohort study with registry data from The CopenHeart survey, The Danish National Patient......OBJECTIVES: Increased physical activity predicts survival and reduces risk of readmission in patients with coronary heart disease. However, few data show how physical activity is associated with survival and readmission after heart valve surgery. Objective were to assess the association between...... Register and The Danish Civil Registration System of 742 eligible patients. Physical activity was quantified with the International Physical Activity Questionnaire and analysed using Kaplan-Meier analysis and Cox regression and logistic regression methods. RESULTS: Patients with a moderate to high physical...

Evaluating the predictive accuracy and the clinical benefit of a nomogram aimed to predict survival in node-positive prostate cancer patients: External validation on a multi-institutional database.

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Bianchi, Lorenzo; Schiavina, Riccardo; Borghesi, Marco; Bianchi, Federico Mineo; Briganti, Alberto; Carini, Marco; Terrone, Carlo; Mottrie, Alex; Gacci, Mauro; Gontero, Paolo; Imbimbo, Ciro; Marchioro, Giansilvio; Milanese, Giulio; Mirone, Vincenzo; Montorsi, Francesco; Morgia, Giuseppe; Novara, Giacomo; Porreca, Angelo; Volpe, Alessandro; Brunocilla, Eugenio

2018-04-06

To assess the predictive accuracy and the clinical value of a recent nomogram predicting cancer-specific mortality-free survival after surgery in pN1 prostate cancer patients through an external validation. We evaluated 518 prostate cancer patients treated with radical prostatectomy and pelvic lymph node dissection with evidence of nodal metastases at final pathology, at 10 tertiary centers. External validation was carried out using regression coefficients of the previously published nomogram. The performance characteristics of the model were assessed by quantifying predictive accuracy, according to the area under the curve in the receiver operating characteristic curve and model calibration. Furthermore, we systematically analyzed the specificity, sensitivity, positive predictive value and negative predictive value for each nomogram-derived probability cut-off. Finally, we implemented decision curve analysis, in order to quantify the nomogram's clinical value in routine practice. External validation showed inferior predictive accuracy as referred to in the internal validation (65.8% vs 83.3%, respectively). The discrimination (area under the curve) of the multivariable model was 66.7% (95% CI 60.1-73.0%) by testing with receiver operating characteristic curve analysis. The calibration plot showed an overestimation throughout the range of predicted cancer-specific mortality-free survival rates probabilities. However, in decision curve analysis, the nomogram's use showed a net benefit when compared with the scenarios of treating all patients or none. In an external setting, the nomogram showed inferior predictive accuracy and suboptimal calibration characteristics as compared to that reported in the original population. However, decision curve analysis showed a clinical net benefit, suggesting a clinical implication to correctly manage pN1 prostate cancer patients after surgery. © 2018 The Japanese Urological Association.

Tumor RNA disruption predicts survival benefit from breast cancer chemotherapy.

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Parissenti, Amadeo M; Guo, Baoqing; Pritzker, Laura B; Pritzker, Kenneth P H; Wang, Xiaohui; Zhu, Mu; Shepherd, Lois E; Trudeau, Maureen E

2015-08-01

In a prior substudy of the CAN-NCIC-MA.22 clinical trial (ClinicalTrials.gov identifier NCT00066443), we observed that neoadjuvant chemotherapy reduced tumor RNA integrity in breast cancer patients, a phenomenon we term "RNA disruption." The purpose of the current study was to assess in the full patient cohort the relationship between mid-treatment tumor RNA disruption and both pCR post-treatment and, subsequently, disease-free survival (DFS) up to 108 months post-treatment. To meet these objectives, we developed the RNA disruption assay (RDA) to quantify RNA disruption and stratify it into 3 response zones of clinical importance. Zone 1 is a level of RNA disruption inadequate for pathologic complete response (pCR); Zone 2 is an intermediate level, while Zone 3 has high RNA disruption. The same RNA disruption cut points developed for pCR response were then utilized for DFS. Tumor RDA identified >fourfold more chemotherapy non-responders than did clinical response by calipers. pCR responders were clustered in RDA Zone 3, irrespective of tumor subtype. DFS was about 2-fold greater for patients with tumors in Zone 3 compared to Zone 1 patients. Kaplan-Meier survival curves corroborated these findings that high tumor RNA disruption was associated with increased DFS. DFS values for patients in zone 3 that did not achieve a pCR were similar to that of pCR recipients across tumor subtypes, including patients with hormone receptor positive tumors that seldom achieve a pCR. RDA appears superior to pCR as a chemotherapy response biomarker, supporting the prospect of its use in response-guided chemotherapy.

Evaluation of miR-182/miR-100 Ratio for Diagnosis and Survival Prediction in Bladder Cancer.

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Chen, Zhanguo; Wu, Lili; Lin, Qi; Shi, Jing; Lin, Xiangyang; Shi, Liang

2016-09-01

Abnormal expression of microRNAs (miRNAs) plays an important role in development of several cancer types, including bladder cancer (BCa). However, the relationship between the ratio of miR-181/miR-100 and the prognosis of BCa has not been studied yet. The aim of this study was to evaluate the expression of miR-182, miR-100 and their clinical significance in BCa. Upregulation of miR-182 and down-regulation of miR-100 were validated in tissue specimens of 134 BCa cases compared with 148 normal bladder epithelia (NBE) specimens  using TaqMan-based real-time reverse transcription quantitative PCR (RT-qPCR). The diagnostic and prognostic evaluation of miR-182, miR-100, and miR-182/miR-100 ratio was also performed. miR-182 was upregulated in BCa and miR-100 was down-regulated in BCa compared with NBE (P ratio increased the diagnostic performance, yielding an AUC of 0.981 (97.01% sensitivity and 90.54% specificity). Moreover, miR-182/miR-100 ratio was associated with pT-stage, histological grade, BCa recurrence and carcinoma in situ (P analysis indicated that miR-182/miR-100 ratio was an independent prognostic factor for overall survival (Hazard ratio: 7.142; 95% CI: 2.106 - 9.891; P analysis revealed that high-level of miR-182/miR-100 ratio was significantly correlated with shortened survival time for BCa patients (P ratio may serve as a novel promising biomarker for diagnosis and survival prediction in BCa. Further studies are needed to elucidate the role of miR-182/miR-100 ratio as a non‑invasive diagnostic tool for BCa.

The prediction of progression-free and overall survival in women with an advanced stage of epithelial ovarian carcinoma.

Science.gov (United States)

Gerestein, C G; Eijkemans, M J C; de Jong, D; van der Burg, M E L; Dykgraaf, R H M; Kooi, G S; Baalbergen, A; Burger, C W; Ansink, A C

2009-02-01

Prognosis in women with ovarian cancer mainly depends on International Federation of Gynecology and Obstetrics stage and the ability to perform optimal cytoreductive surgery. Since ovarian cancer has a heterogeneous presentation and clinical course, predicting progression-free survival (PFS) and overall survival (OS) in the individual patient is difficult. The objective of this study was to determine predictors of PFS and OS in women with advanced stage epithelial ovarian cancer (EOC) after primary cytoreductive surgery and first-line platinum-based chemotherapy. Retrospective observational study. Two teaching hospitals and one university hospital in the south-western part of the Netherlands. Women with advanced stage EOC. All women who underwent primary cytoreductive surgery for advanced stage EOC followed by first-line platinum-based chemotherapy between January 1998 and October 2004 were identified. To investigate independent predictors of PFS and OS, a Cox' proportional hazard model was used. Nomograms were generated with the identified predictive parameters. The primary outcome measure was OS and the secondary outcome measures were response and PFS. A total of 118 women entered the study protocol. Median PFS and OS were 15 and 44 months, respectively. Preoperative platelet count (P = 0.007), and residual disease statistic of 0.63. Predictive parameters for OS were preoperative haemoglobin serum concentration (P = 0.012), preoperative platelet counts (P = 0.031) and residual disease statistic of 0.67. PFS could be predicted by postoperative residual disease and preoperative platelet counts, whereas residual disease, preoperative platelet counts and preoperative haemoglobin serum concentration were predictive for OS. The proposed nomograms need to be externally validated.

Influence of membrane fatty acid composition and fluidity on airborne survival of Escherichia coli.

Science.gov (United States)

Ng, Tsz Wai; Chan, Wing Lam; Lai, Ka Man

2018-04-01

Finding ways to predict and control the survival of bacterial aerosols can contribute to the development of ways to alleviate a number of crucial microbiological problems. Significant damage in the membrane integrity of Escherichia coli during aerosolization and airborne suspension has been revealed which has prompted the question of how the membrane fatty acid composition and fluidity influence the survival of airborne bacteria. Two approaches of using isogenic mutants and different growth temperatures were selected to manipulate the membrane fatty acid composition of E. coli before challenging the bacteria with different relative humidity (RH) levels in an aerosol chamber. Among the mutants (fabR - , cfa. fadA - ), fabR - had the lowest membrane fluidity index (FI) and generally showed a higher survival than the parental strain. Surprisingly, its resistance to airborne stress was so strong that its viability was fully maintained even after airborne suspension at 40% RH, a harsh RH level to bacterial survival. Moreover, E. coli cultured at 20 °C with a higher FI than that at 30 and 37 °C generally had a lower survival after aerosolization and airborne suspension. Unlike FI, individual fatty acid and cyclopropane fatty acid composition did not relate to the bacterial survival. Lipid peroxidation of the membrane was undetected in all the bacteria. Membrane fluidity plays a stronger role in determining the bacteria survival during airborne suspension than during aerosolization. Certain relationships between FI and bacteria survival were identified, which could help predict the transmission of bacteria under different conditions.

Emmprin and survivin predict response and survival following cisplatin-containing chemotherapy in patients with advanced bladder cancer

DEFF Research Database (Denmark)

Als, Anne B; Dyrskjøt, Lars; von der Maase, Hans

2007-01-01

in an independent material of 124 patients receiving cisplatin-containing therapy. RESULTS: Fifty-five differentially expressed genes correlated significantly to survival time. Two of the protein products (emmprin and survivin) were validated using immunohistochemistry. Multivariate analysis identified emmprin...... metastases, both markers showed significant discriminating power as supplemental risk factors (P emmprin and survivin) had estimated 5-year survival rates of 44.......0%, 21.1%, and 0%, respectively. Response to chemotherapy could also be predicted with an odds ratio of 4.41 (95% confidence interval, 1.91-10.1) and 2.48 (95% confidence interval, 1.1-5.5) for emmprin and survivin, respectively. CONCLUSIONS: Emmprin and survivin proteins were identified as strong...

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

Late Release of Circulating Endothelial Cells and Endothelial Progenitor Cells after Chemotherapy Predicts Response and Survival in Cancer Patients

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Jeanine M. Roodhart

2010-01-01

Full Text Available We and others have previously demonstrated that the acute release of progenitor cells in response to chemotherapy actually reduces the efficacy of the chemotherapy. Here, we take these data further and investigate the clinical relevance of circulating endothelial (progenitor cells (CE(PCs and modulatory cytokines in patients after chemotherapy with relation to progression-free and overall survival (PFS/OS. Patients treated with various chemotherapeutics were included. Blood sampling was performed at baseline, 4 hours, and 7 and 21 days after chemotherapy. The mononuclear cell fraction was analyzed for CE(PC by FACS analysis. Plasma was analyzed for cytokines by ELISA or Luminex technique. CE(PCs were correlated with response and PFS/OS using Cox proportional hazard regression analysis. We measured CE(PCs and cytokines in 71 patients. Only patients treated with paclitaxel showed an immediate increase in endothelial progenitor cell 4 hours after start of treatment. These immediate changes did not correlate with response or survival. After 7 and 21 days of chemotherapy, a large and consistent increase in CE(PC was found (P < .01, independent of the type of chemotherapy. Changes in CE(PC levels at day 7 correlated with an increase in tumor volume after three cycles of chemotherapy and predicted PFS/OS, regardless of the tumor type or chemotherapy. These findings indicate that the late release of CE(PC is a common phenomenon after chemotherapeutic treatment. The correlation with a clinical response and survival provides further support for the biologic relevance of these cells in patients' prognosis and stresses their possible use as a therapeutic target.

Will male advertisement be a reliable indicator of paternal care, if offspring survival depends on male care?

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Kelly, Natasha B; Alonzo, Suzanne H

2009-09-07

Existing theory predicts that male signalling can be an unreliable indicator of paternal care, but assumes that males with high levels of mating success can have high current reproductive success, without providing any parental care. As a result, this theory does not hold for the many species where offspring survival depends on male parental care. We modelled male allocation of resources between advertisement and care for species with male care where males vary in quality, and the effect of care and advertisement on male fitness is multiplicative rather than additive. Our model predicts that males will allocate proportionally more of their resources to whichever trait (advertisement or paternal care) is more fitness limiting. In contrast to previous theory, we find that male advertisement is always a reliable indicator of paternal care and male phenotypic quality (e.g. males with higher levels of advertisement never allocate less to care than males with lower levels of advertisement). Our model shows that the predicted pattern of male allocation and the reliability of male signalling depend very strongly on whether paternal care is assumed to be necessary for offspring survival and how male care affects offspring survival and male fitness.

Fear affects parental care, which predicts juvenile survival and exacerbates the total cost of fear on demography.

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Dudeck, Blair P; Clinchy, Michael; Allen, Marek C; Zanette, Liana Y

2018-01-01

Fear itself (perceived predation risk) can affect wildlife demography, but the cumulative impact of fear on population dynamics is not well understood. Parental care is arguably what most distinguishes birds and mammals from other taxa, yet only one experiment on wildlife has tested fear effects on parental food provisioning and the repercussions this has for the survival of dependent offspring, and only during early-stage care. We tested the effect of fear on late-stage parental care of mobile dependent offspring, by locating radio-tagged Song Sparrow fledglings and broadcasting predator or non-predator playbacks in their vicinity, measuring their parent's behavior and their own, and tracking the offspring's survival to independence. Fear significantly reduced late-stage parental care, and parental fearfulness (as indexed by their reduction in provisioning when hearing predators) significantly predicted their offspring's condition and survival. Combining results from this experiment with that on early-stage care, we project that fear itself is powerful enough to reduce late-stage survival by 24%, and cumulatively reduce the number of young reaching independence by more than half, 53%. Experiments in invertebrate and aquatic systems demonstrate that fear is commonly as important as direct killing in affecting prey demography, and we suggest focusing more on fear effects and on offspring survival will reveal the same for wildlife. © 2017 by the Ecological Society of America.

Immune phenotypes predict survival in patients with glioblastoma multiforme

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Haouraa Mostafa

2016-09-01

Full Text Available Abstract Background Glioblastoma multiforme (GBM, a common primary malignant brain tumor, rarely disseminates beyond the central nervous system and has a very bad prognosis. The current study aimed at the analysis of immunological control in individual patients with GBM. Methods Immune phenotypes and plasma biomarkers of GBM patients were determined at the time of diagnosis using flow cytometry and ELISA, respectively. Results Using descriptive statistics, we found that immune anomalies were distinct in individual patients. Defined marker profiles proved highly relevant for survival. A remarkable relation between activated NK cells and improved survival in GBM patients was in contrast to increased CD39 and IL-10 in patients with a detrimental course and very short survival. Recursive partitioning analysis (RPA and Cox proportional hazards models substantiated the relevance of absolute numbers of CD8 cells and low numbers of CD39 cells for better survival. Conclusions Defined alterations of the immune system may guide the course of disease in patients with GBM and may be prognostically valuable for longitudinal studies or can be applied for immune intervention.

Winter Survival of Individual Honey Bees and Honey Bee Colonies Depends on Level of Varroa destructor Infestation

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van Dooremalen, Coby; Gerritsen, Lonne; Cornelissen, Bram; van der Steen, Jozef J. M.; van Langevelde, Frank; Blacquière, Tjeerd

2012-01-01

Background Recent elevated winter loss of honey bee colonies is a major concern. The presence of the mite Varroa destructor in colonies places an important pressure on bee health. V. destructor shortens the lifespan of individual bees, while long lifespan during winter is a primary requirement to survive until the next spring. We investigated in two subsequent years the effects of different levels of V. destructor infestation during the transition from short-lived summer bees to long-lived winter bees on the lifespan of individual bees and the survival of bee colonies during winter. Colonies treated earlier in the season to reduce V. destructor infestation during the development of winter bees were expected to have longer bee lifespan and higher colony survival after winter. Methodology/Principal Findings Mite infestation was reduced using acaricide treatments during different months (July, August, September, or not treated). We found that the number of capped brood cells decreased drastically between August and November, while at the same time, the lifespan of the bees (marked cohorts) increased indicating the transition to winter bees. Low V. destructor infestation levels before and during the transition to winter bees resulted in an increase in lifespan of bees and higher colony survival compared to colonies that were not treated and that had higher infestation levels. A variety of stress-related factors could have contributed to the variation in longevity and winter survival that we found between years. Conclusions/Significance This study contributes to theory about the multiple causes for the recent elevated colony losses in honey bees. Our study shows the correlation between long lifespan of winter bees and colony loss in spring. Moreover, we show that colonies treated earlier in the season had reduced V. destructor infestation during the development of winter bees resulting in longer bee lifespan and higher colony survival after winter. PMID:22558421

Methodology to predict long-term cancer survival from short-term data using Tobacco Cancer Risk and Absolute Cancer Cure models

International Nuclear Information System (INIS)

Mould, R F; Lederman, M; Tai, P; Wong, J K M

2002-01-01

Three parametric statistical models have been fully validated for cancer of the larynx for the prediction of long-term 15, 20 and 25 year cancer-specific survival fractions when short-term follow-up data was available for just 1-2 years after the end of treatment of the last patient. In all groups of cases the treatment period was only 5 years. Three disease stage groups were studied, T1N0, T2N0 and T3N0. The models are the Standard Lognormal (SLN) first proposed by Boag (1949 J. R. Stat. Soc. Series B 11 15-53) but only ever fully validated for cancer of the cervix, Mould and Boag (1975 Br. J. Cancer 32 529-50), and two new models which have been termed Tobacco Cancer Risk (TCR) and Absolute Cancer Cure (ACC). In each, the frequency distribution of survival times of defined groups of cancer deaths is lognormally distributed: larynx only (SLN), larynx and lung (TCR) and all cancers (ACC). All models each have three unknown parameters but it was possible to estimate a value for the lognormal parameter S a priori. By reduction to two unknown parameters the model stability has been improved. The material used to validate the methodology consisted of case histories of 965 patients, all treated during the period 1944-1968 by Dr Manuel Lederman of the Royal Marsden Hospital, London, with follow-up to 1988. This provided a follow-up range of 20- 44 years and enabled predicted long-term survival fractions to be compared with the actual survival fractions, calculated by the Kaplan and Meier (1958 J. Am. Stat. Assoc. 53 457-82) method. The TCR and ACC models are better than the SLN model and for a maximum short-term follow-up of 6 years, the 20 and 25 year survival fractions could be predicted. Therefore the numbers of follow-up years saved are respectively 14 years and 19 years. Clinical trial results using the TCR and ACC models can thus be analysed much earlier than currently possible. Absolute cure from cancer was also studied, using not only the prediction models which

A combination of preoperative CT findings and postoperative serum CEA levels improves recurrence prediction for stage I lung adenocarcinoma

Energy Technology Data Exchange (ETDEWEB)

Yamazaki, Motohiko, E-mail: xackey2001@gmail.com [Department of Radiology, Niigata University Graduate School of Medical and Dental Sciences (Japan); Ishikawa, Hiroyuki [Department of Radiology, Niigata University Graduate School of Medical and Dental Sciences (Japan); Kunii, Ryosuke [Division of Cellular and Molecular Pathology, Niigata University Graduate School of Medical and Dental Sciences (Japan); Tasaki, Akiko; Sato, Suguru; Ikeda, Yohei; Yoshimura, Norihiko [Department of Radiology, Niigata University Graduate School of Medical and Dental Sciences (Japan); Hashimoto, Takehisa; Tsuchida, Masanori [Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences (Japan); Aoyama, Hidefumi [Department of Radiology, Niigata University Graduate School of Medical and Dental Sciences (Japan)

2015-01-15

Objectives: To assess the prognostic value of combined evaluation of preoperative CT findings and pre/postoperative serum carcinoembryonic antigen (CEA) levels for pathological stage I lung adenocarcinoma. Methods: This retrospective study included 250 consecutive patients who underwent complete resection for ≤3-cm pathological stage I (T1–2aN0M0) adenocarcinomas (132 men, 118 women; mean age, 67.8 years). Radiologists evaluated following CT findings: maximum tumor diameter, percentage of solid component (%solid), air bronchogram, spiculation, adjacency of bullae or interstitial pneumonia (IP) around the tumor, notch, and pleural indent. These CT findings, pre/postoperative CEA levels, age, gender, and Brinkman index were assessed by Cox proportional hazards model to determine the best prognostic model. Prognostic accuracy was examined using the area under the receiver operating characteristic curve (AUC). Results: Median follow-up period was 73.2 months. In multivariate analysis, high %solid, adjacency of bullae or IP around the tumor, and high postoperative CEA levels comprised the best combination for predicting recurrence (P < 0.05). A combination of these three findings had a greater accuracy in predicting 5-year disease-free survival than did %solid alone (AUC = 0.853 versus 0.792; P = 0.023), with a sensitivity of 85.7% and a specificity of 74.3% at the optimal threshold. The best cut-off values of %solid and postoperative CEA levels for predicting high-risk patients were ≥48% and ≥3.7 ng/mL, respectively. Conclusion: Compared to %solid alone, combined evaluation of %solid, adjacency of bullae or IP change around the tumor, and postoperative CEA levels improves recurrence prediction for stage I lung adenocarcinoma.

Survival and development of Heliothis virescens (Lepidoptera: Noctuidae) larvae on isogenic tobacco lines with different levels of alkaloids.

Science.gov (United States)

Jackson, D Michael; Johnson, A W; Stephenson, M G

2002-12-01

Levels of pyridine alkaloids were measured in 18 tobacco, Nicotiana tabacum L., entries from three parental isolines ('NC 95', 'SC 58', and 'Coker 139'), grown at Tifton, GA, Florence, SC, and Oxford, NC, in 1991. Levels of alkaloids in bud leaves (first fully unfolded leaf below the apical leaf bud) were negatively correlated to natural infestation ratings of tobacco budworm larvae, Heliothis virescens (F.), 7 wk after transplanting. For artificially infested bud leaves at Oxford, there was a significant negative correlation between levels of total alkaloids and larval weights after 1 wk of feeding. In 1992, four entries from the 'NC 95' isoline were grown at Oxford, and samples for alkaloid analyses were taken every 2 wk at several leaf positions on each plant. During weeks 4, 8, 12, and 16, second instar tobacco budworms were caged on individual, intact leaves inside perforated plastic bags in the field. The survival and development of tobacco budworm larvae after 1 wk were negatively correlated with levels of alkaloids at the various leaf positions. Larvae survived better and grew faster on the bud leaves of each entry where alkaloid levels were lower than they did on leaves further down the stalk where alkaloid levels were higher. More larvae survived on the lower leaves of the low alkaloid lines than on the lower leaves of the high alkaloid lines. Even moderate increases in pyridine alkaloids had negative effects on tobacco budworm survival and development. Nicotine constituted >97% of the pyridine alkaloids in the 'NC95' isoline each year.

