WorldWideScience

Sample records for cancer classification issues

  1. EPA`s program for risk assessment guidelines: Cancer classification issues

    Energy Technology Data Exchange (ETDEWEB)

    Wiltse, J. [Environmental Protection Agency, Washington, DC (United States)

    1990-12-31

    Issues presented are related to classification of weight of evidence in cancer risk assessments. The focus in this paper is on lines of evidence used in constructing a conclusion about potential human carcinogenicity. The paper also discusses issues that are mistakenly addressed as classification issues but are really part of the risk assessment process. 2 figs.

  2. Gene expression based cancer classification

    OpenAIRE

    Sara Tarek; Reda Abd Elwahab; Mahmoud Shoman

    2017-01-01

    Cancer classification based on molecular level investigation has gained the interest of researches as it provides a systematic, accurate and objective diagnosis for different cancer types. Several recent researches have been studying the problem of cancer classification using data mining methods, machine learning algorithms and statistical methods to reach an efficient analysis for gene expression profiles. Studying the characteristics of thousands of genes simultaneously offered a deep in...

  3. Proteomic classification of breast cancer.

    LENUS (Irish Health Repository)

    Kamel, Dalia

    2012-11-01

    Being a significant health problem that affects patients in various age groups, breast cancer has been extensively studied to date. Recently, molecular breast cancer classification has advanced significantly with the availability of genomic profiling technologies. Proteomic technologies have also advanced from traditional protein assays including enzyme-linked immunosorbent assay, immunoblotting and immunohistochemistry to more comprehensive approaches including mass spectrometry and reverse phase protein lysate arrays (RPPA). The purpose of this manuscript is to review the current protein markers that influence breast cancer prediction and prognosis and to focus on novel advances in proteomic classification of breast cancer.

  4. Rare cancers: Challenges & issues

    Directory of Open Access Journals (Sweden)

    Raveendran K Pillai

    2017-01-01

    Full Text Available Rare cancers account for about 22 per cent of all cancers diagnosed worldwide, disproportionately affecting some demographic groups, with an occurrence of less than 6 per 100,000 individuals annually. Many rare cancers in adults, adolescents and children are not curable, and patients and care providers have little option to take therapeutic decisions. The epidemiology of rare cancers is a challenging area of study but is inadequately addressed. Despite efforts mainly in some European nations, a few improvements have been observed in the management of rare cancers. Reasons for this obvious stagnation are multifactorial and are mainly inherent to logistical difficulties in carrying out clinical trials in very small patient populations, hesitation of the pharmaceutical industry to spend in small markets and complexity in creating adequate information for the development of cost-effective drugs. Rare cancers also face specific challenges that include late and incorrect diagnosis, lack of clinical expertise and lack of research interest and development of new therapies. The utilization of nationally representative study findings for the patients' evaluation may possibly offer chances to find out pathogenesis and prevalence, and this will eventually lead to control and prevention. Currently, advancing targeted therapies offer a great opportunity for the better management of rare cancers. Conducting clinical trials with small patient population, innovative clinical trial approach, prevailing controlling obstacles for international cooperation and financial support for research are the present challenges for rare cancers. The International Rare Cancers Initiative functions as a main platform for achieving new international clinical trials in rare tumours. This review delineates the current challenges and issues in the interpretation, management and research scenarios of rare cancers.

  5. Rare cancers: Challenges & issues

    Science.gov (United States)

    Pillai, Raveendran K.; Jayasree, K.

    2017-01-01

    Rare cancers account for about 22 per cent of all cancers diagnosed worldwide, disproportionately affecting some demographic groups, with an occurrence of less than 6 per 100,000 individuals annually. Many rare cancers in adults, adolescents and children are not curable, and patients and care providers have little option to take therapeutic decisions. The epidemiology of rare cancers is a challenging area of study but is inadequately addressed. Despite efforts mainly in some European nations, a few improvements have been observed in the management of rare cancers. Reasons for this obvious stagnation are multifactorial and are mainly inherent to logistical difficulties in carrying out clinical trials in very small patient populations, hesitation of the pharmaceutical industry to spend in small markets and complexity in creating adequate information for the development of cost-effective drugs. Rare cancers also face specific challenges that include late and incorrect diagnosis, lack of clinical expertise and lack of research interest and development of new therapies. The utilization of nationally representative study findings for the patients’ evaluation may possibly offer chances to find out pathogenesis and prevalence, and this will eventually lead to control and prevention. Currently, advancing targeted therapies offer a great opportunity for the better management of rare cancers. Conducting clinical trials with small patient population, innovative clinical trial approach, prevailing controlling obstacles for international cooperation and financial support for research are the present challenges for rare cancers. The International Rare Cancers Initiative functions as a main platform for achieving new international clinical trials in rare tumours. This review delineates the current challenges and issues in the interpretation, management and research scenarios of rare cancers. PMID:28574010

  6. Educational Issues in Childhood Cancer.

    Science.gov (United States)

    Armstrong, Daniel F.; Horn, Marianna

    1995-01-01

    Describes school issues for children with cancer. Presents the relationship between school performance and both the acute and long-term consequences of the type of cancer, radiation therapy, and chemotherapy. Reviews the results of the studies of the cognitive and academic effects of cranial radiation and chemotherapy, and a developmental model…

  7. Power quality event classification: an overview and key issues ...

    African Journals Online (AJOL)

    ... used for PQ events' classifications. Various artificial intelligent techniques which are used in PQ event classification are also discussed. Major Key issues and challenges in classifying PQ events are critically examined and outlined. Keywords: Power quality, PQ event classifiers, artificial intelligence techniques, PQ noise, ...