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.

Integrative analysis of survival-associated gene sets in breast cancer.

Science.gov (United States)

Varn, Frederick S; Ung, Matthew H; Lou, Shao Ke; Cheng, Chao

2015-03-12

Patient gene expression information has recently become a clinical feature used to evaluate breast cancer prognosis. The emergence of prognostic gene sets that take advantage of these data has led to a rich library of information that can be used to characterize the molecular nature of a patient's cancer. Identifying robust gene sets that are consistently predictive of a patient's clinical outcome has become one of the main challenges in the field. We inputted our previously established BASE algorithm with patient gene expression data and gene sets from MSigDB to develop the gene set activity score (GSAS), a metric that quantitatively assesses a gene set's activity level in a given patient. We utilized this metric, along with patient time-to-event data, to perform survival analyses to identify the gene sets that were significantly correlated with patient survival. We then performed cross-dataset analyses to identify robust prognostic gene sets and to classify patients by metastasis status. Additionally, we created a gene set network based on component gene overlap to explore the relationship between gene sets derived from MSigDB. We developed a novel gene set based on this network's topology and applied the GSAS metric to characterize its role in patient survival. Using the GSAS metric, we identified 120 gene sets that were significantly associated with patient survival in all datasets tested. The gene overlap network analysis yielded a novel gene set enriched in genes shared by the robustly predictive gene sets. This gene set was highly correlated to patient survival when used alone. Most interestingly, removal of the genes in this gene set from the gene pool on MSigDB resulted in a large reduction in the number of predictive gene sets, suggesting a prominent role for these genes in breast cancer progression. The GSAS metric provided a useful medium by which we systematically investigated how gene sets from MSigDB relate to breast cancer patient survival. We used

Impact of Molecular Subtypes in Muscle-invasive Bladder Cancer on Predicting Response and Survival after Neoadjuvant Chemotherapy.

Science.gov (United States)

Seiler, Roland; Ashab, Hussam Al Deen; Erho, Nicholas; van Rhijn, Bas W G; Winters, Brian; Douglas, James; Van Kessel, Kim E; Fransen van de Putte, Elisabeth E; Sommerlad, Matthew; Wang, Natalie Q; Choeurng, Voleak; Gibb, Ewan A; Palmer-Aronsten, Beatrix; Lam, Lucia L; Buerki, Christine; Davicioni, Elai; Sjödahl, Gottfrid; Kardos, Jordan; Hoadley, Katherine A; Lerner, Seth P; McConkey, David J; Choi, Woonyoung; Kim, William Y; Kiss, Bernhard; Thalmann, George N; Todenhöfer, Tilman; Crabb, Simon J; North, Scott; Zwarthoff, Ellen C; Boormans, Joost L; Wright, Jonathan; Dall'Era, Marc; van der Heijden, Michiel S; Black, Peter C

2017-10-01

An early report on the molecular subtyping of muscle-invasive bladder cancer (MIBC) by gene expression suggested that response to neoadjuvant chemotherapy (NAC) varies by subtype. To investigate the ability of molecular subtypes to predict pathological downstaging and survival after NAC. Whole transcriptome profiling was performed on pre-NAC transurethral resection specimens from 343 patients with MIBC. Samples were classified according to four published molecular subtyping methods. We developed a single-sample genomic subtyping classifier (GSC) to predict consensus subtypes (claudin-low, basal, luminal-infiltrated and luminal) with highest clinical impact in the context of NAC. Overall survival (OS) according to subtype was analyzed and compared with OS in 476 non-NAC cases (published datasets). Gene expression analysis was used to assign subtypes. Receiver-operating characteristics were used to determine the accuracy of GSC. The effect of GSC on survival was estimated by Cox proportional hazard regression models. The models generated subtype calls in expected ratios with high concordance across subtyping methods. GSC was able to predict four consensus molecular subtypes with high accuracy (73%), and clinical significance of the predicted consensus subtypes could be validated in independent NAC and non-NAC datasets. Luminal tumors had the best OS with and without NAC. Claudin-low tumors were associated with poor OS irrespective of treatment regimen. Basal tumors showed the most improvement in OS with NAC compared with surgery alone. The main limitations of our study are its retrospective design and comparison across datasets. Molecular subtyping may have an impact on patient benefit to NAC. If validated in additional studies, our results suggest that patients with basal tumors should be prioritized for NAC. We discovered the first single-sample classifier to subtype MIBC, which may be suitable for integration into routine clinical practice. Different molecular

Exploring gene expression signatures for predicting disease free survival after resection of colorectal cancer liver metastases.

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Nikol Snoeren

Full Text Available BACKGROUND AND OBJECTIVES: This study was designed to identify and validate gene signatures that can predict disease free survival (DFS in patients undergoing a radical resection for their colorectal liver metastases (CRLM. METHODS: Tumor gene expression profiles were collected from 119 patients undergoing surgery for their CRLM in the Paul Brousse Hospital (France and the University Medical Center Utrecht (The Netherlands. Patients were divided into high and low risk groups. A randomly selected training set was used to find predictive gene signatures. The ability of these gene signatures to predict DFS was tested in an independent validation set comprising the remaining patients. Furthermore, 5 known clinical risk scores were tested in our complete patient cohort. RESULT: No gene signature was found that significantly predicted DFS in the validation set. In contrast, three out of five clinical risk scores were able to predict DFS in our patient cohort. CONCLUSIONS: No gene signature was found that could predict DFS in patients undergoing CRLM resection. Three out of five clinical risk scores were able to predict DFS in our patient cohort. These results emphasize the need for validating risk scores in independent patient groups and suggest improved designs for future studies.

Early α-fetoprotein response predicts survival in patients with advanced hepatocellular carcinoma treated with sorafenib

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Lee SH

2015-04-01

Full Text Available Sangheun Lee,1,* Beom Kyung Kim,2–5,* Seung Up Kim,2–5 Jun Yong Park,2–5 Do Young Kim,2–5 Sang Hoon Ahn,2–6 Kwang-Hyub Han2–6 1Department of Internal Medicine, International St Mary’s Hospital, Catholic Kwandong University, Incheon Metropolitan City, Republic of Korea; 2Department of Internal Medicine, 3Institute of Gastroenterology, 4Liver Cancer Special Clinic, Yonsei University College of Medicine, Seoul, Republic of Korea; 5Liver Cirrhosis Clinical Research Center, Seoul, Republic of Korea; 6Brain Korea 21 Project for Medical Science, Seoul, Republic of Korea.   *These authors contributed equally to this work Background: It is not clear whether tumor marker responses can predict survival during sorafenib treatment in hepatocellular carcinoma (HCC. We investigated whether the α-fetoprotein (AFP response is associated with survival in patients with advanced HCC treated with sorafenib. Methods: We retrospectively reviewed the records of 126 patients with advanced HCC treated with sorafenib between 2007 and 2012. An AFP response was defined as >20% decrease from baseline. At 6–8 weeks after commencing sorafenib, AFP and radiological responses were assessed by modified Response Evaluation Criteria in Solid Tumors. Results: The median overall survival (OS and progression-free survival (PFS were 6.2 and 3.5 months, respectively. Of the study population, a partial response (PR was identified in 5 patients (4.0%, stable disease (SD in 65 patients (51.6%, and progressive disease (PD in 57 patients (44.4%, respectively. AFP non-response was an independent prognostic factor for poor OS (median 10.9 months for AFP response vs 5.2 months for AFP non-response, together with Child-Pugh B, tumor diameter ≥10 cm, and portal vein invasion (all P<0.05, and PFS (median 5.3 months for AFP response vs 2.9 months for AFP non-response, together with tumor diameter ≥10 cm and portal vein invasion (all P<0.05. SD or PR was more frequently found

ATM and p53 combined analysis predicts survival in glioblastoma multiforme patients: A clinicopathologic study.

Science.gov (United States)

Romano, Francesco Jacopo; Guadagno, Elia; Solari, Domenico; Borrelli, Giorgio; Pignatiello, Sara; Cappabianca, Paolo; Del Basso De Caro, Marialaura

2018-06-01

Glioblastoma is one of the most malignant cancers, with a distinguishing dismal prognosis: surgery followed by chemo- and radiotherapy represents the current standard of care, and chemo- and radioresistance underlie disease recurrence and short overall survival of patients suffering from this malignancy. ATM is a kinase activated by autophosphorylation upon DNA doublestrand breaks arising from errors during replication, byproducts of metabolism, chemotherapy or ionizing radiations; TP53 is one of the most popular tumor suppressor, with a preeminent role in DNA damage response and repair. To study the effects of the immunohistochemical expression of p-ATM and p53 in glioblastoma patients, 21 cases were retrospectively examined. In normal brain tissue, p-ATM was expressed only in neurons; conversely, in tumors cells, the protein showed a variable cytoplasmic expression (score: +,++,+++), with being completely undetectable in three cases. Statistical analysis revealed that high p-ATM score (++/+++) strongly correlated to shorter survival (P = 0.022). No difference in overall survival was registered between p53 normally expressed (NE) and overexpressed (OE) glioblastoma patients (P = 0.669). Survival analysis performed on the results from combined assessment of the two proteins showed that patients with NE p53 /low pATM score had longer overall survival than the NE p53/ high pATM score counterpart. Cox-regression analysis confirmed this finding (HR = 0.025; CI 95% = 0.002-0.284; P = 0.003). Our study outlined the immunohistochemical expression of p-ATM/p53 in glioblastomas and provided data on their possible prognostic/predictive of response role. A "non-oncogene addiction" to ATM for NEp53 glioblastoma could be postulated, strengthening the rationale for development of ATM inhibiting drugs. © 2018 Wiley Periodicals, Inc.

Data mining in bone marrow transplant records to identify patients with high odds of survival.

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Taati, Babak; Snoek, Jasper; Aleman, Dionne; Ghavamzadeh, Ardeshir

2014-01-01

Patients undergoing a bone marrow stem cell transplant (BMT) face various risk factors. Analyzing data from past transplants could enhance the understanding of the factors influencing success. Records up to 120 measurements per transplant procedure from 1751 patients undergoing BMT were collected (Shariati Hospital). Collaborative filtering techniques allowed the processing of highly sparse records with 22.3% missing values. Ten-fold cross-validation was used to evaluate the performance of various classification algorithms trained on predicting the survival status. Modest accuracy levels were obtained in predicting the survival status (AUC = 0.69). More importantly, however, operations that had the highest chances of success were shown to be identifiable with high accuracy, e.g., 92% or 97% when identifying 74 or 31 recipients, respectively. Identifying the patients with the highest chances of survival has direct application in the prioritization of resources and in donor matching. For patients where high-confidence prediction is not achieved, assigning a probability to their survival odds has potential applications in probabilistic decision support systems and in combination with other sources of information.

Social Relationships, Inflammation, and Cancer Survival.

Science.gov (United States)

Boen, Courtney E; Barrow, David A; Bensen, Jeannette T; Farnan, Laura; Gerstel, Adrian; Hendrix, Laura H; Yang, Yang Claire

2018-05-01

Background: Social stressors, such as social relationship deficits, have been increasingly linked to chronic disease outcomes, including cancer. However, critical gaps exist in our understanding of the nature and strength of such links, as well as the underlying biological mechanisms relating social relationships to cancer progression and survival. Methods: Utilizing novel questionnaire and biomarker data from the UNC Health Registry/Cancer Survivorship Cohort, this study examines the associations between diverse measures of social support and mortality risk among individuals with cancer ( N = 1,004). We further assess the role of multiple serum markers of inflammation, including high-sensitivity C-reactive protein (CRP), IL6, TNFα, and VEGF, as potential mediators in the social relationship-cancer link. Results: The findings revealed that one's appraisal of their social support was associated with cancer mortality, such that individuals reporting higher levels of social support satisfaction had lower mortality risk than individuals reporting lower levels of satisfaction. The amount of support received, on the other hand, was not predictive of cancer survival. We further found evidence that inflammatory processes may undergird the link between social support satisfaction and mortality among individuals with cancer, with individuals reporting higher levels of social support satisfaction having lower levels of CRP, IL6, and TNFα. Conclusions: These results provide new knowledge of the biosocial processes producing population disparities in cancer outcomes. Impact: Our study offers new insights for intervention efforts aimed at promoting social connectedness as a means for improving cancer survival. Cancer Epidemiol Biomarkers Prev; 27(5); 541-9. ©2018 AACR . ©2018 American Association for Cancer Research.

Joint Serum Tumor Markers Serve as survival predictive model of Erlotinib in the treatment of recurrent Non-small Cell Lung Cancer

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Lan SHAO

2014-05-01

Full Text Available Background and objective Molecular targeting therapy is the direction of individualized treatment of lung cancer, scholars has been established targeted therapy prediction models which provide more guidance for clinical individual therapy. This study investigated the relationship among pulmonary surfactant-associated protein D (SP-D, transforming growth factor α (TGF-α, matrix metalloproteinase 9 (MMP-9, tissue polypeptide specific antigen (TPS, and Krebs von den Lungen-6 (KL-6 and response as well as survival in the patients with recurrent non-small cell lung cancer, which Erlotinib was as second line treatment after failure to chemotherapy. This study also established a predictive prognostic model. Methods Serum levels of SP-D, TGF-α, MMP-9, TPS, and KL-6 in 114 patients before erlotinib treatment were detected by ELISA method. Combined with clinical factors, these levels were used to investigate the relationship with efficacy in erlotinib treatment and construct a predicted prognostic model by Kaplan-Meier curve and Cox proportional hazard model multivariate analysis. Results The objective response rate (ORR and disease control rate (DCR in the 114 patients, were 22.8% (26/114 and 72.8% (83/114, to Erlotinib treatment respectively. The median progression-free survival (PFS and one year survival rate with Erlotinib treatment were 5.13 months and 69.3%, respectively. Patients in the SP-D>110 ng/mL group exhibited more ORR (33.3% vs 13.3%, P=0.011 and DCR (83.3% vs 63.3%, P=0.017 than those in the ≤110 ng/mL group. Patients in the MMP-9≤535 ng/mL group showed more DCR (83.9% than those in the >535 ng/mL group (62.1% (P=0.009. Patients in the TPS110 ng/mL (5.95 months vs 3.25 months, P=0.009, MMP-9≤535 ng/mL (5.83 months vs 3.47 months, P=0.046, KL-6<500 U/mL (6.03 months vs 3.40 months, P=0.040, and TPS<80 U/L (6.15 months vs 2.42 months, P=0.014 groups showed better PFS. Multivariate analysis showed that current or ever-smoker, wild

Nomogram Prediction of Survival and Recurrence in Patients With Extrahepatic Bile Duct Cancer Undergoing Curative Resection Followed by Adjuvant Chemoradiation Therapy

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Song, Changhoon [Department of Radiation Oncology, Seoul National University College of Medicine, Seoul (Korea, Republic of); Kim, Kyubo, E-mail: kyubokim@snu.ac.kr [Department of Radiation Oncology, Seoul National University College of Medicine, Seoul (Korea, Republic of); Chie, Eui Kyu [Department of Radiation Oncology, Seoul National University College of Medicine, Seoul (Korea, Republic of); Institute of Radiation Medicine, Medical Research Center, Seoul National University, Seoul (Korea, Republic of); Kim, Jin Ho [Department of Radiation Oncology, Seoul National University College of Medicine, Seoul (Korea, Republic of); Jang, Jin-Young; Kim, Sun Whe [Department of Surgery, Seoul National University College of Medicine, Seoul (Korea, Republic of); Han, Sae-Won; Oh, Do-Youn; Im, Seock-Ah; Kim, Tae-You; Bang, Yung-Jue [Department of Internal Medicine, Seoul National University College of Medicine, Seoul (Korea, Republic of); Ha, Sung W. [Department of Radiation Oncology, Seoul National University College of Medicine, Seoul (Korea, Republic of); Institute of Radiation Medicine, Medical Research Center, Seoul National University, Seoul (Korea, Republic of)

2013-11-01

Purpose: To develop nomograms for predicting the overall survival (OS) and relapse-free survival (RFS) in patients with extrahepatic bile duct cancer undergoing adjuvant chemoradiation therapy after curative resection. Methods and Materials: From January 1995 through August 2006, a total of 166 consecutive patients underwent curative resection followed by adjuvant chemoradiation therapy. Multivariate analysis using Cox proportional hazards regression was performed, and this Cox model was used as the basis for the nomograms of OS and RFS. We calculated concordance indices of the constructed nomograms and American Joint Committee on Cancer (AJCC) staging system. Results: The OS rate at 2 years and 5 years was 60.8% and 42.5%, respectively, and the RFS rate at 2 years and 5 years was 52.5% and 38.2%, respectively. The model containing age, sex, tumor location, histologic differentiation, perineural invasion, and lymph node involvement was selected for nomograms. The bootstrap-corrected concordance index of the nomogram for OS and RFS was 0.63 and 0.62, respectively, and that of AJCC staging for OS and RFS was 0.50 and 0.52, respectively. Conclusions: We developed nomograms that predicted survival and recurrence better than AJCC staging. With caution, clinicians may use these nomograms as an adjunct to or substitute for AJCC staging for predicting an individual's prognosis and offering tailored adjuvant therapy.

Tumour vasculature immaturity, oxidative damage and systemic inflammation stratify survival of colorectal cancer patients on bevacizumab treatment

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Martin, Petra; Biniecka, Monika; Ó'Meachair, Shane; Maguire, Aoife; Tosetto, Miriam; Nolan, Blathnaid; Hyland, John; Sheahan, Kieran; O'Donoghue, Diarmuid; Mulcahy, Hugh; Fennelly, David; O'Sullivan, Jacintha

2018-01-01

Despite treatment of patients with metastatic colorectal cancer (mCRC) with bevacizumab plus chemotherapy, response rates are modest and there are no biomarkers available that will predict response. The aim of this study was to assess if markers associated with three interconnected cancer-associated biological processes, specifically angiogenesis, inflammation and oxidative damage, could stratify the survival outcome of this cohort. Levels of angiogenesis, inflammation and oxidative damage markers were assessed in pre-bevacizumab resected tumour and serum samples of mCRC patients by dual immunofluorescence, immunohistochemistry and ELISA. This study identified that specific markers of angiogenesis, inflammation and oxidative damage stratify survival of patients on this anti-angiogenic treatment. Biomarkers of immature tumour vasculature (% IMM, p=0.026, n=80), high levels of oxidative damage in the tumour epithelium (intensity of 8-oxo-dG in nuclear and cytoplasmic compartments, p=0.042 and 0.038 respectively, n=75) and lower systemic pro-inflammatory cytokines (IL6 and IL8, p=0.053 and 0.049 respectively, n=61) significantly stratify with median overall survival (OS). In summary, screening for a panel of biomarkers for high levels of immature tumour vasculature, high levels of oxidative DNA damage and low levels of systemic pro-inflammatory cytokines may be beneficial in predicting enhanced survival outcome following bevacizumab treatment for mCRC. PMID:29535825

Low baseline levels of NK cells may predict a positive response to ipilimumab in melanoma therapy.

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Tietze, Julia K; Angelova, Daniela; Heppt, Markus V; Ruzicka, Thomas; Berking, Carola

2017-07-01

The introduction of immune checkpoint blockade (ICB) has been a breakthrough in the therapy of metastatic melanoma. The influence of ICB on T-cell populations has been studied extensively, but little is known about the effect on NK cells. In this study, we analysed the relative and absolute amounts of NK cells and of the subpopulations of CD56 dim and CD56 bright NK cells among the peripheral blood mononuclear cells (PBMCs) of 32 patients with metastatic melanoma before and under treatment with ipilimumab or pembrolizumab by flow cytometry. In 15 (47%) patients, an abnormal low amount of NK cells was found at baseline. Analysis of the subpopulations showed also low or normal baseline levels for CD56 dim NK cells, whereas the baseline levels of CD56 bright NK cells were either normal or abnormally high. The relative and absolute amounts of NK cells and of CD56 dim and CD56 bright NK cell subpopulations in patients with a normal baseline did not change under treatment. However, patients with a low baseline of NK cells and CD56 dim NK cells showed a significant increase in these immune cell subsets, but the amounts remained to be lower than the normal baseline. The amount of CD56 bright NK cells was unaffected by treatment. The baseline levels of NK cells were correlated with the number of metastatic organs. Their proportion increased, whereas the expression of NKG2D decreased significantly when more than one organ was affected by metastases. Low baseline levels of NK cells and CD56 dim NK cells as well as normal baseline levels of CD56 bright NK cells correlated significantly with a positive response to ipilimumab but not to pembrolizumab. Survival curves of patients with low amounts of CD56 dim NK cells treated with ipilimumab showed a trend to longer survival. Normal baseline levels of CD56 bright NK cells were significantly correlated with longer survival as compared to patients with high baseline levels. In conclusion, analysis of the amounts of total NK cells

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.

The Glasgow Prognostic Score at the Time of Palliative Esophageal Stent Insertion is a Predictive Factor of 30-Day Mortality and Overall Survival.

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Driver, Robert J; Handforth, Catherine; Radhakrishna, Ganesh; Bennett, Michael I; Ford, Alexander C; Everett, Simon M

2018-03-01

Optimizing the timing of esophageal stent insertion is a challenge, partly due to difficulty predicting survival in advanced malignancy. The Glasgow prognostic score (GPS) is a validated tool for predicting survival in a number of cancers. To assess the utility of the GPS in predicting 30-day mortality and overall survival postesophageal stent insertion. Patients at a tertiary referral center who had received an esophageal stent for palliation of dysphagia were included if they had a measurement of albumin and C-reactive protein (CRP) in the week preceding the procedure (n=209). Patients with both an elevated CRP (>10 mg/L) and hypoalbuminemia (L) were given a GPS score of 2 (GPS2). Patients with only one of these abnormalities were assigned as GPS1 and those with normal CRP and albumin were assigned as GPS0. Clinical and pathologic parameters were also collected to assess for potential confounding factors in the survival analysis. Increasing GPS was associated with 30-day mortality; for patients with GPS0, 30-day mortality was 5% (2/43), for GPS1 it was 23% (26/114), and for GPS2 it was 33% (17/52). The adjusted hazard ratio for overall poststent mortality was 1.6 (95% confidence interval, 1.1-2.4; P=0.02) for GPS1 and 2.4 (95% confidence interval, 1.5-3.8; PGPS2 patients compared with GPS0. GPS is an independent prognostic factor of 30-day mortality and overall survival after esophageal stent insertion. It is a potential adjunct to clinical assessment in identifying those patients at high-risk of short-term mortality poststent.

Predicting long-term risk for relationship dissolution using nonparametric conditional survival trees.

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Kliem, Sören; Weusthoff, Sarah; Hahlweg, Kurt; Baucom, Katherine J W; Baucom, Brian R

2015-12-01

Identifying risk factors for divorce or separation is an important step in the prevention of negative individual outcomes and societal costs associated with relationship dissolution. Programs that aim to prevent relationship distress and dissolution typically focus on changing processes that occur during couple conflict, although the predictive ability of conflict-specific variables has not been examined in the context of other factors related to relationship dissolution. The authors examine whether emotional responding and communication during couple conflict predict relationship dissolution after controlling for overall relationship quality and individual well-being. Using nonparametric conditional survival trees, the study at hand simultaneously examined the predictive abilities of physiological (systolic and diastolic blood pressure, heart rate, cortisol) and behavioral (fundamental frequency; f0) indices of emotional responding, as well as observationally coded positive and negative communication behavior, on long-term relationship stability after controlling for relationship satisfaction and symptoms of depression. One hundred thirty-six spouses were assessed after participating in a randomized clinical trial of a relationship distress prevention program as well as 11 years thereafter; 32.5% of the couples' relationships had dissolved by follow up. For men, the only significant predictor of relationship dissolution was cortisol change score (p = .012). For women, only f0 range was a significant predictor of relationship dissolution (p = .034). These findings highlight the importance of emotional responding during couple conflict for long-term relationship stability. (c) 2015 APA, all rights reserved).

Pathological stage after neoadjuvant chemoradiation and esophagectomy superiorly predicts survival in patients with esophageal squamous cell carcinoma

International Nuclear Information System (INIS)

Wang, Chia-Chun; Cheng, Jason Chia-Hsien; Tsai, Chiao-Ling; Lee, Jang-Ming; Huang, Pei-Ming; Lin, Chia-Chi; Hsu, Chih-Hung; Hsieh, Min-Shu; Chang, Yih-Leong; Hsu, Feng-Ming

2015-01-01

Background and purpose: To assess the usefulness of pathological stage according to the 7th edition of the Union for International Cancer Control–American Joint Committee on Cancer (UICC–AJCC) as a prognostic tool in patients undergoing neoadjuvant chemoradiation followed by esophagectomy (trimodality therapy, TMT) for locally advanced esophageal squamous cell carcinoma. Material and methods: One hundred twenty-five eligible patients completing TMT were enrolled for analysis. The clinical (cTNM7) and pathological (ypTNM7) stage groups of their tumors were prospectively classified, and re-grouped by the 6th edition (ypTNM6). Survival was analyzed using the Kaplan–Meier method. The Cox proportional hazard model and the Akaike information criterion (AIC) were used to compare the performance of staging systems. Results: With a median follow-up of 24.6 months, 54 patients (43.2%) died. Forty patients (32%) achieved pathological complete remission (pCR). The median survival was 31.8 months. On multivariate analysis, ypTNM7 (but not pCR or pN) was the only independent factor affecting overall survival (p < 0.001). The ypTNM7 was superior to cTNM7 or ypTNM6 in predicting both overall and recurrence-free survival after TMT based on AIC values and Cox proportional hazard model analysis. Conclusions: In patients with locally advanced esophageal squamous cell carcinoma undergoing TMT, ypTNM7 is the best predictor of survival

Probability of Survival Decision Aid (PSDA)

National Research Council Canada - National Science Library

Xu, Xiaojiang; Amin, Mitesh; Santee, William R

2008-01-01

A Probability of Survival Decision Aid (PSDA) is developed to predict survival time for hypothermia and dehydration during prolonged exposure at sea in both air and water for a wide range of environmental conditions...

A gene expression signature associated with survival in metastatic melanoma

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Mandruzzato, Susanna; Callegaro, Andrea; Turcatel, Gianluca; Francescato, Samuela; Montesco, Maria C; Chiarion-Sileni, Vanna; Mocellin, Simone; Rossi, Carlo R; Bicciato, Silvio; Wang, Ena; Marincola, Francesco M; Zanovello, Paola

2006-01-01

Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells. PMID:17129373

A gene expression signature associated with survival in metastatic melanoma

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Rossi Carlo R

2006-11-01

Full Text Available Abstract Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM to identify genes associated with patient survival, and supervised principal components (SPC to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells.

Numerical analysis for prediction of fatigue crack opening level

International Nuclear Information System (INIS)

Choi, Hyeon Chang

2004-01-01

Finite Element Analysis (FEA) is the most popular numerical method to simulate plasticity-induced fatigue crack closure and can predict fatigue crack closure behavior. Finite element analysis under plane stress state using 4-node isoparametric elements is performed to investigate the detailed closure behavior of fatigue cracks and the numerical results are compared with experimental results. The mesh of constant size elements on the crack surface can not correctly predict the opening level for fatigue crack as shown in the previous works. The crack opening behavior for the size mesh with a linear change shows almost flat stress level after a crack tip has passed by the monotonic plastic zone. The prediction of crack opening level presents a good agreement with published experimental data regardless of stress ratios, which are using the mesh of the elements that are in proportion to the reversed plastic zone size considering the opening stress intensity factors. Numerical interpolation results of finite element analysis can precisely predict the crack opening level. This method shows a good agreement with the experimental data regardless of the stress ratios and kinds of materials

Impact of geographic area level on measuring socioeconomic disparities in cancer survival in New South Wales, Australia: A period analysis.

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Stanbury, Julia F; Baade, Peter D; Yu, Yan; Yu, Xue Qin

2016-08-01

Area-based socioeconomic measures are widely used in health research. In theory, the larger the area used the more individual misclassification is introduced, thus biasing the association between such area level measures and health outcomes. In this study, we examined the socioeconomic disparities in cancer survival using two geographic area-based measures to see if the size of the area matters. We used population-based cancer registry data for patients diagnosed with one of 10 major cancers in New South Wales (NSW), Australia during 2004-2008. Patients were assigned index measures of socioeconomic status (SES) based on two area-level units, census Collection District (CD) and Local Government Area (LGA) of their address at diagnosis. Five-year relative survival was estimated using the period approach for patients alive during 2004-2008, for each socioeconomic quintile at each area-level for each cancer. Poisson-regression modelling was used to adjust for socioeconomic quintile, sex, age-group at diagnosis and disease stage at diagnosis. The relative excess risk of death (RER) by socioeconomic quintile derived from this modelling was compared between area-units. We found extensive disagreement in SES classification between CD and LGA levels across all socioeconomic quintiles, particularly for more disadvantaged groups. In general, more disadvantaged patients had significantly lower survival than the least disadvantaged group for both CD and LGA classifications. The socioeconomic survival disparities detected by CD classification were larger than those detected by LGA. Adjusted RER estimates by SES were similar for most cancers when measured at both area levels. We found that classifying patient SES by the widely used Australian geographic unit LGA results in underestimation of survival disparities for several cancers compared to when SES is classified at the geographically smaller CD level. Despite this, our RER of death estimates derived from these survival

Cancer survival classification using integrated data sets and intermediate information.

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Kim, Shinuk; Park, Taesung; Kon, Mark

2014-09-01

Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. FSCOX provides us with intermediate survival information, which is usually discarded when separating survival into 2 groups (short- and long-term), and allows us to perform survival analysis. We used an ML-based protocol for feature selection, integrating information from miRNA and mRNA expression profiles at the feature level. To predict survival phenotypes, we used the following classifiers, first, existing ML methods, support vector machine (SVM) and random forest (RF), second, a new median-based classifier using FSCOX (FSCOX_median), and third, an SVM classifier using FSCOX (FSCOX_SVM). We compared these methods using 3 types of cancer tissue data sets: (i) miRNA expression, (ii) mRNA expression, and (iii) combined miRNA and mRNA expression. The latter data set included features selected either from the combined miRNA/mRNA profile or independently from miRNAs and mRNAs profiles (IFS). In the ovarian data set, the accuracy of survival classification using the combined miRNA/mRNA profiles with IFS was 75% using RF, 86.36% using SVM, 84.09% using FSCOX_median, and 88.64% using FSCOX_SVM with a balanced 22 short-term and 22 long-term survivor data set. These accuracies are higher than those using miRNA alone (70.45%, RF; 75%, SVM; 75%, FSCOX_median; and 75%, FSCOX_SVM) or mRNA alone (65.91%, RF; 63.64%, SVM; 72.73%, FSCOX_median; and 70.45%, FSCOX_SVM). Similarly in the glioblastoma multiforme data, the accuracy of miRNA/mRNA using IFS

Factors Predictive of Tumor Recurrence and Survival After Initial Complete Response of Esophageal Squamous Cell Carcinoma to Definitive Chemoradiotherapy

International Nuclear Information System (INIS)

Ishihara, Ryu; Yamamoto, Sachiko; Iishi, Hiroyasu; Takeuchi, Yoji; Sugimoto, Naotoshi; Higashino, Koji; Uedo, Noriya; Tatsuta, Masaharu; Yano, Masahiko; Imai, Atsushi; Nishiyama, Kinji

2010-01-01

Purpose: To assess factors predictive of recurrent disease and survival after achieving initial complete response (CR) to chemoradiotherapy (CRT) for esophageal cancer. Methods and Materials: Patients who had clinical Stage I-IVA esophageal cancer and received definitive CRT between 2001 and 2007 were retrospectively analyzed. Results: Of 269 patients with esophageal cancer, 110 who achieved CR after definitive CRT were included in the analyses. Chemoradiotherapy mainly consisted of 2 cycles of cisplatin and fluorouracil with concurrent radiotherapy of 60 Gy in 30 fractions. We identified 28 recurrences and 28 deaths during follow-up. The cumulative 1- and 3-year recurrence rates were 18% and 32%, respectively. By univariate and multivariate analyses, tumor category (hazard ratio [HR] 6.6; 95% confidence interval [CI] 1.4-30.2; p = 0.015) was an independent risk factor for local recurrence, whereas age (HR 3.9; 95% CI 1.1-14.0; p = 0.034) and primary tumor location (HR 4.5; 95% CI 1.6-12.4; p = 0.004) were independent risk factors for regional lymph node or distant recurrences. The cumulative overall 1- and 3-year survival rates were 91% and 66%, respectively. As expected, recurrence was associated with poor survival (p = 0.019). By univariate and multivariate analyses, primary tumor location (HR 3.8; 95% CI 1.2-12.0; p = 0.024) and interval to recurrence (HR 4.3; 95% CI 1.3-14.4; p = 0.018) were independent factors predictive of survival after recurrence. Conclusion: Risk of recurrence after definitive CRT for esophageal cancer was associated with tumor category, age, and primary tumor location; this information may help in improved prognostication for these patients.

Predicting survival for well-differentiated liposarcoma: the importance of tumor location.

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Smith, Caitlin A; Martinez, Steve R; Tseng, Warren H; Tamurian, Robert M; Bold, Richard J; Borys, Dariusz; Canter, Robert J

2012-06-01

Although well-differentiated liposarcoma (WD Lipo) is a low grade neoplasm with a negligible risk of metastatic disease, it can be locally aggressive. We hypothesized that survival for WD Lipo varies significantly based on tumor location. We identified 1266 patients with WD Lipo in the Surveillance, Epidemiology, and End Results database from 1988-2004. After excluding patients diagnosed by autopsy only, those lacking histologic confirmation, those lacking data on tumor location, and those with metastatic disease or unknown staging information, we arrived at a final study cohort of 1130 patients. Clinical, pathologic, and treatment variables were analyzed for their association with overall survival (OS) and disease-specific survival (DSS) using Kaplan-Meier analysis and Cox proportional hazards multivariate models. Mean age was 61 y (± 14.6), 72.2% were white, and 60.4% were male. Eighty-one percent of patients were treated with surgical therapy alone, 4.6% were treated with radiotherapy (RT) alone, and 12.9% were treated with both surgery and RT. Extremity location was most common (41.6%), followed by trunk (29%), retroperitoneal/intra-abdominal (RIA, 21.6%), thorax (4.2%), and head/neck (3.6%). With a median follow-up of 45 mo, median OS was 115 mo (95% confidence interval [CI] 92-138 mo) for RIA tumors compared to not reached for other tumor locations (P = 0.002). On multivariate analysis, increasing age and RIA location both predicted worse OS and DSS while tumor size, race, sex, receipt of RT, and Surveillance, Epidemiology, and End Results (SEER) stage did not. Tumor size became a significant predictor of worse DSS, but not OS, only when site, SEER stage, and extent of resection were removed from the multivariate model. Non-RIA locations, including extremity, experienced statistically similar OS, but 5-y DSS for trunk location was intermediate [92.3%, (95% CI 88.5%-96.1%) compared with 98.0% (95% CI, 96.2%-99.8%) for extremity and 86.6 (95% CI 81

Location of subventricular zone recurrence and its radiation dose predicts survival in patients with glioblastoma.

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Weinberg, Brent D; Boreta, Lauren; Braunstein, Steve; Cha, Soonmee

2018-07-01

Glioblastomas are aggressive brain tumors that frequently recur in the subventricular zone (SVZ) despite maximal treatment. The purpose of this study was to evaluate imaging patterns of subventricular progression and impact of recurrent subventricular tumor involvement and radiation dose to patient outcome. Retrospective review of 50 patients diagnosed with glioblastoma and treated with surgery, radiation, and concurrent temozolomide from January 2012 to June 2013 was performed. Tumors were classified based on location, size, and cortical and subventricular zone involvement. Survival was compared based on recurrence type, distance from the initial enhancing tumor (local ≤ 2 cm, distant > 2 cm), and the radiation dose at the recurrence site. Progression of enhancing subventricular tumor was common at both local (58%) and distant (42%) sites. Median survival was better after local SVZ recurrence than distant SVZ recurrence (8.7 vs. 4.3 months, p = 0.04). Radiation doses at local SVZ recurrence sites recurrence averaged 57.0 ± 4.0 Gy compared to 44.7 ± 6.7 Gy at distant SVZ recurrence sites (p = 0.008). Distant subventricular progression at a site receiving ≤ 45 Gy predicted worse subsequent survival (p = 0.05). Glioblastomas frequently recurred in the subventricular zone, and patient survival was worse when enhancing tumor occurred at sites that received lower radiation doses. This recurrent disease may represent disease undertreated at the time of diagnosis, and further study is needed to determine if improved treatment strategies, such as including the subventricular zone in radiation fields, could improve clinical outcomes.

Pretreatment combination of platelet counts and neutrophil–lymphocyte ratio predicts survival of nasopharyngeal cancer patients receiving intensity-modulated radiotherapy

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Lin YH

2017-05-01

Full Text Available Yu-Hsuan Lin,1 Kuo-Ping Chang,2 Yaoh-Shiang Lin,2,3 Ting-Shou Chang2–4 1Department of Otolaryngology, Head and Neck Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, 2Department of Otolaryngology, Head and Neck Surgery, Kaohsiung Veterans General Hospital, Kaohsiung, 3Department of Otolaryngology, Head and Neck Surgery, National Defense Medical Center, Taipei, 4Institute of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan, Republic of China Background: Increased cancer-related inflammation has been associated with unfavorable clinical outcomes. The combination of platelet count and neutrophil–lymphocyte ratio (COP-NLR has related outcomes in several cancers, except for nasopharyngeal carcinoma (NPC. This study evaluated the prognostic value of COP-NLR in predicting outcome in NPC patients treated with intensity-modulated radiotherapy (IMRT.Materials and methods: We analyzed the data collected from 232 NPC patients. Pretreatment total platelet counts, neutrophil–lymphocyte ratio (NLR, and COP-NLR score were evaluated as potential predictors. Optimal cutoff values for NLR and platelets were determined using receiver operating curve. Patients with both elevated NLR (>3 and platelet counts (>300×109/L were assigned a COP-NLR score of 2; those with one elevated or no elevated value were assigned a COP-NLR a score of 1 or 0. Cox proportional hazards model was used to test the association of these factors and relevant 3-year survivals.Results: Patients (COP-NLR scores 1 and 2=85; score 0=147 were followed up for 55.19 months. Univariate analysis showed no association between pretreatment NLR >2.23 and platelet counts >290.5×109/L and worse outcomes. Multivariate analysis revealed that those with COP-NLR scores of 0 had better 3-year disease-specific survival (P=0.02, overall survival (P=0.024, locoregional relapse-free survival (P=0.004, and distant

Prediction of survival by texture-based automated quantitative assessment of regional disease patterns on CT in idiopathic pulmonary fibrosis

International Nuclear Information System (INIS)

Lee, Sang Min; Seo, Joon Beom; Oh, Sang Young; Lee, Sang Min; Kim, Namkug; Kim, Tae Hoon; Song, Jin Woo

2018-01-01

To retrospectively investigate whether the baseline extent and 1-year change in regional disease patterns on CT can predict survival of patients with idiopathic pulmonary fibrosis (IPF). A total of 144 IPF patients with CT scans at the time of diagnosis and 1 year later were included. The extents of five regional disease patterns were quantified using an in-house texture-based automated system. The fibrosis score was defined as the sum of the extent of honeycombing and reticular opacity. The Cox proportional hazard model was used to determine the independent predictors of survival. A total of 106 patients (73.6%) died during the follow-up period. Univariate analysis revealed that age, baseline forced vital capacity, total lung capacity, diffusing capacity of the lung for carbon monoxide, six-minute walk distance, desaturation , honeycombing, reticular opacity, fibrosis score, and interval changes in honeycombing and fibrosis score were significantly associated with survival. Multivariate analysis revealed that age, desaturation, fibrosis score and interval change in fibrosis score were significant independent predictors of survival (p = 0.003, <0.001, 0.001 and <0.001). The C-index for the developed model was 0.768. Texture-based, automated CT quantification of fibrosis can be used as an independent predictor of survival in IPF patients. (orig.)

Prediction of survival by texture-based automated quantitative assessment of regional disease patterns on CT in idiopathic pulmonary fibrosis

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Lee, Sang Min; Seo, Joon Beom; Oh, Sang Young; Lee, Sang Min; Kim, Namkug [University of Ulsan College of Medicine, Asan Medical Center, Department of Radiology and Research Institute of Radiology, Seoul (Korea, Republic of); Kim, Tae Hoon; Song, Jin Woo [University of Ulsan College of Medicine, Asan Medical Center, Department of Pulmonary and Critical Care Medicine, Seoul (Korea, Republic of)

2018-03-15

To retrospectively investigate whether the baseline extent and 1-year change in regional disease patterns on CT can predict survival of patients with idiopathic pulmonary fibrosis (IPF). A total of 144 IPF patients with CT scans at the time of diagnosis and 1 year later were included. The extents of five regional disease patterns were quantified using an in-house texture-based automated system. The fibrosis score was defined as the sum of the extent of honeycombing and reticular opacity. The Cox proportional hazard model was used to determine the independent predictors of survival. A total of 106 patients (73.6%) died during the follow-up period. Univariate analysis revealed that age, baseline forced vital capacity, total lung capacity, diffusing capacity of the lung for carbon monoxide, six-minute walk distance, desaturation{sub ,} honeycombing, reticular opacity, fibrosis score, and interval changes in honeycombing and fibrosis score were significantly associated with survival. Multivariate analysis revealed that age, desaturation, fibrosis score and interval change in fibrosis score were significant independent predictors of survival (p = 0.003, <0.001, 0.001 and <0.001). The C-index for the developed model was 0.768. Texture-based, automated CT quantification of fibrosis can be used as an independent predictor of survival in IPF patients. (orig.)

PROGNOSTIC FACTORS OF SURVIVAL IN RENAL CANCER

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A. V. Seriogin

2014-08-01

Full Text Available The purpose of the study was to reveal the independent anatomic, histological, and clinical factors of cancer-specific survival in patients with renal-cell carcinoma (RCC. For this, the authors retrospectively analyzed their experience with radical surgical treatments in 73 RCC patients operated on at the Department of Urology and Surgical Andrology, Russian Medical Academy of Postgraduate Education, from January 1, 1999 to December 31, 2004; their outcomes have become known by the present time. There was a statistically significant correlation of cancer-specific survival with its parameters, such as pathological stage of a tumor, its maximum pathological size, differentiation grade, involvement of regional lymph nodes, venous tumor thrombosis, level of thrombocytosis, and degree of the clinical symptoms of the disease. Multivariate analysis of survival in RCC in relation to the prognostic factors could reveal odd ratios for the limit values of significant prognostic factors. The statistically significant prognostic values established in the present study, as well as the molecular factors the implication of which is being now investigated can become in future an effective addition to the TNM staging system to define indications for certain treatments and to predict survival in RCC  

PROGNOSTIC FACTORS OF SURVIVAL IN RENAL CANCER

Directory of Open Access Journals (Sweden)

A. V. Seriogin

2009-01-01

Full Text Available The purpose of the study was to reveal the independent anatomic, histological, and clinical factors of cancer-specific survival in patients with renal-cell carcinoma (RCC. For this, the authors retrospectively analyzed their experience with radical surgical treatments in 73 RCC patients operated on at the Department of Urology and Surgical Andrology, Russian Medical Academy of Postgraduate Education, from January 1, 1999 to December 31, 2004; their outcomes have become known by the present time. There was a statistically significant correlation of cancer-specific survival with its parameters, such as pathological stage of a tumor, its maximum pathological size, differentiation grade, involvement of regional lymph nodes, venous tumor thrombosis, level of thrombocytosis, and degree of the clinical symptoms of the disease. Multivariate analysis of survival in RCC in relation to the prognostic factors could reveal odd ratios for the limit values of significant prognostic factors. The statistically significant prognostic values established in the present study, as well as the molecular factors the implication of which is being now investigated can become in future an effective addition to the TNM staging system to define indications for certain treatments and to predict survival in RCC  

Using cure models for analyzing the influence of pathogens on salmon survival

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Ray, Adam R; Perry, Russell W.; Som, Nicholas A.; Bartholomew, Jerri L

2014-01-01

Parasites and pathogens influence the size and stability of wildlife populations, yet many population models ignore the population-level effects of pathogens. Standard survival analysis methods (e.g., accelerated failure time models) are used to assess how survival rates are influenced by disease. However, they assume that each individual is equally susceptible and will eventually experience the event of interest; this assumption is not typically satisfied with regard to pathogens of wildlife populations. In contrast, mixture cure models, which comprise logistic regression and survival analysis components, allow for different covariates to be entered into each part of the model and provide better predictions of survival when a fraction of the population is expected to survive a disease outbreak. We fitted mixture cure models to the host–pathogen dynamics of Chinook Salmon Oncorhynchus tshawytscha and Coho Salmon O. kisutch and the myxozoan parasite Ceratomyxa shasta. Total parasite concentration, water temperature, and discharge were used as covariates to predict the observed parasite-induced mortality in juvenile salmonids collected as part of a long-term monitoring program in the Klamath River, California. The mixture cure models predicted the observed total mortality well, but some of the variability in observed mortality rates was not captured by the models. Parasite concentration and water temperature were positively associated with total mortality and the mortality rate of both Chinook Salmon and Coho Salmon. Discharge was positively associated with total mortality for both species but only affected the mortality rate for Coho Salmon. The mixture cure models provide insights into how daily survival rates change over time in Chinook Salmon and Coho Salmon after they become infected with C. shasta.