  8. Molecular classification and prediction in gastric cancer

    Directory of Open Access Journals (Sweden)

    Xiandong Lin

    2015-01-01

    Full Text Available Gastric cancer, a highly heterogeneous disease, is the second leading cause of cancer death and the fourth most common cancer globally, with East Asia accounting for more than half of cases annually. Alongside TNM staging, gastric cancer clinic has two well-recognized classification systems, the Lauren classification that subdivides gastric adenocarcinoma into intestinal and diffuse types and the alternative World Health Organization system that divides gastric cancer into papillary, tubular, mucinous (colloid, and poorly cohesive carcinomas. Both classification systems enable a better understanding of the histogenesis and the biology of gastric cancer yet have a limited clinical utility in guiding patient therapy due to the molecular heterogeneity of gastric cancer. Unprecedented whole-genome-scale data have been catalyzing and advancing the molecular subtyping approach. Here we cataloged and compared those published gene expression profiling signatures in gastric cancer. We summarized recent integrated genomic characterization of gastric cancer based on additional data of somatic mutation, chromosomal instability, EBV virus infection, and DNA methylation. We identified the consensus patterns across these signatures and identified the underlying molecular pathways and biological functions. The identification of molecular subtyping of gastric adenocarcinoma and the development of integrated genomics approaches for clinical applications such as prediction of clinical intervening emerge as an essential phase toward personalized medicine in treating gastric cancer.

  9. Human Cancer Classification: A Systems Biology- Based Model Integrating Morphology, Cancer Stem Cells, Proteomics, and Genomics

    Directory of Open Access Journals (Sweden)

    Halliday A Idikio

    2011-01-01

    Full Text Available Human cancer classification is currently based on the idea of cell of origin, light and electron microscopic attributes of the cancer. What is not yet integrated into cancer classification are the functional attributes of these cancer cells. Recent innovative techniques in biology have provided a wealth of information on the genomic, transcriptomic and proteomic changes in cancer cells. The emergence of the concept of cancer stem cells needs to be included in a classification model to capture the known attributes of cancer stem cells and their potential contribution to treatment response, and metastases. The integrated model of cancer classification presented here incorporates all morphology, cancer stem cell contributions, genetic, and functional attributes of cancer. Integrated cancer classification models could eliminate the unclassifiable cancers as used in current classifications. Future cancer treatment may be advanced by using an integrated model of cancer classification.

  10. Pathway-based classification of cancer subtypes

    Directory of Open Access Journals (Sweden)

    Kim Shinuk

    2012-07-01

    Full Text Available Abstract Background Molecular markers based on gene expression profiles have been used in experimental and clinical settings to distinguish cancerous tumors in stage, grade, survival time, metastasis, and drug sensitivity. However, most significant gene markers are unstable (not reproducible among data sets. We introduce a standardized method for representing cancer markers as 2-level hierarchical feature vectors, with a basic gene level as well as a second level of (more stable pathway markers, for the purpose of discriminating cancer subtypes. This extends standard gene expression arrays with new pathway-level activation features obtained directly from off-the-shelf gene set enrichment algorithms such as GSEA. Such so-called pathway-based expression arrays are significantly more reproducible across datasets. Such reproducibility will be important for clinical usefulness of genomic markers, and augment currently accepted cancer classification protocols. Results The present method produced more stable (reproducible pathway-based markers for discriminating breast cancer metastasis and ovarian cancer survival time. Between two datasets for breast cancer metastasis, the intersection of standard significant gene biomarkers totaled 7.47% of selected genes, compared to 17.65% using pathway-based markers; the corresponding percentages for ovarian cancer datasets were 20.65% and 33.33% respectively. Three pathways, consisting of Type_1_diabetes mellitus, Cytokine-cytokine_receptor_interaction and Hedgehog_signaling (all previously implicated in cancer, are enriched in both the ovarian long survival and breast non-metastasis groups. In addition, integrating pathway and gene information, we identified five (ID4, ANXA4, CXCL9, MYLK, FBXL7 and six (SQLE, E2F1, PTTG1, TSTA3, BUB1B, MAD2L1 known cancer genes significant for ovarian and breast cancer respectively. Conclusions Standardizing the analysis of genomic data in the process of cancer staging

  11. Cancer metastasis: issues and challenges.

    Science.gov (United States)

    Qian, Chao-Nan; Mei, Yan; Zhang, Jian

    2017-04-03

    Metastasis is the major cause of treatment failure in cancer patients and of cancer-related deaths. This editorial discusses how cancer metastasis may be better perceived and controlled. Based on big-data analyses, a collection of 150 important pro-metastatic genes was studied. Using The Cancer Genome Atlas datasets to re-analyze the effect of some previously reported metastatic genes-e.g., JAM2, PPARGC1A, SIK2, and TRAF6-on overall survival of patients with renal and liver cancers, we found that these genes are actually protective factors for patients with cancer. The role of epithelial-mesenchymal transition (EMT) in single-cell metastasis has been well-documented. However, in metastasis caused by cancer cell clusters, EMT may not be necessary. A novel role of epithelial marker E-cadherin, as a sensitizer for chemoresistant prostate cancer cells by inhibiting Notch signaling, has been found. This editorial also discusses the obstacles for developing anti-metastatic drugs, including the lack of high-throughput technologies for identifying metastasis inhibitors, less application of animal models in the pre-clinical evaluation of the leading compounds, and the need for adjustments in clinical trial design to better reflect the anti-metastatic efficacy of new drugs. We are confident that by developing more effective high-throughput technologies to identify metastasis inhibitors, we can better predict, prevent, and treat cancer metastasis.