Predicted vitamin D status and colon cancer recurrence and mortality in CALGB 89803 (Alliance).

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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.

MAP17 and SGLT1 protein expression levels as prognostic markers for cervical tumor patient survival.

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Marco Perez

Full Text Available MAP17 is a membrane-associated protein that is overexpressed in human tumors. Because the expression of MAP17 increases reactive oxygen species (ROS generation through SGLT1 in cancer cells, in the present work, we investigated whether MAP17 and/or SGLT1 might be markers for the activity of treatments involving oxidative stress, such as cisplatin or radiotherapy. First, we confirmed transcriptional alterations in genes involved in the oxidative stress induced by MAP17 expression in HeLa cervical tumor cells and found that Hela cells expressing MAP17 were more sensitive to therapies that induce ROS than were parental cells. Furthermore, MAP17 increased glucose uptake through SGLT receptors. We then analyzed MAP17 and SGLT1 expression levels in cervical tumors treated with cisplatin plus radiotherapy and correlated the expression levels with patient survival. MAP17 and SGLT1 were expressed in approximately 70% and 50% of cervical tumors of different types, respectively, but they were not expressed in adenoma tumors. Furthermore, there was a significant correlation between MAP17 and SGLT1 expression levels. High levels of either MAP17 or SGLT1 correlated with improved patient survival after treatment. However, the patients with high levels of both MAP17 and SGLT1 survived through the end of this study. Therefore, the combination of high MAP17 and SGLT1 levels is a marker for good prognosis in patients with cervical tumors after cisplatin plus radiotherapy treatment. These results also suggest that the use of MAP17 and SGLT1 markers may identify patients who are likely to exhibit a better response to treatments that boost oxidative stress in other cancer types.

Cytotoxic T lymphocyte response to peptide vaccination predicts survival in stage III colorectal cancer.

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Kawamura, Junichiro; Sugiura, Fumiaki; Sukegawa, Yasushi; Yoshioka, Yasumasa; Hida, Jin-Ichi; Hazama, Shoichi; Okuno, Kiyotaka

2018-02-23

We previously reported a phase I clinical trial of a peptide vaccine ring finger protein 43 (RNF43) and 34-kDa translocase of the outer mitochondrial membrane (TOMM34) combined with uracil-tegafur (UFT)/LV for patients with metastatic colorectal cancer (CRC), and demonstrated the safety and immunological responsiveness of this combination therapy. In this study, we evaluated vaccination-induced immune responses to clarify the survival benefit of the combination therapy as adjuvant treatment. We enrolled 44 patients initially in an HLA-masked fashion. After the disclosure of HLA, 28 patients were in the HLA-A*2402-matched and 16 were in the unmatched group. In the HLA-matched group, 14 patients had positive CTL responses specific for the RNF43 and/or TOMM34 peptides after 2 cycles of treatment and 9 had negative responses; in the HLA-unmatched group, 10 CTL responses were positive and 2 negative. In the HLA-matched group, 3-year relapse-free survival (RFS) was significantly better in the positive CTL subgroup than in the negative-response subgroup. Patients with negative vaccination-induced CTL responses showed a significant trend towards shorter RFS than those with positive responses. Moreover, in the HLA-unmatched group, the positive CTL response subgroup showed an equally good 3-year RFS as in the HLA-matched group. In conclusion, vaccination-induced CTL response to peptide vaccination could predict survival in the adjuvant setting for stage III CRC. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

Predictability of twentieth century sea-level rise from past data

International Nuclear Information System (INIS)

Bittermann, Klaus; Rahmstorf, Stefan; Perrette, Mahé; Vermeer, Martin

2013-01-01

The prediction of global sea-level rise is one of the major challenges of climate science. While process-based models are still being improved to capture the complexity of the processes involved, semi-empirical models, exploiting the observed connection between global-mean sea level and global temperature and calibrated with data, have been developed as a complementary approach. Here we investigate whether twentieth century sea-level rise could have been predicted with such models given a knowledge of twentieth century global temperature increase. We find that either proxy or early tide gauge data do not hold enough information to constrain the model parameters well. However, in combination, the use of proxy and tide gauge sea-level data up to 1900 AD allows a good prediction of twentieth century sea-level rise, despite this rise being well outside the rates experienced in previous centuries during the calibration period of the model. The 90% confidence range for the linear twentieth century rise predicted by the semi-empirical model is 13–30 cm, whereas the observed interval (using two tide gauge data sets) is 14–26 cm. (letter)

Prediction of monthly regional groundwater levels through hybrid soft-computing techniques

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Chang, Fi-John; Chang, Li-Chiu; Huang, Chien-Wei; Kao, I.-Feng

2016-10-01

Groundwater systems are intrinsically heterogeneous with dynamic temporal-spatial patterns, which cause great difficulty in quantifying their complex processes, while reliable predictions of regional groundwater levels are commonly needed for managing water resources to ensure proper service of water demands within a region. In this study, we proposed a novel and flexible soft-computing technique that could effectively extract the complex high-dimensional input-output patterns of basin-wide groundwater-aquifer systems in an adaptive manner. The soft-computing models combined the Self Organized Map (SOM) and the Nonlinear Autoregressive with Exogenous Inputs (NARX) network for predicting monthly regional groundwater levels based on hydrologic forcing data. The SOM could effectively classify the temporal-spatial patterns of regional groundwater levels, the NARX could accurately predict the mean of regional groundwater levels for adjusting the selected SOM, the Kriging was used to interpolate the predictions of the adjusted SOM into finer grids of locations, and consequently the prediction of a monthly regional groundwater level map could be obtained. The Zhuoshui River basin in Taiwan was the study case, and its monthly data sets collected from 203 groundwater stations, 32 rainfall stations and 6 flow stations during 2000 and 2013 were used for modelling purpose. The results demonstrated that the hybrid SOM-NARX model could reliably and suitably predict monthly basin-wide groundwater levels with high correlations (R2 > 0.9 in both training and testing cases). The proposed methodology presents a milestone in modelling regional environmental issues and offers an insightful and promising way to predict monthly basin-wide groundwater levels, which is beneficial to authorities for sustainable water resources management.

Pathologic complete response predicts long-term survival following preoperative radiation therapy for rectal cancer

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Ahmad, Neelofur R.; Nagle, Deborah A.; Topham, Allan

1997-01-01

Purpose: The finding of a pathologic complete response (pCR) after preoperative radiation therapy (RT) for rectal cancer is frequently used as a surrogate endpoint for treatment outcome. In most reported series, the pCR rate ranges from 10 to 25%. An underlying assumption is that pCR relates to favorable long-term patient outcome; however, such results are rarely reported. The purpose of this study was to determine the long-term outcome of patients having pCR's following preoperative RT and surgery for rectal cancer. Materials and Methods: Between 1978 and 1993, 49 of 315 patients (16%) were found to have pCR's following 40 to 65 Gy of preoperative RT for rectal cancer (median RT dose 55.8 Gy). Six complete responders also received concurrent 5-FU chemotherapy with RT. Follow-up time ranged from 7 to 224 months (median 52 months). Actuarial overall survival (OS), disease-free survival (DFS), and local control (LC) rates were calculated. Patient outcome was analyzed with respect to pretreatment clinical stage (mobile vs. tethered/fixed on digital exam), tumor level in the rectum as measured from the anorectal ring (0-3 cm vs. >3 cm), type of surgery (local excision, APR, or other), and use of concurrent chemotherapy vs. RT alone. Results: Prior to treatment, clinical stage tumor stage was 43% mobile ((21(49))) and 35% tethered/fixed ((17(49))). Twenty-two percent ((11(49))) did not have palpable tumor at presentation to our institution due to prior local excision of an invasive cancer. Tumor level in the rectum was 74% 0-3 cm, 16% >3 to 6 cm, and 10% > 6 cm. Surgical procedures were 12% APR, 24% LAR, 6% combined abdominal transsacral resection (CATS), 27% coloanal anastamosis, and 31% full thickness local excision. Overall, 2 of 49 patients (4%) developed a local tumor recurrence, and 4 of 49 (8%) developed distant metastases. The overall 5- and 10-year actuarial survival rates were 91% and 86%, respectively. The 5- and 10-year actuarial DFS rate was 85%, and the

Influence of nutrient levels in Tamarix on Diorhabda sublineata (Coleoptera: Chrysomelidae) survival and fitness with implications for biological control.

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Guenther, D A; Gardner, K T; Thompson, D C

2011-02-01

Establishment of the saltcedar leaf beetle (Diorhabda spp.) has been unpredictable when caged or released in the field for saltcedar (Tamarix spp.) biocontrol. It has been observed that one caged tree might be voraciously fed upon by beetles while an adjacent tree in the cage is left untouched. We hypothesized that differences in the nutrient content of individual trees may explain this behavior. We evaluated survival, development rate, and egg production of beetles fed in the laboratory on saltcedar foliage from trees that had been grown under a range of fertilizer treatments. Tissue samples from the experimental trees and from the field were analyzed for percent nitrogen, phosphorus, and potassium. There was essentially no survival of beetle larvae fed foliage from saltcedar trees at nitrogen levels below 2.0%. At levels above 2.0% N, beetle larvae had corresponding increased survival rates and shorter development times. Multiple regression analyses indicated that nitrogen and phosphorus are important for larval survival and faster development rates. Higher levels of potassium were important for increased egg cluster production. The plant tissue analysis showed that the percentage of nitrogen in the experimental trees reflected the range of trees in the field and also that there is high variability within trees in the field. Our research indicates that if beetles are released on trees with poor nutrient quality, the larvae will not survive. © 2011 Entomological Society of America

Early survival prediction after intra-arterial therapies: a 3D quantitative MRI assessment of tumour response after TACE or radioembolization of colorectal cancer metastases to the liver

International Nuclear Information System (INIS)

Chapiro, Julius; Savic, Lynn Jeanette; Duran, Rafael; Schernthaner, Ruediger; Wang, Zhijun; Geschwind, Jean-Francois; Lin, MingDe; Lesage, David

2015-01-01

This study evaluated the predictive role of 1D, 2D and 3D quantitative, enhancement-based MRI regarding overall survival (OS) in patients with colorectal liver metastases (CLM) following intra-arterial therapies (IAT). This retrospective analysis included 29 patients who underwent transarterial chemoembolization (TACE) or radioembolization and received MRI within 6 weeks after therapy. Tumour response was assessed using 1D and 2D criteria (such as European Association for the Study of the Liver guidelines [EASL] and modified Response Evaluation Criteria in Solid Tumors [mRECIST]). In addition, a segmentation-based 3D quantification of overall (volumetric [v] RECIST) and enhancing lesion volume (quantitative [q] EASL) was performed on portal venous phase MRI. Accordingly, patients were classified as responders (R) and non-responders (NR). Survival was evaluated using Kaplan-Meier analysis and compared using Cox proportional hazard ratios (HR). Only enhancement-based criteria identified patients as responders. EASL and mRECIST did not predict patient survival (P = 0.27 and P = 0.44, respectively). Using uni- and multivariate analysis, qEASL was identified as the sole predictor of patient survival (9.9 months for R, 6.9 months for NR; P = 0.038; HR 0.4). The ability of qEASL to predict survival early after IAT provides evidence for potential advantages of 3D quantitative tumour analysis. (orig.)

Early survival prediction after intra-arterial therapies: a 3D quantitative MRI assessment of tumour response after TACE or radioembolization of colorectal cancer metastases to the liver

Energy Technology Data Exchange (ETDEWEB)

Chapiro, Julius; Savic, Lynn Jeanette [The Johns Hopkins Hospital, Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, Baltimore, MD (United States); Charite Universitaetsmedizin, Department of Diagnostic and Interventional Radiology, Berlin (Germany); Duran, Rafael; Schernthaner, Ruediger; Wang, Zhijun; Geschwind, Jean-Francois [The Johns Hopkins Hospital, Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, Baltimore, MD (United States); Lin, MingDe [The Johns Hopkins Hospital, Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, Baltimore, MD (United States); U/S Imaging and Interventions (UII), Philips Research North America, Briarcliff Manor, NY (United States); Lesage, David [Philips Research, Medisys, Suresnes (France)

2015-07-15

This study evaluated the predictive role of 1D, 2D and 3D quantitative, enhancement-based MRI regarding overall survival (OS) in patients with colorectal liver metastases (CLM) following intra-arterial therapies (IAT). This retrospective analysis included 29 patients who underwent transarterial chemoembolization (TACE) or radioembolization and received MRI within 6 weeks after therapy. Tumour response was assessed using 1D and 2D criteria (such as European Association for the Study of the Liver guidelines [EASL] and modified Response Evaluation Criteria in Solid Tumors [mRECIST]). In addition, a segmentation-based 3D quantification of overall (volumetric [v] RECIST) and enhancing lesion volume (quantitative [q] EASL) was performed on portal venous phase MRI. Accordingly, patients were classified as responders (R) and non-responders (NR). Survival was evaluated using Kaplan-Meier analysis and compared using Cox proportional hazard ratios (HR). Only enhancement-based criteria identified patients as responders. EASL and mRECIST did not predict patient survival (P = 0.27 and P = 0.44, respectively). Using uni- and multivariate analysis, qEASL was identified as the sole predictor of patient survival (9.9 months for R, 6.9 months for NR; P = 0.038; HR 0.4). The ability of qEASL to predict survival early after IAT provides evidence for potential advantages of 3D quantitative tumour analysis. (orig.)

Predicting neo-adjuvant chemotherapy response and progression-free survival of locally advanced breast cancer using textural features of intratumoral heterogeneity on F-18 FDG PET/CT and diffusion-weighted MR imaging.

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Yoon, Hai-Jeon; Kim, Yemi; Chung, Jin; Kim, Bom Sahn

2018-03-30

Predicting response to neo-adjuvant chemotherapy (NAC) and survival in locally advanced breast cancer (LABC) is important. This study investigated the prognostic value of tumor heterogeneity evaluated with textural analysis through F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and diffusion-weighted imaging (DWI). We enrolled 83 patients with LABC who had completed NAC and curative surgery. Tumor texture indices from pretreatment FDG PET and DWI were extracted from histogram analysis and 7 different parent matrices: co-occurrence matrix, the voxel-alignment matrix, neighborhood intensity difference matrix, intensity size-zone matrix (ISZM), normalized gray-level co-occurrence matrix (NGLCM), neighboring gray-level dependence matrix (NGLDM), and texture spectrum matrix. The predictive values of textural features were tested regarding both pathologic NAC response and progression-free survival. Among 83 patients, 46 were pathologic responders, while 37 were nonresponders. The PET texture indices from 7 parent matrices, DWI texture indices from histogram, and 1 parent matrix (NGLCM) showed significant differences according to NAC response. On multivariable analysis, number nonuniformity of PET extracted from the NGLDM was an independent predictor of pathologic response (P = .009). During a median follow-up period of 17.3 months, 14 patients experienced recurrence. High-intensity zone emphasis (HIZE) and high-intensity short-zone emphasis (HISZE) from PET extracted from ISZM were significant textural predictors (P = .011 and P = .033). On Cox regression analysis, only HIZE was a significant predictor of recurrence (P = .027), while HISZE showed borderline significance (P = .107). Tumor texture indices are useful for NAC response prediction in LABC. Moreover, PET texture indices can help to predict disease recurrence. © 2018 Wiley Periodicals, Inc.

A six-gene signature predicts survival of patients with localized pancreatic ductal adenocarcinoma.

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Jeran K Stratford

2010-07-01

Full Text Available Pancreatic ductal adenocarcinoma (PDAC remains a lethal disease. For patients with localized PDAC, surgery is the best option, but with a median survival of less than 2 years and a difficult and prolonged postoperative course for most, there is an urgent need to better identify patients who have the most aggressive disease.We analyzed the gene expression profiles of primary tumors from patients with localized compared to metastatic disease and identified a six-gene signature associated with metastatic disease. We evaluated the prognostic potential of this signature in a training set of 34 patients with localized and resected PDAC and selected a cut-point associated with outcome using X-tile. We then applied this cut-point to an independent test set of 67 patients with localized and resected PDAC and found that our signature was independently predictive of survival and superior to established clinical prognostic factors such as grade, tumor size, and nodal status, with a hazard ratio of 4.1 (95% confidence interval [CI] 1.7-10.0. Patients defined to be high-risk patients by the six-gene signature had a 1-year survival rate of 55% compared to 91% in the low-risk group.Our six-gene signature may be used to better stage PDAC patients and assist in the difficult treatment decisions of surgery and to select patients whose tumor biology may benefit most from neoadjuvant therapy. The use of this six-gene signature should be investigated in prospective patient cohorts, and if confirmed, in future PDAC clinical trials, its potential as a biomarker should be investigated. Genes in this signature, or the pathways that they fall into, may represent new therapeutic targets. Please see later in the article for the Editors' Summary.

Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores.

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Houthooft, Rein; Ruyssinck, Joeri; van der Herten, Joachim; Stijven, Sean; Couckuyt, Ivo; Gadeyne, Bram; Ongenae, Femke; Colpaert, Kirsten; Decruyenaere, Johan; Dhaene, Tom; De Turck, Filip

2015-03-01

The length of stay of critically ill patients in the intensive care unit (ICU) is an indication of patient ICU resource usage and varies considerably. Planning of postoperative ICU admissions is important as ICUs often have no nonoccupied beds available. Estimation of the ICU bed availability for the next coming days is entirely based on clinical judgement by intensivists and therefore too inaccurate. For this reason, predictive models have much potential for improving planning for ICU patient admission. Our goal is to develop and optimize models for patient survival and ICU length of stay (LOS) based on monitored ICU patient data. Furthermore, these models are compared on their use of sequential organ failure (SOFA) scores as well as underlying raw data as input features. Different machine learning techniques are trained, using a 14,480 patient dataset, both on SOFA scores as well as their underlying raw data values from the first five days after admission, in order to predict (i) the patient LOS, and (ii) the patient mortality. Furthermore, to help physicians in assessing the prediction credibility, a probabilistic model is tailored to the output of our best-performing model, assigning a belief to each patient status prediction. A two-by-two grid is built, using the classification outputs of the mortality and prolonged stay predictors to improve the patient LOS regression models. For predicting patient mortality and a prolonged stay, the best performing model is a support vector machine (SVM) with GA,D=65.9% (area under the curve (AUC) of 0.77) and GS,L=73.2% (AUC of 0.82). In terms of LOS regression, the best performing model is support vector regression, achieving a mean absolute error of 1.79 days and a median absolute error of 1.22 days for those patients surviving a nonprolonged stay. Using a classification grid based on the predicted patient mortality and prolonged stay, allows more accurate modeling of the patient LOS. The detailed models allow to support

Monitoring of regulatory T cell frequencies and expression of CTLA-4 on T cells, before and after DC vaccination, can predict survival in GBM patients.

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Brendan Fong

Full Text Available PURPOSE: Dendritic cell (DC vaccines have recently emerged as an innovative therapeutic option for glioblastoma patients. To identify novel surrogates of anti-tumor immune responsiveness, we studied the dynamic expression of activation and inhibitory markers on peripheral blood lymphocyte (PBL subsets in glioblastoma patients treated with DC vaccination at UCLA. EXPERIMENTAL DESIGN: Pre-treatment and post-treatment PBL from 24 patients enrolled in two Phase I clinical trials of dendritic cell immunotherapy were stained and analyzed using flow cytometry. A univariate Cox proportional hazards model was utilized to investigate the association between continuous immune monitoring variables and survival. Finally, the immune monitoring variables were dichotomized and a recursive partitioning survival tree was built to obtain cut-off values predictive of survival. RESULTS: The change in regulatory T cell (CD3(+CD4(+CD25(+CD127(low frequency in PBL was significantly associated with survival (p = 0.0228; hazard ratio = 3.623 after DC vaccination. Furthermore, the dynamic expression of the negative co-stimulatory molecule, CTLA-4, was also significantly associated with survival on CD3(+CD4(+ T cells (p = 0.0191; hazard ratio = 2.840 and CD3(+CD8(+ T cells (p = 0.0273; hazard ratio = 2.690, while that of activation markers (CD25, CD69 was not. Finally, a recursive partitioning tree algorithm was utilized to dichotomize the post/pre fold change immune monitoring variables. The resultant cut-off values from these immune monitoring variables could effectively segregate these patients into groups with significantly different overall survival curves. CONCLUSIONS: Our results suggest that monitoring the change in regulatory T cell frequencies and dynamic expression of the negative co-stimulatory molecules on peripheral blood T cells, before and after DC vaccination, may predict survival. The cut-off point generated from these data can be utilized in future

Levels of and changes in life satisfaction predict mortality hazards: Disentangling the role of physical health, perceived control, and social orientation.

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Hülür, Gizem; Heckhausen, Jutta; Hoppmann, Christiane A; Infurna, Frank J; Wagner, Gert G; Ram, Nilam; Gerstorf, Denis

2017-09-01

It is well documented that well-being typically evinces precipitous decrements at the end of life. However, research has primarily taken a postdictive approach by knowing the outcome (date of death) and aligning, in retrospect, how well-being has changed for people with documented death events. In the present study, we made use of a predictive approach by examining whether and how levels of and changes in life satisfaction prospectively predict mortality hazards and delineate the role of contributing factors, including health, perceived control, and social orientation. To do so, we applied shared parameter growth-survival models to 20-year longitudinal data from 10,597 participants (n = 1,560 [15%] deceased; age at baseline: M = 44 years, SD = 17, range = 18-98 years) from the national German Socio-Economic Panel Study. Our findings showed that lower levels and steeper declines of life satisfaction each uniquely predicted higher mortality risks. Results also revealed moderating effects of age and perceived control: Life satisfaction levels and changes had stronger predictive effects for mortality hazards among older adults. Perceived control was associated with lower mortality hazards; however, this effect was diminished for those who experienced accelerated life satisfaction decline. Variance decomposition suggests that predictive effects of life satisfaction trajectories were partially unique (3%-6%) and partially shared with physical health, perceived control, and social orientation (17%-19%). Our discussion focuses on the strengths and challenges of a predictive approach to link developmental changes (in life satisfaction) to mortality hazards, and considers implications of our findings for healthy aging. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

DDX3X Biomarker Correlates with Poor Survival in Human Gliomas

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Dueng-Yuan Hueng

2015-07-01

Full Text Available Primary high-grade gliomas possess invasive growth and lead to unfavorable survival outcome. The investigation of biomarkers for prediction of survival outcome in patients with gliomas is important for clinical assessment. The DEAD (Asp-Glu-Ala-Asp box helicase 3, X-linked (DDX3X controls tumor migration, proliferation, and progression. However, the role of DDX3X in defining the pathological grading and survival outcome in patients with human gliomas is not yet clarified. We analyzed the DDX3X gene expression, WHO pathological grading, and overall survival from de-linked data. Further validation was done using quantitative RT-PCR of cDNA from normal brain and glioma, and immunohistochemical (IHC staining of tissue microarray. Statistical analysis of GEO datasets showed that DDX3X mRNA expression demonstrated statistically higher in WHO grade IV (n = 81 than in non-tumor controls (n = 23, p = 1.13 × 10−10. Moreover, DDX3X level was also higher in WHO grade III (n = 19 than in non-tumor controls (p = 2.43 × 10−5. Kaplan–Meier survival analysis showed poor survival in patients with high DDX3X mRNA levels (n = 24 than in those with low DDX3X expression (n = 53 (median survival, 115 vs. 58 weeks, p = 0.0009, by log-rank test, hazard ratio: 0.3507, 95% CI: 0.1893–0.6496. Furthermore, DDX3X mRNA expression and protein production significantly increased in glioma cells compared with normal brain tissue examined by quantitative RT-PCR, and Western blot. IHC staining showed highly staining of high-grade glioma in comparison with normal brain tissue. Taken together, DDX3X expression level positively correlates with WHO pathologic grading and poor survival outcome, indicating that DDX3X is a valuable biomarker in human gliomas.