  12. Non-linear cancer classification using a modified radial basis function classification algorithm.

    Science.gov (United States)

    Wang, Hong-Qiang; Huang, De-Shuang

    2005-10-01

    This paper proposes a modified radial basis function classification algorithm for non-linear cancer classification. In the algorithm, a modified simulated annealing method is developed and combined with the linear least square and gradient paradigms to optimize the structure of the radial basis function (RBF) classifier. The proposed algorithm can be adopted to perform non-linear cancer classification based on gene expression profiles and applied to two microarray data sets involving various human tumor classes: (1) Normal versus colon tumor; (2) acute myeloid leukemia (AML) versus acute lymphoblastic leukemia (ALL). Finally, accuracy and stability for the proposed algorithm are further demonstrated by comparing with the other cancer classification algorithms.

  13. Nominated Texture Based Cervical Cancer Classification

    Directory of Open Access Journals (Sweden)

    Edwin Jayasingh Mariarputham

    2015-01-01

    Full Text Available Accurate classification of Pap smear images becomes the challenging task in medical image processing. This can be improved in two ways. One way is by selecting suitable well defined specific features and the other is by selecting the best classifier. This paper presents a nominated texture based cervical cancer (NTCC classification system which classifies the Pap smear images into any one of the seven classes. This can be achieved by extracting well defined texture features and selecting best classifier. Seven sets of texture features (24 features are extracted which include relative size of nucleus and cytoplasm, dynamic range and first four moments of intensities of nucleus and cytoplasm, relative displacement of nucleus within the cytoplasm, gray level cooccurrence matrix, local binary pattern histogram, tamura features, and edge orientation histogram. Few types of support vector machine (SVM and neural network (NN classifiers are used for the classification. The performance of the NTCC algorithm is tested and compared to other algorithms on public image database of Herlev University Hospital, Denmark, with 917 Pap smear images. The output of SVM is found to be best for the most of the classes and better results for the remaining classes.

  14. Human Cancer Classification: A Systems Biology- Based Model Integrating Morphology, Cancer Stem Cells, Proteomics, and Genomics

    OpenAIRE

    Halliday A Idikio

    2011-01-01

    Human cancer classification is currently based on the idea of cell of origin, light and electron microscopic attributes of the cancer. What is not yet integrated into cancer classification are the functional attributes of these cancer cells. Recent innovative techniques in biology have provided a wealth of information on the genomic, transcriptomic and proteomic changes in cancer cells. The emergence of the concept of cancer stem cells needs to be included in a classification model to capture...

  15. School Refusal Behavior: Classification, Assessment, and Treatment Issues.

    Science.gov (United States)

    Lee, Marcella I.; Miltenberger, Raymond G.

    1996-01-01

    Discusses diagnostic and functional classification, assessment, and treatment approaches for school refusal behavior. Diagnostic classification focuses on separation anxiety disorder, specific phobia, social phobia, depression, and truancy. Functional classification focuses on the maintaining consequences of the behavior, such as avoidance of…

  16. Revised classification/nomenclature of vitiligo and related issues: the Vitiligo Global Issues Consensus Conference

    Science.gov (United States)

    Ezzedine, K.; Lim, H. W.; Suzuki, T.; Katayama, I.; Hamzavi, I.; Lan, C. C. E.; Goh, B. K.; Anbar, T.; de Castro, C. Silva; Lee, A. Y.; Parsad, D.; van Geel, N.; Le Poole, I. C.; Oiso, N.; Benzekri, L.; Spritz, R.; Gauthier, Y.; Hann, S. K.; Picardo, M.; Taieb, A.

    2012-01-01

    Summary During the 2011 International Pigment Cell Conference (IPCC), the Vitiligo European Taskforce (VETF) convened a consensus conference on issues of global importance for vitiligo clinical research. As suggested by an international panel of experts, the conference focused on four topics: classification and nomenclature; definition of stable disease; definition of Koebner’s phenomenon (KP); and ‘autoimmune vitiligo’. These topics were discussed in seven working groups representing different geographical regions. A consensus emerged that segmental vitiligo be classified separately from all other forms of vitiligo and that the term ‘vitiligo’ be used as an umbrella term for all non-segmental forms of vitiligo, including ‘mixed vitiligo’ in which segmental and non-segmental vitiligo are combined and which is considered a subgroup of vitiligo. Further, the conference recommends that disease stability be best assessed based on the stability of individual lesions rather than the overall stability of the disease as the latter is difficult to define precisely and reliably. The conference also endorsed the classification of KP for vitiligo as proposed by the VETF (history based, clinical observation based, or experimentally induced). Lastly, the conference agreed that ‘autoimmune vitiligo’ should not be used as a separate classification as published evidence indicates that the pathophysiology of all forms of vitiligo likely involves autoimmune or inflammatory mechanisms. PMID:22417114

  17. Ethical issues in cancer screening and prevention.

    Science.gov (United States)

    Plutynski, Anya

    2012-06-01

    November 2009's announcement of the USPSTF's recommendations for screening for breast cancer raised a firestorm of objections. Chief among them were that the panel had insufficiently valued patients' lives or allowed cost considerations to influence recommendations. The publicity about the recommendations, however, often either simplified the actual content of the recommendations or bypassed significant methodological issues, which a philosophical examination of both the science behind screening recommendations and their import reveals. In this article, I discuss two of the leading ethical considerations at issue in screening recommendations: respect for patient autonomy and beneficence and then turn to the most significant methodological issues raised by cancer screening: the potential biases that may infect a trial of screening effectiveness, the problem of base rates in communicating risk, and the trade-offs involved in a judgment of screening effectiveness. These issues reach more broadly, into the use of "evidence-based" medicine generally, and have important implications for informed consent.

  18. Fertility Issues in Girls and Women with Cancer

    Science.gov (United States)

    ... Professionals Questions to Ask about Your Treatment Research Fertility Issues in Girls and Women with Cancer Treatment ... Issues in Women . Cancer Treatments May Affect Your Fertility Cancer treatments are important for your future health, ...

  19. [CLASSIFICATION OF ACUTE PANCREATITIS: CURRENT STATE OF THE ISSUE].

    Science.gov (United States)

    Bagnenko, S F; Gol'tsov, V P; Savello, V E; Vashetko, R V

    2015-01-01

    The article analyzed disadvantages of "Atlanta-92" classification of acute pancreatitis and its two modifications: APCWG-2012 and IAP-2011. The school of Saint-Petersburg pancreatologists suggested the classification AP of Russian Surgical Society (2014), which represented the concept of disease staging.

  20. CHILD HEADACHE: MODERN CLASSIFICATION, CLINICAL DETAILS, TREATMENT ISSUES

    Directory of Open Access Journals (Sweden)

    E.I. Karpovich

    2008-01-01

    Full Text Available The article is devoted to classification, diagnostics and treatment of headaches. It describes positive properties of ibuprofen which is recommended for relieving pain for children as young as 3 months old.Key words: children, headache, classification, diagnostics, treatment.

  1. SOMOTE_EASY: AN ALGORITHM TO TREAT THE CLASSIFICATION ISSUE IN REAL DATABASES

    Directory of Open Access Journals (Sweden)

    Hugo Leonardo Pereira Rufino

    2016-04-01

    Full Text Available Most classification tools assume that data distribution be balanced or with similar costs, when not properly classified. Nevertheless, in practical terms, the existence of database where unbalanced classes occur is commonplace, such as in the diagnosis of diseases, in which the confirmed cases are usually rare when compared with a healthy population. Other examples are the detection of fraudulent calls and the detection of system intruders. In these cases, the improper classification of a minority class (for instance, to diagnose a person with cancer as healthy may result in more serious consequences that incorrectly classify a majority class. Therefore, it is important to treat the database where unbalanced classes occur. This paper presents the SMOTE_Easy algorithm, which can classify data, even if there is a high level of unbalancing between different classes. In order to prove its efficiency, a comparison with the main algorithms to treat classification issues was made, where unbalanced data exist. This process was successful in nearly all tested databases

  2. Accurate molecular classification of cancer using simple rules

    Directory of Open Access Journals (Sweden)

    Gotoh Osamu

    2009-10-01

    Full Text Available Abstract Background One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible. Methods We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV of training sets and classification of independent test sets. Results We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML], lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML. Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods. Conclusion In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.

  3. Design issues in cancer screening trials.

    Science.gov (United States)

    Moss, Sue

    2010-10-01

    Randomised controlled trials avoid many of the potential biases associated with the evaluation of cancer screening. Nevertheless there are many issues concerning the design of such trials that require careful consideration and that will influence interpretation of the results. This article discusses issues related to recruitment and randomisation, which will affect the extent to which the population studied, is representative of the eventual target population of a screening programme. It addresses sample size considerations, the use of appropriate outcome measures and the timing of the intervention. Finally, issues related to ensuring appropriate analyses are discussed.

  4. Multi-class cancer classification using multinomial probit regression with Bayesian gene selection.

    Science.gov (United States)

    Zhou, X; Wang, X; Dougherty, E R

    2006-03-01

    We consider the problems of multi-class cancer classification from gene expression data. After discussing the multinomial probit regression model with Bayesian gene selection, we propose two Bayesian gene selection schemes: one employs different strongest genes for different probit regressions; the other employs the same strongest genes for all regressions. Some fast implementation issues for Bayesian gene selection are discussed, including preselection of the strongest genes and recursive computation of the estimation errors using QR decomposition. The proposed gene selection techniques are applied to analyse real breast cancer data, small round blue-cell tumours, the national cancer institute's anti-cancer drug-screen data and acute leukaemia data. Compared with existing multi-class cancer classifications, our proposed methods can find which genes are the most important genes affecting which kind of cancer. Also, the strongest genes selected using our methods are consistent with the biological significance. The recognition accuracies are very high using our proposed methods.