Extensions and Applications of the Cox-Aalen Survival Model

DEFF Research Database (Denmark)

Scheike, Thomas H.; Zhang, Mei-Jie

2003-01-01

Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects......Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects...

Monitoring of high-density lipoprotein cholesterol level is predictive of EGFR mutation and efficacy of EGFR-TKI in patients with advanced lung adenocarcinoma

Directory of Open Access Journals (Sweden)

Lv Y

2016-01-01

Full Text Available Yang Lv,1,2 Li-Yun Miao,2 Qiu-Fang Chen,1 Yan Li,2 Zhi-Xiang Shi,1 Xuan-Sheng Ding1 1Department of Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, People’s Republic of China; 2Division of Respiratory Medicine, Department of Respiration, The Affiliated Drum Tower Hospital of Nanjing University Medical College, Nanjing University Medical School, Nanjing, Jiangsu, People’s Republic of China Abstract: High-density lipoprotein cholesterol (HDL-C has an inverse association with the incidence of lung cancer. However, whether it can be used as a predictive factor in advanced lung adenocarcinoma patients treated with epidermal growth factor receptor (EGFR tyrosine kinase inhibitors (TKI still remains undefined. This research aimed at studying the relationship of serum HDL-C baseline level and HDL-C kinetics to EGFR mutation, the efficacy of EGFR-TKI, and the predictive value of PFS. The presence of mutation rate in the 192 patients with lung adenocarcinoma was compared within stratified groups. Levels of baseline HDL-C and kinetics of HDL-C were analyzed retrospectively in patients treated with EGFR-TKI harboring EGFR mutation. Univariate and multivariate analyses were performed to investigate the prognostic value of HDL-C. EGFR mutation rate of HDL-C high-level group was significantly higher than that of low-level group (59.0% vs 35.6%, P=0.001. Multivariate logistic analysis showed that high-level HDL-C was an independent predictive factor for EGFR gene mutation (P=0.005; odds ratio =0.417; 95% confidence interval [CI], 0.227–0.768. Patients with a low level of HDL-C before therapy showed a progression of disease in most cases (P<0.001. According to HDL-C kinetics, patients who received EGFR-TKI treatment harboring EGFR mutation were divided into four groups. Univariate analysis showed that patients in nondecreased group had longer progression-free survival (P<0.001; hazard ratio =0.003; 95% CI, 0.001–0.018. Multivariate

Survival of rats subjected to acute anemia at different levels of erythrocyte 2,3-diphosphoglycerate.

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Arturson, G; Westman, M

1975-12-01

An experimental procedure was worked out in which rats were subjected to an exchange of erythrocytes, followed by acute anemia by means of hemodilution. One group of rats received erythrocytes with a high concentration of 2,3-diphosphoglycerate (DPG), and the other group was given erythrocytes with a low DPG concentration. The survival rate was equal in the two groups. Irrespective of DPG concentration, the rats whose hemoglobin concentration reached the lowest level died. The rats that died were also more acidotic than the others. The results indicate that the hemoglobin concentration and the pH value were more important determinants for survival than the DPG concentrations.

Serum lactate dehydrogenase with a systemic inflammation score is useful for predicting response and survival in patients with newly diagnosed diffuse large B-cell lymphoma.

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Jung, Sung-Hoon; Yang, Deok-Hwan; Ahn, Jae-Sook; Kim, Yeo-Kyeoung; Kim, Hyeoung-Joon; Lee, Je-Jung

2015-01-01

We evaluated the relationship between serum lactate dehydrogenase (LDH) level with systemic inflammation score and survival in 213 patients with diffuse large B-cell lymphoma (DLBCL) receiving R-CHOP chemotherapy. The patients were classified into 3 groups based on LDH with the Glasgow Prognostic Score (L-GPS). A score of 2 was assigned to patients with elevated C-reactive protein, hypoalbuminemia and elevated LDH, a score of 1 to those with one or two abnormalities and a score of 0 to those with no abnormality. In multivariate analysis, independent poor prognostic factors for progression-free survival were L-GPS 2 [hazard ratio (HR) 5.415, p = 0.001], Eastern Cooperative Oncology Group performance status (ECOG PS) ≥2 (HR 3.504, p = 0.001) and bulky lesion (HR 2.030, p = 0.039). Independent poor prognostic factors for overall survival were L-GPS 2 (HR 5.898, p = 0.001) and ECOG PS ≥2 (HR 3.525, p = 0.001). The overall response rate for the R-CHOP chemotherapy decreased according to the L-GPS; it was 96.7% at L-GPS 0, 87% at L-GPS 1 and 75% at L-GPS 2 (p = 0.009). L-GPS based on systemic inflammatory indicators may be a useful clinical prognostic indicator for survival, and predicts the response for R-CHOP chemotherapy in patients with newly diagnosed DLBCL. © 2014 S. Karger AG, Basel.

Loss of NOTCH2 Positively Predicts Survival in Subgroups of Human Glial Brain Tumors

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Boulay, Jean-Louis; Miserez, André R.; Zweifel, Christian; Sivasankaran, Balasubramanian; Kana, Veronika; Ghaffari, Anthony; Luyken, Cordelia; Sabel, Michael; Zerrouqi, Abdessamad; Wasner, Morten; Meir, Erwin Van; Tolnay, Markus; Reifenberger, Guido; Merlo, Adrian

2007-01-01

The structural complexity of chromosome 1p centromeric region has been an obstacle for fine mapping of tumor suppressor genes in this area. Loss of heterozygosity (LOH) on chromosome 1p is associated with the longer survival of oligodendroglioma (OD) patients. To test the clinical relevance of 1p loss in glioblastomas (GBM) patients and identifiy the underlying tumor suppressor locus, we constructed a somatic deletion map on chromosome 1p in 26 OG and 118 GBM. Deletion hotspots at 4 microsatellite markers located at 1p36.3, 1p36.1, 1p22 and 1p11 defined 10 distinct haplotypes that were related to patient survival. We found that loss of 1p centromeric marker D1S2696 within NOTCH2 intron 12 was associated with favorable prognosis in OD (P = 0.0007) as well as in GBM (P = 0.0175), while 19q loss, concomitant with 1p LOH in OD, had no influence on GBM survival (P = 0.918). Assessment of the intra-chromosomal ratio between NOTCH2 and its 1q21 pericentric duplication N2N (N2/N2N-test) allowed delineation of a consistent centromeric breakpoint in OD that also contained a minimally lost area in GBM. OD and GBM showed distinct deletion patterns that converged to the NOTCH2 gene in both glioma subtypes. Moreover, the N2/N2N-test disclosed homozygous deletions of NOTCH2 in primary OD. The N2/N2N test distinguished OD from GBM with a specificity of 100% and a sensitivity of 97%. Combined assessment of NOTCH2 genetic markers D1S2696 and N2/N2N predicted 24-month survival with an accuracy (0.925) that is equivalent to histological classification combined with the D1S2696 status (0.954) and higher than current genetic evaluation by 1p/19q LOH (0.762). Our data propose NOTCH2 as a powerful new molecular test to detect prognostically favorable gliomas. PMID:17593975

Loss of NOTCH2 positively predicts survival in subgroups of human glial brain tumors.

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Jean-Louis Boulay

Full Text Available The structural complexity of chromosome 1p centromeric region has been an obstacle for fine mapping of tumor suppressor genes in this area. Loss of heterozygosity (LOH on chromosome 1p is associated with the longer survival of oligodendroglioma (OD patients. To test the clinical relevance of 1p loss in glioblastomas (GBM patients and identifiy the underlying tumor suppressor locus, we constructed a somatic deletion map on chromosome 1p in 26 OG and 118 GBM. Deletion hotspots at 4 microsatellite markers located at 1p36.3, 1p36.1, 1p22 and 1p11 defined 10 distinct haplotypes that were related to patient survival. We found that loss of 1p centromeric marker D1S2696 within NOTCH2 intron 12 was associated with favorable prognosis in OD (P = 0.0007 as well as in GBM (P = 0.0175, while 19q loss, concomitant with 1p LOH in OD, had no influence on GBM survival (P = 0.918. Assessment of the intra-chromosomal ratio between NOTCH2 and its 1q21 pericentric duplication N2N (N2/N2N-test allowed delineation of a consistent centromeric breakpoint in OD that also contained a minimally lost area in GBM. OD and GBM showed distinct deletion patterns that converged to the NOTCH2 gene in both glioma subtypes. Moreover, the N2/N2N-test disclosed homozygous deletions of NOTCH2 in primary OD. The N2/N2N test distinguished OD from GBM with a specificity of 100% and a sensitivity of 97%. Combined assessment of NOTCH2 genetic markers D1S2696 and N2/N2N predicted 24-month survival with an accuracy (0.925 that is equivalent to histological classification combined with the D1S2696 status (0.954 and higher than current genetic evaluation by 1p/19q LOH (0.762. Our data propose NOTCH2 as a powerful new molecular test to detect prognostically favorable gliomas.

Prediction of the survival and functional ability of severe stroke patients after ICU therapeutic intervention

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Aoun-Bacha Zeina

2008-06-01

Full Text Available Abstract Background This study evaluated the benefits and impact of ICU therapeutic interventions on the survival and functional ability of severe cerebrovascular accident (CVA patients. Methods Sixty-two ICU patients suffering from severe ischemic/haemorrhagic stroke were evaluated for CVA severity using APACHE II and the Glasgow coma scale (GCS. Survival was determined using Kaplan-Meier survival tables and survival prediction factors were determined by Cox multivariate analysis. Functional ability was assessed using the stroke impact scale (SIS-16 and Karnofsky score. Risk factors, life support techniques and neurosurgical interventions were recorded. One year post-CVA dependency was investigated using multivariate analysis based on linear regression. Results The study cohort constituted 6% of all CVA (37.8% haemorrhagic/62.2% ischemic admissions. Patient mean(SD age was 65.8(12.3 years with a 1:1 male: female ratio. During the study period 16 patients had died within the ICU and seven in the year following hospital release. The mean(SD APACHE II score at hospital admission was 14.9(6.0 and ICU mean duration of stay was 11.2(15.4 days. Mechanical ventilation was required in 37.1% of cases. Risk ratios were; GCS at admission 0.8(0.14, (p = 0.024, APACHE II 1.11(0.11, (p = 0.05 and duration of mechanical ventilation 1.07(0.07, (p = 0.046. Linear coefficients were: type of CVA – haemorrhagic versus ischemic: -18.95(4.58 (p = 0.007, GCS at hospital admission: -6.83(1.08, (p = 0.001, and duration of hospital stay -0.38(0.14, (p = 0.40. Conclusion To ensure a better prognosis CVA patients require ICU therapeutic interventions. However, as we have shown, where tests can determine the worst affected patients with a poor vital and functional outcome should treatment be withheld?

Groundwater level prediction of landslide based on classification and regression tree

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Yannan Zhao

2016-09-01

Full Text Available According to groundwater level monitoring data of Shuping landslide in the Three Gorges Reservoir area, based on the response relationship between influential factors such as rainfall and reservoir level and the change of groundwater level, the influential factors of groundwater level were selected. Then the classification and regression tree (CART model was constructed by the subset and used to predict the groundwater level. Through the verification, the predictive results of the test sample were consistent with the actually measured values, and the mean absolute error and relative error is 0.28 m and 1.15% respectively. To compare the support vector machine (SVM model constructed using the same set of factors, the mean absolute error and relative error of predicted results is 1.53 m and 6.11% respectively. It is indicated that CART model has not only better fitting and generalization ability, but also strong advantages in the analysis of landslide groundwater dynamic characteristics and the screening of important variables. It is an effective method for prediction of ground water level in landslides.

Elevated serum levels of vascular endothelial growth factor predict a poor prognosis of platinum-based chemotherapy in non-small cell lung cancer

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Zang JL

2017-01-01

Full Text Available Jialan Zang,1–3,* Yong Hu,1,2,* Xiaoyue Xu,1,2 Jie Ni,1,2 Dali Yan,1,2 Siwen Liu,4 Jieyu He,5 Jing Xue,4 Jianzhong Wu,4 Jifeng Feng2 1The Fourth Clinical School of Nanjing Medical University, 2Department of Chemotherapy, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, 3Department of Oncology, The First Hospital of Harbin City, Harbin, 4Center of Clinical Laboratory, Nanjing Medical University Affiliated Cancer Hospital, 5Department of Public Health, Southeast University, Nanjing, People’s Republic of China *These authors contributed equally to this work Aim: This study was designed to investigate the predictive and prognostic values of serum vascular endothelial growth factor (VEGF level in non-small cell lung cancer (NSCLC patients treated with platinum-based chemotherapy. Methods: Patients’ peripheral blood samples were collected prior to chemotherapy and after 1 week of the third cycle of combination chemotherapy. Serum VEGF levels were evaluated through Luminex multiplex technique. Between September 2011 and August 2015, a total of 135 consecutive advanced or recurrent histologically verified NSCLC patients were enrolled in the study. Moreover, all the patients received platinum-based combination chemotherapy as a first-line treatment. Results: No significant associations were found between pretreatment serum VEGF levels and clinical characteristics, such as sex (P=0.0975, age (P=0.2522, stage (P=0.1407, lymph node metastasis (P=0.6409, tumor location (P=0.3520, differentiated degree (P=0.5608, pathological (histological type (P=0.4885, and response to treatment (P=0.9859. The VEGF load per platelet (VEGFPLT levels were not correlated with sex, age, primary tumor site, and pathological type in NSCLC patients (all P>0.05. The median survival time of progression-free survival (PFS was 6.407 and 5.29 months in the low and high groups, respectively, when using 280 pg/mL VEGF level as the cutoff point (P=0.024. Conclusion

SU-E-J-256: Predicting Metastasis-Free Survival of Rectal Cancer Patients Treated with Neoadjuvant Chemo-Radiotherapy by Data-Mining of CT Texture Features of Primary Lesions

International Nuclear Information System (INIS)

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

2015-01-01

Purpose: The purpose of this study is to investigate the relationship between computed tomographic (CT) texture features of primary lesions and metastasis-free survival for rectal cancer patients; and to develop a datamining prediction model using texture features. Methods: A total of 220 rectal cancer patients treated with neoadjuvant chemo-radiotherapy (CRT) were enrolled in this study. All patients underwent CT scans before CRT. The primary lesions on the CT images were delineated by two experienced oncologists. The CT images were filtered by Laplacian of Gaussian (LoG) filters with different filter values (1.0–2.5: from fine to coarse). Both filtered and unfiltered images were analyzed using Gray-level Co-occurrence Matrix (GLCM) texture analysis with different directions (transversal, sagittal, and coronal). Totally, 270 texture features with different species, directions and filter values were extracted. Texture features were examined with Student’s t-test for selecting predictive features. Principal Component Analysis (PCA) was performed upon the selected features to reduce the feature collinearity. Artificial neural network (ANN) and logistic regression were applied to establish metastasis prediction models. Results: Forty-six of 220 patients developed metastasis with a follow-up time of more than 2 years. Sixtyseven texture features were significantly different in t-test (p<0.05) between patients with and without metastasis, and 12 of them were extremely significant (p<0.001). The Area-under-the-curve (AUC) of ANN was 0.72, and the concordance index (CI) of logistic regression was 0.71. The predictability of ANN was slightly better than logistic regression. Conclusion: CT texture features of primary lesions are related to metastasisfree survival of rectal cancer patients. Both ANN and logistic regression based models can be developed for prediction

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.

Development and validation of risk prediction equations to estimate survival in patients with colorectal cancer: cohort study

OpenAIRE

Hippisley-Cox, Julia; Coupland, Carol

2017-01-01

Objective: To develop and externally validate risk prediction equations to estimate absolute and conditional survival in patients with colorectal cancer. \\ud \\ud Design: Cohort study.\\ud \\ud Setting: General practices in England providing data for the QResearch database linked to the national cancer registry.\\ud \\ud Participants: 44 145 patients aged 15-99 with colorectal cancer from 947 practices to derive the equations. The equations were validated in 15 214 patients with colorectal cancer ...

A New Clinicobiological Scoring System for the Prediction of Infection-Related Mortality and Survival after Allogeneic Hematopoietic Stem Cell Transplantation.

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Forcina, Alessandra; Rancoita, Paola M V; Marcatti, Magda; Greco, Raffaella; Lupo-Stanghellini, Maria Teresa; Carrabba, Matteo; Marasco, Vincenzo; Di Serio, Clelia; Bernardi, Massimo; Peccatori, Jacopo; Corti, Consuelo; Bondanza, Attilio; Ciceri, Fabio

2017-12-01

Infection-related mortality (IRM) is a substantial component of nonrelapse mortality (NRM) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). No scores have been developed to predict IRM before transplantation. Pretransplantation clinical and biochemical data were collected from a study cohort of 607 adult patients undergoing allo-HSCT between January 2009 and February 2017. In a training set of 273 patients, multivariate analysis revealed that age >60 years (P = .003), cytomegalovirus host/donor serostatus different from negative/negative (P < .001), pretransplantation IgA level <1.11 g/L (P = .004), and pretransplantation IgM level <.305 g/L (P = .028) were independent predictors of increased IRM. Based on these results, we developed and subsequently validated a 3-tiered weighted prognostic index for IRM in a retrospective set of patients (n = 219) and a prospective set of patients (n = 115). Patients were assigned to 3 different IRM risk classes based on this index score. The score significantly predicted IRM in the training set, retrospective validation set, and prospective validation set (P < .001, .044, and .011, respectively). In the training set, 100-day IRM was 5% for the low-risk group, 11% for the intermediate-riak group, and 16% for the high-risk groups. In the retrospective validation set, the respective 100-day IRM values were 7%, 17%, and 28%, and in the prospective set, they were 0%, 5%, and 7%. This score predicted also overall survival (P < .001 in the training set, P < 041 in the retrospective validation set, and P < .023 in the prospective validation set). Because pretransplantation levels of IgA/IgM can be modulated by the supplementation of enriched immunoglobulins, these results suggest the possibility of prophylactic interventional studies to improve transplantation outcomes. Copyright © 2017 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All

Fuselage Burnthrough Protection for Increased Postcrash Occupant Survivability: Safety Benefit Analysis Based on Past Accidents

National Research Council Canada - National Science Library

Cherry, Ray

1999-01-01

.... The methodology gives a reasonable assessment of the tolerance on the predicted levels. Fire hardening of fuselages will provide benefits in terms of enhanced occupant survival and may be found to be cost beneficial if low-cost solutions can be found...

Prognostic value of CT findings to predict survival outcomes in patients with pancreatic neuroendocrine neoplasms: a single institutional study of 161 patients

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Kim, Dong Wook; Kim, Hyoung Jung; Kim, Kyung Won; Byun, Jae Ho; Kim, So Yeon [University of Ulsan College of Medicine, Department of Radiology and Research Institute of Radiology, Asan Medical Center, Seoul (Korea, Republic of); Song, Ki Byung [University of Ulsan College of Medicine, Department of Surgery, Asan Medical Center, Seoul (Korea, Republic of); Ramaiya, Nikhil H.; Tirumani, Sree Harsha [Harvard Medical School, Department of Imaging, Dana-Farber Cancer Institute, Brigham and Women' s Hospital, Boston, MA (United States); Hong, Seung-Mo [University of Ulsan College of Medicine, Department of Pathology, Asan Medical Center, Seoul (Korea, Republic of)

2016-05-15

To evaluate the prognostic value of CT to predict recurrence-free and overall survival in patients with pancreatic neuroendocrine neoplasms (PanNENs). Between January 2004 and December 2012, 161 consecutive patients who underwent preoperative triphasic CT and surgical resection with curative intent for PanNENs were identified. The tumour consistency, margin, presence of calcification, pancreatic duct dilatation, bile duct dilatation, vascular invasion, and hepatic metastases were evaluated. The tumour size, arterial enhancement ratio, and portal enhancement ratio were measured. The Cox proportional hazard model was used to determine the association between CT features and recurrence-free survival and overall survival. By multivariate analysis, tumour size (>3 cm) (hazard ratio, 3.314; p = 0.006), portal enhancement ratio (≤1.1) (hazard ratio, 2.718; p = 0.006), and hepatic metastases (hazard ratio, 4.374; p = 0.003) were independent significant variables for worse recurrence-free survival. Portal enhancement ratio (≤1.1) (hazard ratio, 5.951; p = 0.001) and hepatic metastases (hazard ratio, 4.122; p = 0.021) were independent significant variables for worse overall survival. Portal enhancement ratio (≤1.1) and hepatic metastases assessed on CT were common independent prognostic factors for worse recurrence-free survival and overall survival in patients with PanNENs. (orig.)