  5. Gene expression-based diagnostics for molecular cancer classification of difficult to diagnose tumors.

    Science.gov (United States)

    Schnabel, Catherine A; Erlander, Mark G

    2012-09-01

    Standardized methods for accurate tumor classification are of critical importance for cancer diagnosis and treatment, particularly in diagnostically-challenging cases where site-directed therapies are an option. Molecular diagnostics for tumor classification, subclassification and site of origin determination based on advances in gene expression profiling have translated into clinical practice as complementary approaches to clinicopathological evaluations. In this review, the foundational science of gene expression-based cancer classification, technical and clinical considerations for clinical translation, and an overview of molecular signatures of tumor classification that are available for clinical use will be discussed. Proposed approaches will also be described for further integration of molecular tests for cancer classification into the diagnostic paradigm using a tissue-based strategy as a key component to direct evaluation. Increasing evidence of improved patient outcomes with the application of site and molecularly-targeted cancer therapy through use of molecular tools highlights the growing potential for these gene expression-based diagnostics to positively impact patient management. Looking forward, the availability of adequate tissue will be a significant issue and limiting factor as cancer diagnosis progresses; when the tumor specimen is limited, use of molecular classification may be a reasonable early step in the evaluation, particularly if the tumor is poorly-differentiated and has atypical features.

  6. Dissecting cancer heterogeneity--an unsupervised classification approach

    NARCIS (Netherlands)

    Wang, Xin; Markowetz, Florian; de Sousa E Melo, Felipe; Medema, Jan Paul; Vermeulen, Louis

    2013-01-01

    Gene-expression-based classification studies have changed the way cancer is traditionally perceived. It is becoming increasingly clear that many cancer types are in fact not single diseases but rather consist of multiple molecular distinct subtypes. In this review, we discuss unsupervised

  7. Plastic surgery for breast cancer: еssentials, classification, performance algorithm

    Directory of Open Access Journals (Sweden)

    A. Kh. Ismagilov

    2014-01-01

    Full Text Available The choice of plastic surgical techniques for cancer is influenced by two factors: resection volume/baseline breast volume ratio and tumor site.Based on these factors, the authors propose a two-level classification and an algorithm for performing the most optimal plastic operation onthe breast for its cancer.

  8. NIM: A Node Influence Based Method for Cancer Classification

    Directory of Open Access Journals (Sweden)

    Yiwen Wang

    2014-01-01

    Full Text Available The classification of different cancer types owns great significance in the medical field. However, the great majority of existing cancer classification methods are clinical-based and have relatively weak diagnostic ability. With the rapid development of gene expression technology, it is able to classify different kinds of cancers using DNA microarray. Our main idea is to confront the problem of cancer classification using gene expression data from a graph-based view. Based on a new node influence model we proposed, this paper presents a novel high accuracy method for cancer classification, which is composed of four parts: the first is to calculate the similarity matrix of all samples, the second is to compute the node influence of training samples, the third is to obtain the similarity between every test sample and each class using weighted sum of node influence and similarity matrix, and the last is to classify each test sample based on its similarity between every class. The data sets used in our experiments are breast cancer, central nervous system, colon tumor, prostate cancer, acute lymphoblastic leukemia, and lung cancer. experimental results showed that our node influence based method (NIM is more efficient and robust than the support vector machine, K-nearest neighbor, C4.5, naive Bayes, and CART.

  9. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  10. Cancer classification: Mutual information, target network and strategies of therapy.

    Science.gov (United States)

    Hsu, Wen-Chin; Liu, Chan-Cheng; Chang, Fu; Chen, Su-Shing

    2012-10-02

    Cancer therapy is a challenging research area because side effects often occur in chemo and radiation therapy. We intend to study a multi-targets and multi-components design that will provide synergistic results to improve efficiency of cancer therapy. We have developed a general methodology, AMFES (Adaptive Multiple FEature Selection), for ranking and selecting important cancer biomarkers based on SVM (Support Vector Machine) classification. In particular, we exemplify this method by three datasets: a prostate cancer (three stages), a breast cancer (four subtypes), and another prostate cancer (normal vs. cancerous). Moreover, we have computed the target networks of these biomarkers as the signatures of the cancers with additional information (mutual information between biomarkers of the network). Then, we proposed a robust framework for synergistic therapy design approach which includes varies existing mechanisms. These methodologies were applied to three GEO datasets: GSE18655 (three prostate stages), GSE19536 (4 subtypes breast cancers) and GSE21036 (prostate cancer cells and normal cells) shown in. We selected 96 biomarkers for first prostate cancer dataset (three prostate stages), 72 for breast cancer (luminal A vs. luminal B), 68 for breast cancer (basal-like vs. normal-like), and 22 for another prostate cancer (cancerous vs. normal. In addition, we obtained statistically significant results of mutual information, which demonstrate that the dependencies among these biomarkers can be positive or negative. We proposed an efficient feature ranking and selection scheme, AMFES, to select an important subset from a large number of features for any cancer dataset. Thus, we obtained the signatures of these cancers by building their target networks. Finally, we proposed a robust framework of synergistic therapy for cancer patients. Our framework is not only supported by real GEO datasets but also aim to a multi-targets/multi-components drug design tool, which improves

  11. CLASSIFICATION OF CERVICAL CANCER CELLS IN PAP SMEAR SCREENING TEST

    Directory of Open Access Journals (Sweden)

    S. Athinarayanan

    2016-05-01

    Full Text Available Cervical cancer is second topmost cancers among women but also, it was a curable one. Regular smear test can discover the sign of precancerous cell and treated the patient according to the result. However sometimes the detection errors can be occurred by smear thickness, cell overlapping or by un-wanted particles in the smear and cytotechnologists faulty diagnosis. Therefore the reason automatic cancer detection was developed. This was help to increase cancer cell mindfulness, diagnosis accuracy with low cost. This detection process consists of some techniques of the image preprocessing that is segmentation and effective texture feature extraction with SVM classification. Then the Final Classification Results of this proposed technique was compared to the previous classification techniques of KNN and ANN and the result would be very useful to cytotechnologists for their further analysis

  12. Building a Joint-Service Classification Research Roadmap: Methodological Issues in Selection and Classification

    Science.gov (United States)

    1994-02-01

    NEW METHODS FOR ESTIMATING GAINS DUE TO CLASSIFICATION AND NEW PROCEDURES FOR MAKING D!FFERENTIAL JOB ASSIGNMENTS Paul J. Sticha Classification...people, assumed to be reflected in test performance" (Cronbach & Meehl , 1955, p. 283). Methods for establishing and testing a latent structure will be...and Meehl ). Because of this close tie to theory development and testing, and the ability to explicitly account for measurement error in the observed

  13. Magnetic resonance imaging texture analysis classification of primary breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Waugh, S.A.; Lerski, R.A. [Ninewells Hospital and Medical School, Department of Medical Physics, Dundee (United Kingdom); Purdie, C.A.; Jordan, L.B. [Ninewells Hospital and Medical School, Department of Pathology, Dundee (United Kingdom); Vinnicombe, S. [University of Dundee, Division of Imaging and Technology, Ninewells Hospital and Medical School, Dundee (United Kingdom); Martin, P. [Ninewells Hospital and Medical School, Department of Clinical Radiology, Dundee (United Kingdom); Thompson, A.M. [University of Texas MD Anderson Cancer Center, Department of Surgical Oncology, Houston, TX (United States)

    2016-02-15

    Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

  14. Classification of oral cancers using Raman spectroscopy of serum

    Science.gov (United States)

    Sahu, Aditi; Talathi, Sneha; Sawant, Sharada; Krishna, C. Murali

    2014-03-01

    Oral cancers are the sixth most common malignancy worldwide, with low 5-year disease free survival rates, attributable to late detection due to lack of reliable screening modalities. Our in vivo Raman spectroscopy studies have demonstrated classification of normal and tumor as well as cancer field effects (CFE), the earliest events in oral cancers. In view of limitations such as requirement of on-site instrumentation and stringent experimental conditions of this approach, feasibility of classification of normal and cancer using serum was explored using 532 nm excitation. In this study, strong resonance features of β-carotenes, present differentially in normal and pathological conditions, were observed. In the present study, Raman spectra of sera of 36 buccal mucosa, 33 tongue cancers and 17 healthy subjects were recorded using Raman microprobe coupled with 40X objective using 785 nm excitation, a known source of excitation for biomedical applications. To eliminate heterogeneity, average of 3 spectra recorded from each sample was subjected to PC-LDA followed by leave-one-out-cross-validation. Findings indicate average classification efficiency of ~70% for normal and cancer. Buccal mucosa and tongue cancer serum could also be classified with an efficiency of ~68%. Of the two cancers, buccal mucosa cancer and normal could be classified with a higher efficiency. Findings of the study are quite comparable to that of our earlier study, which suggest that there exist significant differences, other than β- carotenes, between normal and cancerous samples which can be exploited for the classification. Prospectively, extensive validation studies will be undertaken to confirm the findings.

  15. Psychosocial issues in the cancer patient.

    Science.gov (United States)

    Csaszar, N; Ganju, Aruna; Mirnics, Z S; Varga, P P

    2009-10-15

    Systematic review of the literature. To identify psychosocial issues affecting patients with a diagnosis of a spinal column or cord tumor. Using the keywords "cancer communication," "psychosocial care," "cancer patient," and "spine cancer patient," a review of the English literature was performed on Medline, EMBASE, and PsycInfo, a database of the psychology and psychiatry literature in the United States. The relevant articles were reviewed; in addition, relevant references from selected articles were searched. The Spine Oncology Study Group, an international panel of spine oncology surgeons, medical and radiation oncologists, identified 2 key questions to be addressed in the course of the systematic review of the literature. Pertinent manuscripts were rated as being of high, moderate, low, or very low quality. Using the Grading of Recommendations, Assessment, Development, and Evaluation evidence-based review system, the 2 key questions were answered using literature review and expert opinion. 1. Who are the allied health care professionals necessary for the comprehensive care of the spine tumor patient? 2. Does compassionate communication (in giving life altering information) affect outcome? What tools can be used in communication with the spine tumor patient? Systematic review of the 3 databases yielded 228 articles pertaining to the psychosocial care of spine tumor patients; systematic review yielded 326 articles addressing communication in cancer patients. Systematic search of the Medline, EMBASE, and PsycInfo databases failed to identify any articles that specifically addressed the 2 questions of interest in the spine tumor patient population. The literature search identified low and very low quality evidence; 2 randomized controlled studies were identified. Although neither specifically pertained to the spine tumor patient population, these articles were reviewed and graded as low-quality evidence. A multidisciplinary group of allied health care professionals

  16. MORPHOLOGICAL CLASSIFICATION OF RENAL-CANCER

    NARCIS (Netherlands)

    STORKEL, S; VANDENBERG, E

    The current classification of renal-cell adenomas (RCAs) and carcinomas (RCCs) is based on eight basic cell and tumor types (entities) with characteristic morphologic features: (1) RCCs of clear-cell type, (2) RCAs/RCCs of chromophilic-cell type, (3) RCAs/RCCs of chromophobic-cell type, (4) RCCs of