Prognostic value of CT findings to predict survival outcomes in patients with pancreatic neuroendocrine neoplasms: a single institutional study of 161 patients

International Nuclear Information System (INIS)

Kim, Dong Wook; Kim, Hyoung Jung; Kim, Kyung Won; Byun, Jae Ho; Kim, So Yeon; Song, Ki Byung; Ramaiya, Nikhil H.; Tirumani, Sree Harsha; Hong, Seung-Mo

2016-01-01

To evaluate the prognostic value of CT to predict recurrence-free and overall survival in patients with pancreatic neuroendocrine neoplasms (PanNENs). Between January 2004 and December 2012, 161 consecutive patients who underwent preoperative triphasic CT and surgical resection with curative intent for PanNENs were identified. The tumour consistency, margin, presence of calcification, pancreatic duct dilatation, bile duct dilatation, vascular invasion, and hepatic metastases were evaluated. The tumour size, arterial enhancement ratio, and portal enhancement ratio were measured. The Cox proportional hazard model was used to determine the association between CT features and recurrence-free survival and overall survival. By multivariate analysis, tumour size (>3 cm) (hazard ratio, 3.314; p = 0.006), portal enhancement ratio (≤1.1) (hazard ratio, 2.718; p = 0.006), and hepatic metastases (hazard ratio, 4.374; p = 0.003) were independent significant variables for worse recurrence-free survival. Portal enhancement ratio (≤1.1) (hazard ratio, 5.951; p = 0.001) and hepatic metastases (hazard ratio, 4.122; p = 0.021) were independent significant variables for worse overall survival. Portal enhancement ratio (≤1.1) and hepatic metastases assessed on CT were common independent prognostic factors for worse recurrence-free survival and overall survival in patients with PanNENs. (orig.)

On the increase of predictive performance with high-level data fusion

International Nuclear Information System (INIS)

Doeswijk, T.G.; Smilde, A.K.; Hageman, J.A.; Westerhuis, J.A.; Eeuwijk, F.A. van

2011-01-01

The combination of the different data sources for classification purposes, also called data fusion, can be done at different levels: low-level, i.e. concatenating data matrices, medium-level, i.e. concatenating data matrices after feature selection and high-level, i.e. combining model outputs. In this paper the predictive performance of high-level data fusion is investigated. Partial least squares is used on each of the data sets and dummy variables representing the classes are used as response variables. Based on the estimated responses y-hat j for data set j and class k, a Gaussian distribution p(g k |y-hat j ) is fitted. A simulation study is performed that shows the theoretical performance of high-level data fusion for two classes and two data sets. Within group correlations of the predicted responses of the two models and differences between the predictive ability of each of the separate models and the fused models are studied. Results show that the error rate is always less than or equal to the best performing subset and can theoretically approach zero. Negative within group correlations always improve the predictive performance. However, if the data sets have a joint basis, as with metabolomics data, this is not likely to happen. For equally performing individual classifiers the best results are expected for small within group correlations. Fusion of a non-predictive classifier with a classifier that exhibits discriminative ability lead to increased predictive performance if the within group correlations are strong. An example with real life data shows the applicability of the simulation results.

Can venous ProBNP levels predict placenta accreta?

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Ersoy, Ali Ozgur; Oztas, Efser; Ozler, Sibel; Ersoy, Ebru; Erkenekli, Kudret; Uygur, Dilek; Caglar, Ali Turhan; Danisman, Nuri

2016-12-01

Placenta previa (PP) is a potential life-threatening pregnancy complication. Pro-brain natriuretic peptide (ProBNP), creatine kinase (CK), cardiac form of CK (CK-MB) and Troponin I are circulatory biomarkers related to cardiac functions. We aimed to determine whether these biomarkers are related to PP and placenta accreta. In this case-control study, fifty-four pregnant women who attended our tertiary care center for perinatology with the diagnosis of PP totalis, and of them, 14 patients with placenta accreta were recruited as the study groups. Forty-six uncomplicated control patients who were matched for age, BMI were also included. Maternal venous ProBNP, CK, CK-MB and Troponin I levels were compared between the three groups. Obstetric history characteristics were comparable among groups, generally. CK and CK-MB levels were similar among three groups. Troponin I levels in the previa and accreta groups were significantly higher than the controls. ProBNP levels in the accreta group were significantly higher than other two groups. The multivariate regression model revealed that ProBNP could predict placental adhesion anomalies. Troponin I and ProBNP levels in PP cases were higher than controls and ProBNP could predict placenta accreta.

Anti-Inflammatory (IL-10 Levels and Affects the Survival of Prostate Carcinoma Patients: An Explorative Study in North Indian Population

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Shailendra Dwivedi

2014-01-01

Full Text Available Objective. Inflammation is an important hallmark of all cancers and net inflammatory response is determined by a delicate balance between pro- and anti-inflammatory cytokines, which may be affected by tobacco exposure, so the present study was designed to explore the effect of various modes of tobacco exposure on interleukin-12 (IL-12 and interleukin-10 (IL-10 inflammatory cytokine levels and survival in prostate carcinoma (PCa patients. Methods. 285 cancer patients and equal controls with 94 BPH (benign prostatic hyperplasia were recruited; baseline levels of serum IL-12 and IL-10 were measured and analyzed in various tobacco exposed groups by appropriate statistical tool. Five-year survivals of patients were analyzed by Log-rank (Mantel-Cox test (graph pad version 5. Results. The expression of serum proinflammatory (IL-12 and anti-inflammatory (IL-10 cytokines was correlated with tobacco exposed group as smokers, chewers, and alcohol users have shown significantly higher levels (P<0.001 with significantly lower median survivals (27.1 months, standard error = 2.86, and 95% CI: 21.4–32.62; than nonusers. Stages III and IV of tobacco addicted patients have also shown significantly increased levels of IL-12 and IL-10. Conclusions. IL-12 and IL-10 seem to be affected by various modes of tobacco exposure and inflammation also affects median survival of cancer patients.

N0/N1, PNL, or LNR? The effect of lymph node number on accurate survival prediction in pancreatic ductal adenocarcinoma.

Science.gov (United States)

Valsangkar, Nakul P; Bush, Devon M; Michaelson, James S; Ferrone, Cristina R; Wargo, Jennifer A; Lillemoe, Keith D; Fernández-del Castillo, Carlos; Warshaw, Andrew L; Thayer, Sarah P

2013-02-01

We evaluated the prognostic accuracy of LN variables (N0/N1), numbers of positive lymph nodes (PLN), and lymph node ratio (LNR) in the context of the total number of examined lymph nodes (ELN). Patients from SEER and a single institution (MGH) were reviewed and survival analyses performed in subgroups based on numbers of ELN to calculate excess risk of death (hazard ratio, HR). In SEER and MGH, higher numbers of ELN improved the overall survival for N0 patients. The prognostic significance (N0/N1) and PLN were too variable as the importance of a single PLN depended on the total number of LN dissected. LNR consistently correlated with survival once a certain number of lymph nodes were dissected (≥13 in SEER and ≥17 in the MGH dataset). Better survival for N0 patients with increasing ELN likely represents improved staging. PLN have some predictive value but the ELN strongly influence their impact on survival, suggesting the need for a ratio-based classification. LNR strongly correlates with outcome provided that a certain number of lymph nodes is evaluated, suggesting that the prognostic accuracy of any LN variable depends on the total number of ELN.

Somatic mutation load of estrogen receptor-positive breast tumors predicts overall survival: an analysis of genome sequence data.

Science.gov (United States)

Haricharan, Svasti; Bainbridge, Matthew N; Scheet, Paul; Brown, Powel H

2014-07-01

Breast cancer is one of the most commonly diagnosed cancers in women. While there are several effective therapies for breast cancer and important single gene prognostic/predictive markers, more than 40,000 women die from this disease every year. The increasing availability of large-scale genomic datasets provides opportunities for identifying factors that influence breast cancer survival in smaller, well-defined subsets. The purpose of this study was to investigate the genomic landscape of various breast cancer subtypes and its potential associations with clinical outcomes. We used statistical analysis of sequence data generated by the Cancer Genome Atlas initiative including somatic mutation load (SML) analysis, Kaplan-Meier survival curves, gene mutational frequency, and mutational enrichment evaluation to study the genomic landscape of breast cancer. We show that ER(+), but not ER(-), tumors with high SML associate with poor overall survival (HR = 2.02). Further, these high mutation load tumors are enriched for coincident mutations in both DNA damage repair and ER signature genes. While it is known that somatic mutations in specific genes affect breast cancer survival, this study is the first to identify that SML may constitute an important global signature for a subset of ER(+) tumors prone to high mortality. Moreover, although somatic mutations in individual DNA damage genes affect clinical outcome, our results indicate that coincident mutations in DNA damage response and signature ER genes may prove more informative for ER(+) breast cancer survival. Next generation sequencing may prove an essential tool for identifying pathways underlying poor outcomes and for tailoring therapeutic strategies.

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.

Early diffusion weighted magnetic resonance imaging can predict survival in women with locally advanced cancer of the cervix treated with combined chemo-radiation

International Nuclear Information System (INIS)

Somoye, Gbolahan; Parkin, David; Harry, Vanessa; Semple, Scott; Plataniotis, George; Scott, Neil; Gilbert, Fiona J.

2012-01-01

To assess the predictive value of diffusion weighted imaging (DWI) for survival in women treated for advanced cancer of the cervix with concurrent chemo-radiotherapy. Twenty women treated for advanced cancer of the cervix were recruited and followed up for a median of 26 (range -3 /mm 2 /s), respectively, P = 0.02. The median change in ADC 14 days after treatment commencement was significantly higher in the alive group compared to non-survivors, 0.28 and 0.14 (x 10 -3 /mm 2 /s), respectively, P = 0.02. There was no evidence of a difference between survivors and non-survivors for pretreatment baseline or post-therapy ADC values. Functional DWI early in the treatment of advanced cancer of the cervix may provide useful information in predicting survival. (orig.)

Method for Assigning Priority Levels in Acute Care (MAPLe-AC predicts outcomes of acute hospital care of older persons - a cross-national validation

Directory of Open Access Journals (Sweden)

Ljunggren Gunnar

2011-06-01

Full Text Available Abstract Background Although numerous risk factors for adverse outcomes for older persons after an acute hospital stay have been identified, a decision making tool combining all available information in a clinically meaningful way would be helpful for daily hospital practice. The purpose of this study was to evaluate the ability of the Method for Assigning Priority Levels for Acute Care (MAPLe-AC to predict adverse outcomes in acute care for older people and to assess its usability as a decision making tool for discharge planning. Methods Data from a prospective multicenter study in five Nordic acute care hospitals with information from admission to a one year follow-up of older acute care patients were compared with a prospective study of acute care patients from admission to discharge in eight hospitals in Canada. The interRAI Acute Care assessment instrument (v1.1 was used for data collection. Data were collected during the first 24 hours in hospital, including pre-morbid and admission information, and at day 7 or at discharge, whichever came first. Based on this information a crosswalk was developed from the original MAPLe algorithm for home care settings to acute care (MAPLe-AC. The sample included persons 75 years or older who were admitted to acute internal medical services in one hospital in each of the five Nordic countries (n = 763 or to acute hospital care either internal medical or combined medical-surgical services in eight hospitals in Ontario, Canada (n = 393. The outcome measures considered were discharge to home, discharge to institution or death. Outcomes in a 1-year follow-up in the Nordic hospitals were: living at home, living in an institution or death, and survival. Logistic regression with ROC curves and Cox regression analyses were used in the analyses. Results Low and mild priority levels of MAPLe-AC predicted discharge home and high and very high priority levels predicted adverse outcome at discharge both in the Nordic

Prediction of blast vibration level considered propagation characteristics; Denpa tokusei to koryoshita happa shindo level no yosoku

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Kunimatsu, S; Jinguji, M [National Institute for Resources and Environment, Tsukuba (Japan); Yamada, M; Hirai, T [Newjec Inc., Osaka (Japan); Durucan, S; Farsangi, M

1997-10-22

With an objective to assess environmental influence induced by blast vibration, a study has been carried out on a method to predict vibration levels. The study has discussed a method to calculate vibration levels, in which vibration propagating characteristics are sought on blast vibration generated from an open-cut limestone mine from acceleration waveforms in the vicinity of the blast source and residential housings by using an octave analysis, and waveforms are predicted. The shortest straight line distance from the blast position to a housing is about 150 m, and the height difference is about 30 to 40 meters. The measuring instruments include a vibration level meter used for pollution measurement and a data recorder, with signals lower than 1 Hz and higher than 90 Hz being interrupted. The environmental influence assessment discusses not only the maximum value of the vibration level, but also sizes of values of each band by using a frequency analysis. The result of the discussions revealed that the prediction of the vibration levels is little affected by phase characteristics, and that no problems are caused in the measurement accuracy even if the vibration levels are predicted by using relative decay amount according to a one-third octave analysis for the propagation characteristics. 5 figs., 4 tabs.

Circulating microRNAs in relation to EGFR status and survival of lung adenocarcinoma in female non-smokers.

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Huan Zhang

Full Text Available OBJECTIVES: Lung adenocarcinoma is considered a unique disease for Asian female non-smokers. We investigated whether plasma microRNA (miRNA expression profiles are different by the EGFR status and are associated with survival outcomes of the patients. METHODS: Using real-time RT-PCR, we analyzed the expression of 20 miRNAs in the plasma of 105 female patients with lung adenocarcinoma. Kaplan-Meier survival analysis and Cox proportional hazards regression were performed to determine the association between miRNA expression and overall survival. Time dependent receiver operating characteristic (ROC analysis was also performed. RESULTS: In the 20 miRNAs, miR-122 were found differently expressed between wild and mutant EGFR carriers (P=0.018. Advanced disease stage and tumor metastasis were independently associated with poor prognosis of patients with lung adenocarcinoma (P=0.010 and 1.0×10(-4. Plasma levels of miR-195 and miR-122 expression were also associated with overall survival in the patients, especially in those with advanced stage (HR=0.23, 95%CI:0.07-0.84; and HR=0.22, 95%CI:0.06-0.77 and EGFR mutation (HR=0.27, 95%CI:0.08-0.96; and HR=0.23, 95%CI=0.06-0.81. Moreover, a model including miR-195, miR-122 may predict survival outcomes of female patients with lung adenocarcinoma (AUC=0.707. CONCLUSIONS: Circulating miR-195 and miR-122 may have prognostic values in predicting the overall survival as well as predicting EGFR mutation status in non-smoking female patients with lung adenocarcinoma. Measuring plasma levels of miR-195 and miR-122 may especially be useful in EGFR mutant patients with lung adenocarcinoma.

Spatial predictions at the community level

DEFF Research Database (Denmark)

D'Amen, Manuela; Rahbek, Carsten; Zimmermann, Niklaus E.

2017-01-01

of communities, with a particular focus on species richness, composition, relative abundance and related attributes. We first briefly describe the concepts and theories that span the different drivers of species assembly. A combination of abiotic processes and biotic mechanisms are thought to influence...... the community assembly process. In this review, we describe four categories of drivers: (i) historical and evolutionary, (ii) environmental, (iii) biotic, and (iv) stochastic. We discuss the different modelling approaches proposed or applied at the community level and examine them from different standpoints, i......A fundamental goal of ecological research is to understand and model how processes generate patterns so that if conditions change, changes in the patterns can be predicted. Different approaches have been proposed for modelling species assemblage, but their use to predict spatial patterns of species...

Survival and cardiovascular events after coarctation-repair in long-term follow-up (COAFU): Predictive value of clinical variables.

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Bambul Heck, P; Pabst von Ohain, J; Kaemmerer, H; Ewert, P; Hager, A

2017-02-01

Long-term sequelae and events after coarctation repair are well described. However, the predictive value of variables from clinical follow-up investigation for late events and survival has rarely been investigated. All patients who participated in the prospective cross-sectional COALA Study in 2000 with a structural clinical investigation including blood pressure measurement and symptom-limited exercise test were contacted for reevaluation of survival, current clinical status and major cardiovascular events. Of 273 eligible patients, 209 were available for follow-up. Nine patients had died at a median age of 46years (range 30-64years), five of them due to cardiovascular complications. Late mortality after surgical intervention was 5.7% with a median age of 41years (range 16-64years). Twenty-five patients had a major cardiovascular event: 12 had procedures at the aortic valve or aortic arch, 8 had procedures for restenosis, 2 had endocarditis, 2 had a cerebrovascular insult and 1 an aortic dissection. The presence of bicuspid aortic valve (p=0.009), brachial-ankle blood pressure gradient >20mmHg (p<0.001) and reduced left ventricular function (p=0.002) correlated with major cardiovascular events. Surgical correction of coarctation of the aorta shows fairly low mortality in the long-term follow-up. Late morbidities include recoarctation, but also the consequences of the hemodynamics produced by a congenital bicuspid aortic valve, presence of which is predictive for aortic valve procedures: however the predictive value of clinical variables is limited. Copyright © 2016. Published by Elsevier Ireland Ltd.

Efficacy of Various Scoring Systems for Predicting the 28-Day Survival Rate among Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease Requiring Emergency Intensive Care

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Zhihong Feng

2017-01-01

Full Text Available We aimed to investigate the efficacy of four severity-of-disease scoring systems in predicting the 28-day survival rate among patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD requiring emergency care. Clinical data of patients with AECOPD who required emergency care were recorded over 2 years. APACHE II, SAPS II, SOFA, and MEDS scores were calculated from severity-of-disease indicators recorded at admission and compared between patients who died within 28 days of admission (death group; 46 patients and those who did not (survival group; 336 patients. Compared to the survival group, the death group had a significantly higher GCS score, frequency of comorbidities including hypertension and heart failure, and age (P<0.05 for all. With all four systems, scores of age, gender, renal inadequacy, hypertension, coronary heart disease, heart failure, arrhythmia, anemia, fracture leading to bedridden status, tumor, and the GCS were significantly higher in the death group than the survival group. The prediction efficacy of the APACHE II and SAPS II scores was 88.4%. The survival rates did not differ significantly between APACHE II and SAPS II (P=1.519. Our results may guide triage for early identification of critically ill patients with AECOPD in the emergency department.

Preoperative prognostic nutritional index and nomogram predicting recurrence-free survival in patients with primary non-muscle-invasive bladder cancer without carcinoma in situ

Directory of Open Access Journals (Sweden)

Cui J

2017-11-01

Full Text Available Jianfeng Cui,1,* Shouzhen Chen,1,* Qiyu Bo,2 Shiyu Wang,1 Ning Zhang,1 Meng Yu,1 Wenfu Wang,1 Jie Han,3 Yaofeng Zhu,1 Benkang Shi1 1Department of Urology, 2Department of First Operating Room, Qilu Hospital of Shandong University, 3Department of Radiation Oncology, Shandong Cancer Hospital and Institute Affiliated to Shandong University, Jinan, People’s Republic of China *These authors contributed equally to this work Background and objectives: Among the cancers of the urogenital system, bladder cancer is ranked second both in incidence and mortality, and hence, a more accurate estimate of the prognosis for individual patients with non-muscle-invasive bladder cancer (NMIBC is urgently needed. Prognostic nutritional index (PNI which is based on serum albumin levels and peripheral lymphocyte count has been confirmed to have prognostic value in various cancers. The aim of this study was to clarify the prognostic value of PNI in patients with NMIBC.Methods: Data of 329 patients with NMIBC were evaluated retrospectively. Recurrence-free survival (RFS was assessed using the Kaplan–Meier method, and the equivalences of survival curves were tested by log-rank tests. The univariate and multivariate analyses were performed using the Cox proportional hazards regression model. Discrimination of the nomogram was measured by the concordance index. A p-value of <0.05 was considered statistically significant.Results: In univariate analysis, age, tumor focality, tumor size, tumor grade, pathological T stage and preoperative PNI were significantly associated with RFS. Multivariate analysis identified PNI as an independent predictor of RFS in patients with NMIBC. According to these independent predictors, a nomogram for the prediction of recurrence was developed.Conclusion: PNI can be regarded as an independent prognostic factor for predicting RFS in NMIBC. The nomogram could be useful to improve personalized therapy for patients with NMIBC. Keywords: non

Value of {sup 18}F-fluorodeoxyglucose uptake in positron emission tomography/computed tomography in predicting survival in multiple myeloma

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Haznedar, Rauf; Aki, Sahika Z.; Oezkurt, Zuebeyde N.; Yagci, Muenci; Sucak, Gulsan T. [Gazi University Faculty of Medicine, Department of Hematology, Ankara (Turkey); Akdemir, Oezguer U. [Gazi University Faculty of Medicine, Department of Nuclear Medicine, Ankara (Turkey); Ceneli, Oezcan [Kirikkale University Sueleyman Demirel Hospital, Department of Hematology, Kirikkale (Turkey); Uenlue, Mustafa [Gazi University Faculty of Medicine, Department of Nuclear Medicine, Ankara (Turkey); Gazi University Faculty of Medicine, Ankara (Turkey)

2011-06-15

We assessed the role of the maximum standardized uptake value (SUV{sub max}) of bone marrow and the extramedullary lesion with the highest SUV{sub max} in positron emission tomography/computed tomography (PET/CT) of newly diagnosed multiple myeloma (MM) patients in predicting overall survival (OS). A total of 61 newly diagnosed patients (55 MM and 6 plasmacytoma) were enrolled in the study [37 men and 24 women with a median age of 57 years (range 28-80 years)]. The SUV{sub max} of bone marrow and the extramedullary lesion in PET/CT was correlated with the levels of {beta}{sub 2}-microglobulin, C-reactive protein (CRP), albumin, creatinine, per cent of bone marrow plasma cells, serum free light chain (FLC) ratio, International Staging System (ISS) score and Durie-Salmon stage. The extramedullary lesion with the highest SUV{sub max} showed significant correlation with bone marrow fluorodeoxyglucose (FDG) uptake (p = 0.027) and near significant correlation with ISS (p = 0.048). Bone marrow SUV{sub max} correlated significantly with the per cent of bone marrow plasma cell count (p = 0.024), CRP (p = 0.012) and ISS (p = 0.013). In stage III MM the mean values of SUV{sub max} in extramedullary lesions were significantly higher than stages I and II (6.23 {+-} 6.32 vs 2.85 {+-} 3.44, p = 0.023). The serum FLC ratio did not show any correlation with SUV{sub max} of lesions and bone marrow (p > 0.05). Forty-four MM patients with FDG-positive lesions in PET/CT showed inferior 5-year estimated survival (61.73%) when compared to 11 patients without FDG-positive lesions, all of whom were alive (p = 0.01). In multivariate analysis an extramedullary lesion with the highest SUV{sub max} was the only independent predictor of OS (p = 0.03). PET/CT allows identification of high-risk myeloma patients, and extramedullary lesions with the highest SUV{sub max} independently predict inferior OS. (orig.)

Fasting Lipoprotein Lipase Protein Levels Can Predict a Postmeal Increment of Triglyceride Levels in Fasting Normohypertriglyceridemic Subjects.