  17. Genetic issues in patients with breast cancer.

    Science.gov (United States)

    Fossland, Victoria Sahadevan; Stroop, Jennifer B; Schwartz, Robin C; Kurtzman, Scott H

    2009-01-01

    Screening for genetic abnormalities is a relatively complex task requiring detailed training and knowledge. Analysis of a person's genetic makeup has implications not only for that individual but also for their progenitors, offspring, siblings, and spouses. There are potential insurance, employment, and other risks regarding disclosure of this information. With proper training, surgeons or nurses with advanced skills can be qualified to conduct this type of initial analysis. Geneticists may be the ideal professionals to counsel patients. In this article, we explore these and other issues. The goal is to provide the surgeon with the information needed to identify patients at risk for carrying identifiable mutations that might lead to the development of breast cancer.

  18. Magnetic resonance imaging texture analysis classification of primary breast cancer.

    Science.gov (United States)

    Waugh, S A; Purdie, C A; Jordan, L B; Vinnicombe, S; Lerski, R A; Martin, P; Thompson, A M

    2016-02-01

    Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75%, AUROC = 0.816; test: 72.5%, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. • MR-derived entropy features, representing heterogeneity, provide important information on tissue composition. • Entropy features can differentiate between histological and immunohistochemical subtypes of breast cancer. • Differing entropy features between breast cancer subtypes implies differences in lesion heterogeneity. • Texture analysis of breast cancer potentially provides added information for decision making.

  19. Pathway-based classification of cancer subtypes

    OpenAIRE

    Kim, Shinuk; Kon, Mark; DeLisi, Charles

    2012-01-01

    Abstract Background Molecular markers based on gene expression profiles have been used in experimental and clinical settings to distinguish cancerous tumors in stage, grade, survival time, metastasis, and drug sensitivity. However, most significant gene markers are unstable (not reproducible) among data sets. We introduce a standardized method for representing cancer markers as 2-level hierarchical feature vectors, with a basic gene level as well as a second level of (more stable) pathway mar...

  20. Association between gastric cancer and the Kyoto classification of gastritis.

    Science.gov (United States)

    Shichijo, Satoki; Hirata, Yoshihiro; Niikura, Ryota; Hayakawa, Yoku; Yamada, Atsuo; Koike, Kazuhiko

    2017-09-01

    Histological gastritis is associated with gastric cancer, but its diagnosis requires biopsy. Many classifications of endoscopic gastritis are available, but not all are useful for risk stratification of gastric cancer. The Kyoto Classification of Gastritis was proposed at the 85th Congress of the Japan Gastroenterological Endoscopy Society. This cross-sectional study evaluated the usefulness of the Kyoto Classification of Gastritis for risk stratification of gastric cancer. From August 2013 to September 2014, esophagogastroduodenoscopy was performed and the gastric findings evaluated according to the Kyoto Classification of Gastritis in a total of 4062 patients. The following five endoscopic findings were selected based on previous reports: atrophy, intestinal metaplasia, enlarged folds, nodularity, and diffuse redness. A total of 3392 patients (1746 [51%] men and 1646 [49%] women) were analyzed. Among them, 107 gastric cancers were diagnosed. Atrophy was found in 2585 (78%) and intestinal metaplasia in 924 (27%). Enlarged folds, nodularity, and diffuse redness were found in 197 (5.8%), 22 (0.6%), and 573 (17%), respectively. In univariate analyses, the severity of atrophy, intestinal metaplasia, diffuse redness, age, and male sex were associated with gastric cancer. In a multivariate analysis, atrophy and male sex were found to be independent risk factors. Younger age and severe atrophy were determined to be associated with diffuse-type gastric cancer. Endoscopic detection of atrophy was associated with the risk of gastric cancer. Thus, patients with severe atrophy should be examined carefully and may require intensive follow-up. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  1. Lung cancer classification using neural networks for CT images.

    Science.gov (United States)

    Kuruvilla, Jinsa; Gunavathi, K

    2014-01-01

    Early detection of cancer is the most promising way to enhance a patient's chance for survival. This paper presents a computer aided classification method in computed tomography (CT) images of lungs developed using artificial neural network. The entire lung is segmented from the CT images and the parameters are calculated from the segmented image. The statistical parameters like mean, standard deviation, skewness, kurtosis, fifth central moment and sixth central moment are used for classification. The classification process is done by feed forward and feed forward back propagation neural networks. Compared to feed forward networks the feed forward back propagation network gives better classification. The parameter skewness gives the maximum classification accuracy. Among the already available thirteen training functions of back propagation neural network, the Traingdx function gives the maximum classification accuracy of 91.1%. Two new training functions are proposed in this paper. The results show that the proposed training function 1 gives an accuracy of 93.3%, specificity of 100% and sensitivity of 91.4% and a mean square error of 0.998. The proposed training function 2 gives a classification accuracy of 93.3% and minimum mean square error of 0.0942. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  2. Classification of neuropathic pain in cancer patients

    DEFF Research Database (Denmark)

    Brunelli, Cinzia; Bennett, Michael I; Kaasa, Stein

    2014-01-01

    and on the relevance of patient-reported outcome (PRO) descriptors for the screening of NP in this population. An international group of 42 experts was invited to participate in a consensus process through a modified 2-round Internet-based Delphi survey. Relevant topics investigated were: peculiarities of NP...... was found on the statement "the pathophysiology of NP due to cancer can be different from non-cancer NP" (MED=9, IQR=2). Satisfactory consensus was reached for the first 3 NeuPSIG criteria (pain distribution, history, and sensory findings; MEDs⩾8, IQRs⩽3), but not for the fourth one (diagnostic test...