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Tsuzaki, Kokoro; Kotani, Kazuhiko; Yamada, Kazunori; Sakane, Naoki

2016-09-01

Although a postprandial increment in triglyceride (TG) levels is considered to be a risk factor for atherogenesis, tests (e.g., fat load) to assess postprandial changes in TG levels cannot be easily applied to clinical practice. Therefore, fasting markers that predict postprandial TG states are needed to be developed. One current candidate is lipoprotein lipase (LPL) protein, a molecule that hydrides TGs. This study investigated whether fasting LPL levels could predict postprandial TG levels. A total of 17 subjects (11 men, 6 women, mean age 52 ± 11 years) with normotriglyceridemia during fasting underwent the meal test. Several fasting parameters, including LPL, were measured for the area under the curve of postprandial TGs (AUC-TG). The subjects' mean fasting TG level was 1.30 mmol/l, and their mean LPL level was 41.6 ng/ml. The subjects' TG levels increased after loading (they peaked after two postprandial hours). Stepwise multiple regression analysis demonstrated that fasting TG levels were a predictor of the AUC-TG. In addition, fasting LPL mass levels were found to be a predictor of the AUC-TG (β = 0.65, P fasting TG levels. Fasting LPL levels may be useful to predict postprandial TG increment in this population. © 2015 Wiley Periodicals, Inc.

Does Prison Crowding Predict Higher Rates of Substance Use Related Parole Violations? A Recurrent Events Multi-Level Survival Analysis.

Science.gov (United States)

Ruderman, Michael A; Wilson, Deirdra F; Reid, Savanna

2015-01-01

This administrative data-linkage cohort study examines the association between prison crowding and the rate of post-release parole violations in a random sample of prisoners released with parole conditions in California, for an observation period of two years (January 2003 through December 2004). Crowding overextends prison resources needed to adequately protect inmates and provide drug rehabilitation services. Violence and lack of access to treatment are known risk factors for drug use and substance use disorders. These and other psychosocial effects of crowding may lead to higher rates of recidivism in California parolees. Rates of parole violation for parolees exposed to high and medium levels of prison crowding were compared to parolees with low prison crowding exposure. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using a Cox model for recurrent events. Our dataset included 13070 parolees in California, combining individual level parolee data with aggregate level crowding data for multilevel analysis. Comparing parolees exposed to high crowding with those exposed to low crowding, the effect sizes from greatest to least were absconding violations (HR 3.56 95% CI: 3.05-4.17), drug violations (HR 2.44 95% CI: 2.00-2.98), non-violent violations (HR 2.14 95% CI: 1.73-2.64), violent and serious violations (HR 1.88 95% CI: 1.45-2.43), and technical violations (HR 1.86 95% CI: 1.37-2.53). Prison crowding predicted higher rates of parole violations after release from prison. The effect was magnitude-dependent and particularly strong for drug charges. Further research into whether adverse prison experiences, such as crowding, are associated with recidivism and drug use in particular may be warranted.

Linking Measures of Colony and Individual Honey Bee Health to Survival among Apiaries Exposed to Varying Agricultural Land Use

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Smart, Matthew; Pettis, Jeff; Rice, Nathan; Browning, Zac; Spivak, Marla

2016-01-01

We previously characterized and quantified the influence of land use on survival and productivity of colonies positioned in six apiaries and found that colonies in apiaries surrounded by more land in uncultivated forage experienced greater annual survival, and generally more honey production. Here, detailed metrics of honey bee health were assessed over three years in colonies positioned in the same six apiaries. The colonies were located in North Dakota during the summer months and were transported to California for almond pollination every winter. Our aim was to identify relationships among measures of colony and individual bee health that impacted and predicted overwintering survival of colonies. We tested the hypothesis that colonies in apiaries surrounded by more favorable land use conditions would experience improved health. We modeled colony and individual bee health indices at a critical time point (autumn, prior to overwintering) and related them to eventual spring survival for California almond pollination. Colony measures that predicted overwintering apiary survival included the amount of pollen collected, brood production, and Varroa destructor mite levels. At the individual bee level, expression of vitellogenin, defensin1, and lysozyme2 were important markers of overwinter survival. This study is a novel first step toward identifying pertinent physiological responses in honey bees that result from their positioning near varying landscape features in intensive agricultural environments. PMID:27027871

Linking Measures of Colony and Individual Honey Bee Health to Survival among Apiaries Exposed to Varying Agricultural Land Use.

Science.gov (United States)

Smart, Matthew; Pettis, Jeff; Rice, Nathan; Browning, Zac; Spivak, Marla

2016-01-01

We previously characterized and quantified the influence of land use on survival and productivity of colonies positioned in six apiaries and found that colonies in apiaries surrounded by more land in uncultivated forage experienced greater annual survival, and generally more honey production. Here, detailed metrics of honey bee health were assessed over three years in colonies positioned in the same six apiaries. The colonies were located in North Dakota during the summer months and were transported to California for almond pollination every winter. Our aim was to identify relationships among measures of colony and individual bee health that impacted and predicted overwintering survival of colonies. We tested the hypothesis that colonies in apiaries surrounded by more favorable land use conditions would experience improved health. We modeled colony and individual bee health indices at a critical time point (autumn, prior to overwintering) and related them to eventual spring survival for California almond pollination. Colony measures that predicted overwintering apiary survival included the amount of pollen collected, brood production, and Varroa destructor mite levels. At the individual bee level, expression of vitellogenin, defensin1, and lysozyme2 were important markers of overwinter survival. This study is a novel first step toward identifying pertinent physiological responses in honey bees that result from their positioning near varying landscape features in intensive agricultural environments.

Linking Measures of Colony and Individual Honey Bee Health to Survival among Apiaries Exposed to Varying Agricultural Land Use.

Directory of Open Access Journals (Sweden)

Matthew Smart

Full Text Available We previously characterized and quantified the influence of land use on survival and productivity of colonies positioned in six apiaries and found that colonies in apiaries surrounded by more land in uncultivated forage experienced greater annual survival, and generally more honey production. Here, detailed metrics of honey bee health were assessed over three years in colonies positioned in the same six apiaries. The colonies were located in North Dakota during the summer months and were transported to California for almond pollination every winter. Our aim was to identify relationships among measures of colony and individual bee health that impacted and predicted overwintering survival of colonies. We tested the hypothesis that colonies in apiaries surrounded by more favorable land use conditions would experience improved health. We modeled colony and individual bee health indices at a critical time point (autumn, prior to overwintering and related them to eventual spring survival for California almond pollination. Colony measures that predicted overwintering apiary survival included the amount of pollen collected, brood production, and Varroa destructor mite levels. At the individual bee level, expression of vitellogenin, defensin1, and lysozyme2 were important markers of overwinter survival. This study is a novel first step toward identifying pertinent physiological responses in honey bees that result from their positioning near varying landscape features in intensive agricultural environments.

Impact of tumour volume on prediction of progression-free survival in sinonasal cancer

International Nuclear Information System (INIS)

Hennersdorf, Florian; Mauz, Paul-Stefan; Adam, Patrick; Welz, Stefan; Sievert, Anne; Ernemann, Ulrike; Bisdas, Sotirios

2015-01-01

The present study aimed to analyse potential prognostic factors, with emphasis on tumour volume, in determining progression free survival (PFS) for malignancies of the nasal cavity and the paranasal sinuses. Retrospective analysis of 106 patients with primary sinonasal malignancies treated and followed-up between March 2006 and October 2012. Possible predictive parameters for PFS were entered into univariate and multivariate Cox regression analysis. Kaplan-Meier curve analysis included age, sex, baseline tumour volume (based on MR imaging), histology type, TNM stage and prognostic groups according to the American Joint Committee on Cancer (AJCC) classification. Receiver operating characteristic (ROC) curve analysis concerning the predictive value of tumour volume for recurrence was also conducted. The main histological subgroup consisted of epithelial tumours (77%). The majority of the patients (68%) showed advanced tumour burden (AJCC stage III–IV). Lymph node involvement was present in 18 cases. The mean tumour volume was 26.6 ± 21.2 cm 3 . The median PFS for all patients was 24.9 months (range: 2.5–84.5 months). The ROC curve analysis for the tumour volume showed 58.1% sensitivity and 75.4% specificity for predicting recurrence. Tumour volume, AJCC staging, T- and N- stage were significant predictors in the univariate analysis. Positive lymph node status and tumour volume remained significant and independent predictors in the multivariate analysis. Radiological tumour volume proofed to be a statistically reliable predictor of PFS. In the multivariate analysis, T-, N- and overall AJCC staging did not show significant prognostic value

Deep radiomic prediction with clinical predictors of the survival in patients with rheumatoid arthritis-associated interstitial lung diseases

Science.gov (United States)

Nasirudina, Radin A.; Näppi, Janne J.; Watari, Chinatsu; Matsuhiro, Mikio; Hironaka, Toru; Kido, Shoji; Yoshida, Hiroyuki

2018-02-01

We developed and evaluated the effect of our deep-learning-derived radiomic features, called deep radiomic features (DRFs), together with their combination with clinical predictors, on the prediction of the overall survival of patients with rheumatoid arthritis-associated interstitial lung disease (RA-ILD). We retrospectively identified 70 RA-ILD patients with thin-section lung CT and pulmonary function tests. An experienced observer delineated regions of interest (ROIs) from the lung regions on the CT images, and labeled them into one of four ILD patterns (ground-class opacity, reticulation, consolidation, and honeycombing) or a normal pattern. Small image patches centered at individual pixels on these ROIs were extracted and labeled with the class of the ROI to which the patch belonged. A deep convolutional neural network (DCNN), which consists of a series of convolutional layers for feature extraction and a series of fully connected layers, was trained and validated with 5-fold cross-validation for classifying the image patches into one of the above five patterns. A DRF vector for each patch was identified as the output of the last convolutional layer of the DCNN. Statistical moments of each element of the DRF vectors were computed to derive a DRF vector that characterizes the patient. The DRF vector was subjected to a Cox proportional hazards model with elastic-net penalty for predicting the survival of the patient. Evaluation was performed by use of bootstrapping with 2,000 replications, where concordance index (C-index) was used as a comparative performance metric. Preliminary results on clinical predictors, DRFs, and their combinations thereof showed (a) Gender and Age: C-index 64.8% [95% confidence interval (CI): 51.7, 77.9]; (b) gender, age, and physiology (GAP index): C-index: 78.5% [CI: 70.50 86.51], P < 0.0001 in comparison with (a); (c) DRFs: C-index 85.5% [CI: 73.4, 99.6], P < 0.0001 in comparison with (b); and (d) DRF and GAP: C-index 91.0% [CI: 84

CT texture features of liver parenchyma for predicting development of metastatic disease and overall survival in patients with colorectal cancer.

Science.gov (United States)

Lee, Scott J; Zea, Ryan; Kim, David H; Lubner, Meghan G; Deming, Dustin A; Pickhardt, Perry J

2018-04-01

To determine if identifiable hepatic textural features are present at abdominal CT in patients with colorectal cancer (CRC) prior to the development of CT-detectable hepatic metastases. Four filtration-histogram texture features (standard deviation, skewness, entropy and kurtosis) were extracted from the liver parenchyma on portal venous phase CT images at staging and post-treatment surveillance. Surveillance scans corresponded to the last scan prior to the development of CT-detectable CRC liver metastases in 29 patients (median time interval, 6 months), and these were compared with interval-matched surveillance scans in 60 CRC patients who did not develop liver metastases. Predictive models of liver metastasis-free survival and overall survival were built using regularised Cox proportional hazards regression. Texture features did not significantly differ between cases and controls. For Cox models using all features as predictors, all coefficients were shrunk to zero, suggesting no association between any CT texture features and outcomes. Prognostic indices derived from entropy features at surveillance CT incorrectly classified patients into risk groups for future liver metastases (p < 0.001). On surveillance CT scans immediately prior to the development of CRC liver metastases, we found no evidence suggesting that changes in identifiable hepatic texture features were predictive of their development. • No correlation between liver texture features and metastasis-free survival was observed. • Liver texture features incorrectly classified patients into risk groups for liver metastases. • Standardised texture analysis workflows need to be developed to improve research reproducibility.

Edge Contrast of the FLAIR Hyperintense Region Predicts Survival in Patients with High-Grade Gliomas following Treatment with Bevacizumab.

Science.gov (United States)

Bahrami, N; Piccioni, D; Karunamuni, R; Chang, Y-H; White, N; Delfanti, R; Seibert, T M; Hattangadi-Gluth, J A; Dale, A; Farid, N; McDonald, C R

2018-04-05

Treatment with bevacizumab is standard of care for recurrent high-grade gliomas; however, monitoring response to treatment following bevacizumab remains a challenge. The purpose of this study was to determine whether quantifying the sharpness of the fluid-attenuated inversion recovery hyperintense border using a measure derived from texture analysis-edge contrast-improves the evaluation of response to bevacizumab in patients with high-grade gliomas. MRIs were evaluated in 33 patients with high-grade gliomas before and after the initiation of bevacizumab. Volumes of interest within the FLAIR hyperintense region were segmented. Edge contrast magnitude for each VOI was extracted using gradients of the 3D FLAIR images. Cox proportional hazards models were generated to determine the relationship between edge contrast and progression-free survival/overall survival using age and the extent of surgical resection as covariates. After bevacizumab, lower edge contrast of the FLAIR hyperintense region was associated with poorer progression-free survival ( P = .009) and overall survival ( P = .022) among patients with high-grade gliomas. Kaplan-Meier curves revealed that edge contrast cutoff significantly stratified patients for both progression-free survival (log-rank χ 2 = 8.3, P = .003) and overall survival (log-rank χ 2 = 5.5, P = .019). Texture analysis using edge contrast of the FLAIR hyperintense region may be an important predictive indicator in patients with high-grade gliomas following treatment with bevacizumab. Specifically, low FLAIR edge contrast may partially reflect areas of early tumor infiltration. This study adds to a growing body of literature proposing that quantifying features may be important for determining outcomes in patients with high-grade gliomas. © 2018 by American Journal of Neuroradiology.

Resection of pulmonary metastases from colon and rectal cancer: factors to predict survival differ regarding to the origin of the primary tumor.

Science.gov (United States)

Meimarakis, G; Spelsberg, F; Angele, M; Preissler, G; Fertmann, J; Crispin, A; Reu, S; Kalaitzis, N; Stemmler, M; Giessen, C; Heinemann, V; Stintzing, S; Hatz, R; Winter, H

2014-08-01

The purpose of the present study was to determine differences in prognostic factors for survival of patients with pulmonary metastases resected in curative intent from colon or rectum cancer. Between 1980 and 2006, prognostic factors after resection of pulmonary metastases in 171 patients with primary rectum or colon tumor were evaluated. Survival of patients after surgical metastasectomy was compared with that of patients receiving standard chemotherapy by matched-pair analysis. Median survival after pulmonary resection was 35.2 months (confidence interval 27.3-43.2). One-, 3-, and 5-year survival for patients following R0 resection was 88.8, 52.1, and 32.9 % respectively. Complete metastasectomy (R0), UICC stage of the primary tumor, pleural infiltration, and hilar or mediastinal lymph node metastases are independent prognostic factors for survival. Matched-pair analysis confirmed that pulmonary metastasectomy significantly improved survival. Although no difference in survival for patients with pulmonary metastases from lower rectal compared to upper rectal or colon cancer was observed, factors to predict survival are different for patients with lower and middle rectal cancer (R0, mediastinal and/or hilar lymph nodes, gender, UICC stage) compared with patients with upper rectal or colon cancer (R0, number of metastases). Our results indicate that distinct prognostic factors exist for patients with pulmonary metastases from lower rectal compared with upper rectal or colon cancer. This supports the notion that colorectal cancer should not be considered as a single-tumor entity. Metastasectomy, especially after complete resection resulted in a dramatic improvement of survival compared with patients treated with chemotherapy alone.

Diffusion-weighted magnetic resonance imaging predicts survival in patients with liver-predominant metastatic colorectal cancer shortly after selective internal radiation therapy

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Schmeel, Frederic Carsten; Simon, Birgit; Luetkens, Julian Alexander; Traeber, Frank; Schmeel, Leonard Christopher; Schild, Hans Heinz; Hadizadeh, Dariusch Reza [University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universitaet Bonn, Department of Radiology, Bonn (Germany); Sabet, Amir [University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universitaet Bonn, Department of Nuclear Medicine, Bonn (Germany); University Hospital Essen, Universitaet Duisburg-Essen, Department of Nuclear Medicine, Essen (Germany); Ezziddin, Samer [University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universitaet Bonn, Department of Nuclear Medicine, Bonn (Germany); University Hospital Saarland, Universitaet des Saarlandes, Department of Nuclear Medicine, Homburg (Germany)

2017-03-15

To investigate whether quantifications of apparent diffusion coefficient (ADC) on diffusion-weighted imaging (DWI) can predict overall survival (OS) in patients with liver-predominant metastatic colorectal cancer (CRC) following selective internal radiation therapy with {sup 90}Yttrium-microspheres (SIRT). Forty-four patients underwent DWI 19 ± 16 days before and 36 ± 10 days after SIRT. Tumour-size and intratumoral minimal ADC (minADC) values were measured for 132 liver metastases on baseline and follow-up DWI. Optimal functional imaging response to treatment was determined by receiver operating characteristics and defined as ≥22 % increase in post-therapeutic minADC. Survival analysis was performed with the Kaplan-Meier method and Cox-regression comparing various variables with potential impact on OS. Median OS was 8 months. The following parameters were significantly associated with median OS: optimal functional imaging response (18 vs. 5 months; p < 0.001), hepatic tumour burden <50 % (8 vs. 5 months; p = 0.018), Eastern Cooperative Oncology Group performance scale <1 (10 vs. 4 months; p = 0.012) and progressive disease according to Response and Evaluation Criteria in Solid Tumours (8 vs. 3 months; p = 0.001). On multivariate analysis, optimal functional imaging response and hepatic tumour burden remained independent predictors of OS. Functional imaging response assessment using minADC changes on DWI may predict survival in CRC shortly after SIRT. (orig.)

Sarcopenia predicts survival outcomes among patients with urothelial carcinoma of the upper urinary tract undergoing radical nephroureterectomy: a retrospective multi-institution study.

Science.gov (United States)

Ishihara, Hiroki; Kondo, Tsunenori; Omae, Kenji; Takagi, Toshio; Iizuka, Junpei; Kobayashi, Hirohito; Hashimoto, Yasunobu; Tanabe, Kazunari

2017-02-01

We aimed to evaluate the effect of sarcopenia, a condition of low muscle mass, on the survival among patients who were undergoing radical nephroureterectomy (RNU) for urothelial carcinoma of the upper urinary tract (UCUT). We retrospectively reviewed consecutive patients with UCUT (cT[any]N0M0) who underwent RNU between 2003 and 2013 at our department and its affiliated institutions. Preoperative computed tomography images were used to calculate each patient's skeletal muscle index, an indicator of whole-body muscle mass. Sarcopenia was defined according to the sex-specific consensus definitions, based on the patient's skeletal muscle and body mass indexes. We analyzed the relapse-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS) after RNU to identify factors that predicted patient survival. A total of 137 patients were included, and 90 patients (65.7 %) were diagnosed with sarcopenia. Compared to the non-sarcopenic patients, the sarcopenic patients had a significant inferior 5-year RFS (48.8 vs. 79.6 %, p = 0.0002), CSS (57.1 vs. 92.6 %, p sarcopenia was an independent predictor of shorter RFS, CSS, and OS (all, p Sarcopenia was an independent predictor of survival among patients with UCUT who were undergoing RNU.

Keratin 17 is overexpressed and predicts poor survival in estrogen receptor-negative/human epidermal growth factor receptor-2-negative breast cancer.

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Merkin, Ross D; Vanner, Elizabeth A; Romeiser, Jamie L; Shroyer, A Laurie W; Escobar-Hoyos, Luisa F; Li, Jinyu; Powers, Robert S; Burke, Stephanie; Shroyer, Kenneth R

2017-04-01

Clinicopathological features of breast cancer have limited accuracy to predict survival. By immunohistochemistry (IHC), keratin 17 (K17) expression has been correlated with triple-negative status (estrogen receptor [ER]/progesterone receptor/human epidermal growth factor receptor-2 [HER2] negative) and decreased survival, but K17 messenger RNA (mRNA) expression has not been evaluated in breast cancer. K17 is a potential prognostic cancer biomarker, targeting p27, and driving cell cycle progression. This study compared K17 protein and mRNA expression to ER/progesterone receptor/HER2 receptor status and event-free survival. K17 IHC was performed on 164 invasive breast cancers and K17 mRNA was evaluated in 1097 breast cancers. The mRNA status of other keratins (16/14/9) was evaluated in 113 ER - /HER2 - ductal carcinomas. IHC demonstrated intense cytoplasmic and membranous K17 localization in myoepithelial cells of benign ducts and lobules and tumor cells of ductal carcinoma in situ. In ductal carcinomas, K17 protein was detected in most triple-negative tumors (28/34, 82%), some non-triple-negative tumors (52/112, 46%), but never in lobular carcinomas (0/15). In ductal carcinomas, high K17 mRNA was associated with reduced 5-year event-free survival in advanced tumor stage (n = 149, hazard ratio [HR] = 3.68, P = .018), and large (n = 73, HR = 3.95, P = .047), triple-negative (n = 103, HR = 2.73, P = .073), and ER - /HER2 - (n = 113, HR = 2.99, P = .049) tumors. There were significant correlations among keratins 17, 16, 14, and 9 mRNA levels suggesting these keratins (all encoded on chromosome 17) could be coordinately expressed in breast cancer. Thus, K17 is expressed in a subset of triple-negative breast cancers, and is a marker of poor prognosis in patients with advanced stage and ER - /HER2 - breast cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

A chip-level modeling approach for rail span collapse and survivability analyses

International Nuclear Information System (INIS)

Marvis, D.G.; Alexander, D.R.; Dinger, G.L.

1989-01-01

A general semiautomated analysis technique has been developed for analyzing rail span collapse and survivability of VLSI microcircuits in high ionizing dose rate radiation environments. Hierarchical macrocell modeling permits analyses at the chip level and interactive graphical postprocessing provides a rapid visualization of voltage, current and power distributions over an entire VLSIC. The technique is demonstrated for a 16k C MOS/SOI SRAM and a CMOS/SOS 8-bit multiplier. The authors also present an efficient method to treat memory arrays as well as a three-dimensional integration technique to compute sapphire photoconduction from the design layout

Low expression of tissue inhibitor of metalloproteinases-1 (TIMP-1) in glioblastoma predicts longer patient survival

DEFF Research Database (Denmark)

Aaberg-Jessen, Charlotte; Christensen, Karina; Offenberg, Hanne Kjær

2009-01-01

In colorectal cancer and breast cancer a high TIMP-1 level has been shown to correlate with a shorter overall patient survival and it has been suggested that TIMP-1 is involved in tumour invasion, proliferation and apoptosis in different types of cancers. TIMP-1 is known to be expressed in glioma...

Insurance and education predict long-term survival after orthotopic heart transplantation in the United States.

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Allen, Jeremiah G; Weiss, Eric S; Arnaoutakis, George J; Russell, Stuart D; Baumgartner, William A; Shah, Ashish S; Conte, John V

2012-01-01

Insurance status and education are known to affect health outcomes. However, their importance in orthotopic heart transplantation (OHT) is unknown. The United Network for Organ Sharing (UNOS) database provides a large cohort of OHT recipients in which to evaluate the effect of insurance and education on survival. UNOS data were retrospectively reviewed to identify adult primary OHT recipients (1997 to 2008). Patients were stratified by insurance at the time of transplantation (private/self-pay, Medicare, Medicaid, and other) and college education. All-cause mortality was examined using multivariable Cox proportional hazard regression incorporating 15 variables. Survival was modeled using the Kaplan-Meier method. Insurance for 20,676 patients was distributed as follows: private insurance/self-pay, 12,298 (59.5%); Medicare, 5,227 (25.3%); Medicaid, 2,320 (11.2%); and "other" insurance, 831 (4.0%). Educational levels were recorded for 15,735 patients (76.1% of cohort): 7,738 (49.2%) had a college degree. During 53 ± 41 months of follow-up, 6,125 patients (29.6%) died (6.7 deaths/100 patient-years). Survival differed by insurance and education. Medicare and Medicaid patients had 8.6% and 10.0% lower 10-year survival, respectively, than private/self-pay patients. College-educated patients had 7.0% higher 10-year survival. On multivariable analysis, college education decreased mortality risk by 11%. Medicare and Medicaid increased mortality risk by 18% and 33%, respectively (p ≤ 0.001). Our study examining insurance and education in a large cohort of OHT patients found that long-term mortality after OHT is higher in Medicare/Medicaid patients and in those without a college education. This study points to potential differences in the care of OHT patients based on education and insurance status. Copyright © 2012 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Does Prison Crowding Predict Higher Rates of Substance Use Related Parole Violations? A Recurrent Events Multi-Level Survival Analysis.

Directory of Open Access Journals (Sweden)

Michael A Ruderman

Full Text Available This administrative data-linkage cohort study examines the association between prison crowding and the rate of post-release parole violations in a random sample of prisoners released with parole conditions in California, for an observation period of two years (January 2003 through December 2004.Crowding overextends prison resources needed to adequately protect inmates and provide drug rehabilitation services. Violence and lack of access to treatment are known risk factors for drug use and substance use disorders. These and other psychosocial effects of crowding may lead to higher rates of recidivism in California parolees.Rates of parole violation for parolees exposed to high and medium levels of prison crowding were compared to parolees with low prison crowding exposure. Hazard ratios (HRs with 95% confidence intervals (CIs were estimated using a Cox model for recurrent events. Our dataset included 13070 parolees in California, combining individual level parolee data with aggregate level crowding data for multilevel analysis.Comparing parolees exposed to high crowding with those exposed to low crowding, the effect sizes from greatest to least were absconding violations (HR 3.56 95% CI: 3.05-4.17, drug violations (HR 2.44 95% CI: 2.00-2.98, non-violent violations (HR 2.14 95% CI: 1.73-2.64, violent and serious violations (HR 1.88 95% CI: 1.45-2.43, and technical violations (HR 1.86 95% CI: 1.37-2.53.Prison crowding predicted higher rates of parole violations after release from prison. The effect was magnitude-dependent and particularly strong for drug charges. Further research into whether adverse prison experiences, such as crowding, are associated with recidivism and drug use in particular may be warranted.

Does Prison Crowding Predict Higher Rates of Substance Use Related Parole Violations? A Recurrent Events Multi-Level Survival Analysis

Science.gov (United States)

Ruderman, Michael A.; Wilson, Deirdra F.; Reid, Savanna

2015-01-01

Objective This administrative data-linkage cohort study examines the association between prison crowding and the rate of post-release parole violations in a random sample of prisoners released with parole conditions in California, for an observation period of two years (January 2003 through December 2004). Background Crowding overextends prison resources needed to adequately protect inmates and provide drug rehabilitation services. Violence and lack of access to treatment are known risk factors for drug use and substance use disorders. These and other psychosocial effects of crowding may lead to higher rates of recidivism in California parolees. Methods Rates of parole violation for parolees exposed to high and medium levels of prison crowding were compared to parolees with low prison crowding exposure. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using a Cox model for recurrent events. Our dataset included 13070 parolees in California, combining individual level parolee data with aggregate level crowding data for multilevel analysis. Results Comparing parolees exposed to high crowding with those exposed to low crowding, the effect sizes from greatest to least were absconding violations (HR 3.56 95% CI: 3.05–4.17), drug violations (HR 2.44 95% CI: 2.00–2.98), non-violent violations (HR 2.14 95% CI: 1.73–2.64), violent and serious violations (HR 1.88 95% CI: 1.45–2.43), and technical violations (HR 1.86 95% CI: 1.37–2.53). Conclusions Prison crowding predicted higher rates of parole violations after release from prison. The effect was magnitude-dependent and particularly strong for drug charges. Further research into whether adverse prison experiences, such as crowding, are associated with recidivism and drug use in particular may be warranted. PMID:26492490

Blood glucose level prediction based on support vector regression using mobile platforms.

Science.gov (United States)

Reymann, Maximilian P; Dorschky, Eva; Groh, Benjamin H; Martindale, Christine; Blank, Peter; Eskofier, Bjoern M

2016-08-01

The correct treatment of diabetes is vital to a patient's health: Staying within defined blood glucose levels prevents dangerous short- and long-term effects on the body. Mobile devices informing patients about their future blood glucose levels could enable them to take counter-measures to prevent hypo or hyper periods. Previous work addressed this challenge by predicting the blood glucose levels using regression models. However, these approaches required a physiological model, representing the human body's response to insulin and glucose intake, or are not directly applicable to mobile platforms (smart phones, tablets). In this paper, we propose an algorithm for mobile platforms to predict blood glucose levels without the need for a physiological model. Using an online software simulator program, we trained a Support Vector Regression (SVR) model and exported the parameter settings to our mobile platform. The prediction accuracy of our mobile platform was evaluated with pre-recorded data of a type 1 diabetes patient. The blood glucose level was predicted with an error of 19 % compared to the true value. Considering the permitted error of commercially used devices of 15 %, our algorithm is the basis for further development of mobile prediction algorithms.

Non-invasive prediction of hematocrit levels by portable visible and near-infrared spectrophotometer.

Science.gov (United States)

Sakudo, Akikazu; Kato, Yukiko Hakariya; Kuratsune, Hirohiko; Ikuta, Kazuyoshi

2009-10-01

After blood donation, in some individuals having polycythemia, dehydration causes anemia. Although the hematocrit (Ht) level is closely related to anemia, the current method of measuring Ht is performed after blood drawing. Furthermore, the monitoring of Ht levels contributes to a healthy life. Therefore, a non-invasive test for Ht is warranted for the safe donation of blood and good quality of life. A non-invasive procedure for the prediction of hematocrit levels was developed on the basis of a chemometric analysis of visible and near-infrared (Vis-NIR) spectra of the thumbs using portable spectrophotometer. Transmittance spectra in the 600- to 1100-nm region from thumbs of Japanese volunteers were subjected to a partial least squares regression (PLSR) analysis and leave-out cross-validation to develop chemometric models for predicting Ht levels. Ht levels of masked samples predicted by this model from Vis-NIR spectra provided a coefficient of determination in prediction of 0.6349 with a standard error of prediction of 3.704% and a detection limit in prediction of 17.14%, indicating that the model is applicable for normal and abnormal value in Ht level. These results suggest portable Vis-NIR spectrophotometer to have potential for the non-invasive measurement of Ht levels with a combination of PLSR analysis.

Heart Rate Recovery After 6-Min Walk Test Predicts Survival in Patients With Idiopathic Pulmonary Fibrosis

Science.gov (United States)

Swigris, Jeffrey J.; Swick, Jeff; Wamboldt, Frederick S.; Sprunger, David; du Bois, Roland; Fischer, Aryeh; Cosgrove, Gregory P.; Frankel, Stephen K.; Fernandez-Perez, Evans R.; Kervitsky, Dolly; Brown, Kevin K.

2009-01-01

Background: In patients with idiopathic pulmonary fibrosis (IPF), our objectives were to identify predictors of abnormal heart rate recovery (HRR) at 1 min after completion of a 6-min walk test (6MWT) [HRR1] and 2 min after completion of a 6MWT (HRR2), and to determine whether abnormal HRR predicts mortality. Methods: From 2003 to 2008, we identified IPF patients who had been evaluated at our center (n = 76) with a pulmonary physiologic examination and the 6MWT. We used logistic regression to identify predictors of abnormal HRR, the product-limit method to compare survival in the sample stratified on HRR, and Cox proportional hazards analysis to estimate the prognostic capability of abnormal HRR. Results: Cutoff values were 13 beats for abnormal HRR1 and 22 beats for HRR2. In a multivariable model, predictors of abnormal HRR1 were diffusing capacity of the lung for carbon monoxide (odds ratio [OR], 0.4 per 10% predicted; 95% confidence interval [CI], 0.2 to 0.7; p = 0.003), change in heart rate from baseline to maximum (OR, 0.9; 95% CI, 0.8 to 0.97; p = 0.01), and having a right ventricular systolic pressure > 35 mm Hg as determined by transthoracic echocardiogram (OR, 12.7; 95% CI, 2.0 to 79.7; p = 0.01). Subjects with an abnormal HRR had significantly worse survival than subjects with a normal HRR (for HRR1, p = 0.0007 [log-rank test]; for HRR2, p = 0.03 [log-rank test]); these results held for the subgroup of 30 subjects without resting pulmonary hypertension (HRR1, p = 0.04 [log-rank test]). Among several candidate variables, abnormal HRR1 appeared to be the most potent predictor of mortality (hazard ratio, 5.2; 95% CI, 1.8 to 15.2; p = 0.004). Conclusion: Abnormal HRR after 6MWT predicts mortality in IPF patients. Research is needed to confirm these findings prospectively and to examine the mechanisms of HRR in IPF patients. PMID:19395579

Modeling time-to-event (survival) data using classification tree analysis.

Science.gov (United States)

Linden, Ariel; Yarnold, Paul R

2017-12-01

Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

Prediction of SO{sub 2} levels using neural networks

Energy Technology Data Exchange (ETDEWEB)

Belen M. Fernandez de Castro; Jose Manuel Prada Sanchez; Wenceslao Gonzalez Manteiga [and others] [University of Santiago de Compostela, Santiago (Spain). Department of Statistics and Operations Research, Faculty of Mathematics

2003-05-01

The paper presents an adaptation of the air pollution control help system in the neighbourhood of a coal-fired power plant in As Pontes (A Coruna, Spain), property of Endesa Generacion S.A., to the European Council Directive 1999/30/CE. This system contains a statistical prediction made half an hour before the measurement, and it helps the staff in the power plant prevent air quality level episodes. The prediction is made using neural network models. This prediction is compared with one made by a semiparametric model. 11 refs., 6 figs., 4 tabs.

Fledgling survival increases with development time and adult survival across north and south temperate zones

Science.gov (United States)

Lloyd, Penn; Martin, Thomas E.

2016-01-01

Slow life histories are characterized by high adult survival and few offspring, which are thought to allow increased investment per offspring to increase juvenile survival. Consistent with this pattern, south temperate zone birds are commonly longer-lived and have fewer young than north temperate zone species. However, comparative analyses of juvenile survival, including during the first few weeks of the post-fledging period when most juvenile mortality occurs, are largely lacking. We combined our measurements of fledgling survival for eight passerines in South Africa with estimates from published studies of 57 north and south temperate zone songbird species to test three predictions: (1) fledgling survival increases with length of development time in the nest; (2) fledgling survival increases with adult survival and reduced brood size controlled for development time; and (3) south temperate zone species, with their higher adult survival and smaller brood sizes, exhibit higher fledgling survival than north temperate zone species controlled for development time. We found that fledgling survival was higher among south temperate zone species and generally increased with development time and adult survival within and between latitudinal regions. Clutch size did not explain additional variation, but was confounded with adult survival. Given the importance of age-specific mortality to life history evolution, understanding the causes of these geographical patterns of mortality is important.

Genetic Programming for Sea Level Predictions in an Island Environment

Directory of Open Access Journals (Sweden)

M.A. Ghorbani

2010-03-01

Full Text Available Accurate predictions of sea-level are important for geodetic applications, navigation, coastal, industrial and tourist activities. In the current work, the Genetic Programming (GP and artificial neural networks (ANNs were applied to forecast half-daily and daily sea-level variations from 12 hours to 5 days ahead. The measurements at the Cocos (Keeling Islands in the Indian Ocean were used for training and testing of the employed artificial intelligence techniques. A comparison was performed of the predictions from the GP model and the ANN simulations. Based on the comparison outcomes, it was found that the Genetic Programming approach can be successfully employed in forecasting of sea level variations.

A nonparametric approach to medical survival data: Uncertainty in the context of risk in mortality analysis

International Nuclear Information System (INIS)

Janurová, Kateřina; Briš, Radim

2014-01-01

Medical survival right-censored data of about 850 patients are evaluated to analyze the uncertainty related to the risk of mortality on one hand and compare two basic surgery techniques in the context of risk of mortality on the other hand. Colorectal data come from patients who underwent colectomy in the University Hospital of Ostrava. Two basic surgery operating techniques are used for the colectomy: either traditional (open) or minimally invasive (laparoscopic). Basic question arising at the colectomy operation is, which type of operation to choose to guarantee longer overall survival time. Two non-parametric approaches have been used to quantify probability of mortality with uncertainties. In fact, complement of the probability to one, i.e. survival function with corresponding confidence levels is calculated and evaluated. First approach considers standard nonparametric estimators resulting from both the Kaplan–Meier estimator of survival function in connection with Greenwood's formula and the Nelson–Aalen estimator of cumulative hazard function including confidence interval for survival function as well. The second innovative approach, represented by Nonparametric Predictive Inference (NPI), uses lower and upper probabilities for quantifying uncertainty and provides a model of predictive survival function instead of the population survival function. The traditional log-rank test on one hand and the nonparametric predictive comparison of two groups of lifetime data on the other hand have been compared to evaluate risk of mortality in the context of mentioned surgery techniques. The size of the difference between two groups of lifetime data has been considered and analyzed as well. Both nonparametric approaches led to the same conclusion, that the minimally invasive operating technique guarantees the patient significantly longer survival time in comparison with the traditional operating technique

Survival chance in papillary thyroid cancer in Hungary: individual survival probability estimation using the Markov method

International Nuclear Information System (INIS)

Esik, Olga; Tusnady, Gabor; Daubner, Kornel; Nemeth, Gyoergy; Fuezy, Marton; Szentirmay, Zoltan

1997-01-01

Purpose: The typically benign, but occasionally rapidly fatal clinical course of papillary thyroid cancer has raised the need for individual survival probability estimation, to tailor the treatment strategy exclusively to a given patient. Materials and methods: A retrospective study was performed on 400 papillary thyroid cancer patients with a median follow-up time of 7.1 years to establish a clinical database for uni- and multivariate analysis of the prognostic factors related to survival (Kaplan-Meier product limit method and Cox regression). For a more precise prognosis estimation, the effect of the most important clinical events were then investigated on the basis of a Markov renewal model. The basic concept of this approach is that each patient has an individual disease course which (besides the initial clinical categories) is affected by special events, e.g. internal covariates (local/regional/distant relapses). On the supposition that these events and the cause-specific death are influenced by the same biological processes, the parameters of transient survival probability characterizing the speed of the course of the disease for each clinical event and their sequence were determined. The individual survival curves for each patient were calculated by using these parameters and the independent significant clinical variables selected from multivariate studies, summation of which resulted in a mean cause-specific survival function valid for the entire group. On the basis of this Markov model, prediction of the cause-specific survival probability is possible for extrastudy cases, if it is supposed that the clinical events occur within new patients in the same manner and with the similar probability as within the study population. Results: The patient's age, a distant metastasis at presentation, the extent of the surgical intervention, the primary tumor size and extent (pT), the external irradiation dosage and the degree of TSH suppression proved to be

Prognostic value of biochemical variables for survival after surgery for metastatic bone disease of the extremities.

Science.gov (United States)

Sørensen, Michala Skovlund; Hovgaard, Thea Bechman; Hindsø, Klaus; Petersen, Michael Mørk

2017-03-01

Prediction of survival in patients having surgery for metastatic bone disease in the extremities (MBDex) has been of interest in more than two decades. Hitherto no consensus on the value of biochemical variables has been achieved. Our purpose was (1) to investigate if standard biochemical variables have independent prognostic value for survival after surgery for MBDex and (2) to identify optimal prognostic cut off values for survival of biochemical variables. In a consecutive cohort of 270 patients having surgery for MBDex, we measured preoperative biochemical variables: hemoglobin, alkaline phosphatase, C-reactive protein and absolute, neutrophil and lymphocyte count. ROC curve analyses were performed to identify optimal cut off levels. Independent prognostic factors for variables were addressed with multiple Cox regression analyses. Optimal cut off levels were identified as: hemoglobin 7.45 mmol/L, absolute lymphocyte count 8.5 × 10 9 /L, neutrophil 5.68 × 10 9 /L, lymphocyte 1.37 × 10 9 /L, C-reactive protein 22.5 mg/L, and alkaline phosphatase 129 U/L. Regression analyses found alkaline phosphatase (HR 2.49) and neutrophil count (HR 2.49) to be independent prognostic factors. We found neutrophil count and alkaline phosphatase to be independent prognostic variables in predicting survival in patients after surgery for MBDex. © 2016 Wiley Periodicals, Inc.

HPV Genotypes Predict Survival Benefits From Concurrent Chemotherapy and Radiation Therapy in Advanced Squamous Cell Carcinoma of the Cervix

International Nuclear Information System (INIS)

Wang, Chun-Chieh; Lai, Chyong-Huey; Huang, Yi-Ting; Chao, Angel; Chou, Hung-Hsueh; Hong, Ji-Hong

2012-01-01

Purpose: To study the prognostic value of human papillomavirus (HPV) genotypes in patients with advanced cervical cancer treated with radiation therapy (RT) alone or concurrent chemoradiation therapy (CCRT). Methods and Materials: Between August 1993 and May 2000, 327 patients with advanced squamous cell carcinoma of the cervix (International Federation of Gynecology and Obstetrics stage III/IVA or stage IIB with positive lymph nodes) were eligible for this study. HPV genotypes were determined using the Easychip® HPV genechip. Outcomes were analyzed using Kaplan-Meier survival analysis and the Cox proportional hazards model. Results: We detected 22 HPV genotypes in 323 (98.8%) patients. The leading 4 types were HPV16, 58, 18, and 33. The 5-year overall and disease-specific survival estimates for the entire cohort were 41.9% and 51.4%, respectively. CCRT improved the 5-year disease-specific survival by an absolute 9.8%, but this was not statistically significant (P=.089). There was a significant improvement in disease-specific survival in the CCRT group for HPV18-positive (60.9% vs 30.4%, P=.019) and HPV58-positive (69.3% vs 48.9%, P=.026) patients compared with the RT alone group. In contrast, the differences in survival with CCRT compared with RT alone in the HPV16-positive and HPV-33 positive subgroups were not statistically significant (P=.86 and P=.53, respectively). An improved disease-specific survival was observed for CCRT treated patients infected with both HPV16 and HPV18, but these differenced also were not statistically significant. Conclusions: The HPV genotype may be a useful predictive factor for the effect of CCRT in patients with advanced squamous cell carcinoma of the cervix. Verifying these results in prospective trials could have an impact on tailoring future treatment based on HPV genotype.

Partner resources and incidence and survival in two major causes of death

Directory of Open Access Journals (Sweden)

Jenny Torssander

2018-04-01

Full Text Available Because people tend to marry social equals – and possibly also because partners affect each other’s health – the social position of one partner is associated with the other partner’s health and mortality. Although this link is fairly well established, the underlying mechanisms are not fully identified. Analyzing disease incidence and survival separately may help us to assess when in the course of the disease a partner’s resources are of most significance. This article addresses the importance of partner’s education, income, employment status, and health for incidence and survival in two major causes of death: cancer and cardiovascular diseases (CVD. Based on a sample of Finnish middle-aged and older couples (around 200,000 individuals we show that a partner’s education is more often connected to incidence than to survival, in particular for CVD. Once ill, any direct effect of partner’s education seems to decline: The survival chances after being hospitalized for cancer or CVD are rather associated with partner’s employment status and/or income level when other individual and partner factors are adjusted for. In addition, a partner’s history of poor health predicted higher CVD incidence and, for women, lower cancer survival. The findings suggest that various partner’s characteristics may have different implications for disease and survival, respectively. A wider focus on social determinants of health at the household level, including partner’s social resources, is needed. Keywords: Marital/cohabiting partners, Education, Income, CVD, Cancer, Survival, Finland

Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.

Science.gov (United States)

Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak

2016-03-01

One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi

A retrospective analysis of survival and prognostic factors after stereotactic radiosurgery for aggressive meningiomas

International Nuclear Information System (INIS)

Ferraro, Daniel J; Zoberi, Imran; Simpson, Joseph R; Jaboin, Jerry J; Funk, Ryan K; Blackett, John William; Ju, Michelle R; DeWees, Todd A; Chicoine, Michael R; Dowling, Joshua L; Rich, Keith M; Drzymala, Robert E

2014-01-01

While most meningiomas are benign, aggressive meningiomas are associated with high levels of recurrence and mortality. A single institution’s Gamma Knife radiosurgical experience with atypical and malignant meningiomas is presented, stratified by the most recent WHO classification. Thirty-one patients with atypical and 4 patients with malignant meningiomas treated with Gamma Knife radiosurgery between July 2000 and July 2011 were retrospectively reviewed. All patients underwent prior surgical resection. Overall survival was the primary endpoint and rate of disease recurrence in the brain was a secondary endpoint. Patients who had previous radiotherapy or prior surgical resection were included. Kaplan-Meier and Cox proportional hazards models were used to estimate survival and identify factors predictive of recurrence and survival. Post-Gamma Knife recurrence was identified in 11 patients (31.4%) with a median overall survival of 36 months and progression-free survival of 25.8 months. Nine patients (25.7%) had died. Three-year overall survival (OS) and progression-free survival (PFS) rates were 78.0% and 65.0%, respectively. WHO grade II 3-year OS and PFS were 83.4% and 70.1%, while WHO grade III 3-year OS and PFS were 33.3% and 0%. Recurrence rate was significantly higher in patients with a prior history of benign meningioma, nuclear atypia, high mitotic rate, spontaneous necrosis, and WHO grade III diagnosis on univariate analysis; only WHO grade III diagnosis was significant on multivariate analysis. Overall survival was adversely affected in patients with WHO grade III diagnosis, prior history of benign meningioma, prior fractionated radiotherapy, larger tumor volume, and higher isocenter number on univariate analysis; WHO grade III diagnosis and larger treated tumor volume were significant on multivariate analysis. Atypical and anaplastic meningiomas remain difficult tumors to treat. WHO grade III diagnosis and treated tumor volume were significantly