  3. Pathological Bases for a Robust Application of Cancer Molecular Classification

    Directory of Open Access Journals (Sweden)

    Salvador J. Diaz-Cano

    2015-04-01

    Full Text Available Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes, and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors.

  4. Classification of FTIR cancer data using wavelets and BPNN

    Science.gov (United States)

    Cheng, Cungui; Tian, Yumei; Zhang, Changjiang

    2007-11-01

    In this paper, a feature extracting method based on wavelets for horizontal attenuated total reflectance Fourier transform infrared spectroscopy (HATR-FTIR) cancer data analysis and classification using artificial neural network trained with back-propagation algorithm is presented. 168 Spectra were collected from 84 pairs of fresh normal and abnormal lung tissue's samples. After preprocessing, 12 features were extracted with continuous wavelet analysis. Based on BPNN classification, all spectra were classified into two categories : normal or abnormal. The accuracy of identifying normal, early carcinoma, and advanced carcinoma were 100%, 90% and 100% respectively. This result indicated that FTIR with continuous wavelet transform (CWT) and the back-propagation neural network (BPNN) could effectively and easily diagnose lung cancer in its early stages.

  5. Computer aided decision support system for cervical cancer classification

    Science.gov (United States)

    Rahmadwati, Rahmadwati; Naghdy, Golshah; Ros, Montserrat; Todd, Catherine

    2012-10-01

    Conventional analysis of a cervical histology image, such a pap smear or a biopsy sample, is performed by an expert pathologist manually. This involves inspecting the sample for cellular level abnormalities and determining the spread of the abnormalities. Cancer is graded based on the spread of the abnormal cells. This is a tedious, subjective and time-consuming process with considerable variations in diagnosis between the experts. This paper presents a computer aided decision support system (CADSS) tool to help the pathologists in their examination of the cervical cancer biopsies. The main aim of the proposed CADSS system is to identify abnormalities and quantify cancer grading in a systematic and repeatable manner. The paper proposes three different methods which presents and compares the results using 475 images of cervical biopsies which include normal, three stages of pre cancer, and malignant cases. This paper will explore various components of an effective CADSS; image acquisition, pre-processing, segmentation, feature extraction, classification, grading and disease identification. Cervical histological images are captured using a digital microscope. The images are captured in sufficient resolution to retain enough information for effective classification. Histology images of cervical biopsies consist of three major sections; background, stroma and squamous epithelium. Most diagnostic information are contained within the epithelium region. This paper will present two levels of segmentations; global (macro) and local (micro). At the global level the squamous epithelium is separated from the background and stroma. At the local or cellular level, the nuclei and cytoplasm are segmented for further analysis. Image features that influence the pathologists' decision during the analysis and classification of a cervical biopsy are the nuclei's shape and spread; the ratio of the areas of nuclei and cytoplasm as well as the texture and spread of the abnormalities

  6. Critical issues in cancer vaccine trial design.

    Science.gov (United States)

    Clifton, Guy T; Kohrt, Holbrook E; Peoples, George E

    2015-12-16

    As the clinical experience with cancer vaccines and cancer immunotherapy increases, there are important lessons that can be learned from the successes and failures of past trials. Many lessons affect the design and conduct of clinical trials themselves. Appropriate patient selection, clinical trial design, immunologic monitoring, and appropriate endpoints are all essential to the efficiency and success of bringing cancer vaccines from conception to clinical use. Copyright © 2015. Published by Elsevier Ltd.

  7. Testicular cancer: addressing the psychosexual issues.

    LENUS (Irish Health Repository)

    Moore, Annamarie

    2012-01-31

    Testicular cancer is the most common malignancy in men aged 15-35 years and predominantly occurs at a time in a man\\'s life when important decisions about marriage, starting a family and a professional career are being made. While treatments for testicular cancer are very successful, they can have a major impact on the person\\'s sexuality and sense of self. The focus of this article is on exploring the impact of cancer treatments for testicular cancer on men\\'s sexuality and how nurses can respond to their concerns in a sensitive and informed manner.

  8. Surviving testicular cancer: : sexuality & other existential issues

    NARCIS (Netherlands)

    Pool, Grietje

    2003-01-01

    The thesis deals with the psychological aspects of ‘sexuality after testicular cancer’, where my collegue, the physician dr. Van Basten formerly predominantly described the physical-biological aspects of this subject. Testicular cancer is a type of male genital cancer, usually diagnosed between

  9. Issues in adult blood cancer survivorship care.

    Science.gov (United States)

    Bugos, Kelly G

    2015-02-01

    To describe the current literature and future directions of survivorship care for the adult blood cancer population including unique features, identification of needs, practice guidelines, care models and the implications for nursing. Peer reviewed literature, government and national advocacy organization reports, professional organization guidelines. Adult blood cancer survivors are a heterogeneous population that often receives complicated treatments to live a longer life. Survivorship needs among this population are often unmet throughout the cancer care continuum. The limited research literature and guidelines point to survivorship care strategies from the day of diagnosis to enhance long-term outcomes and improve quality of life. Nurses are experts in symptom management and central to preventing, detecting, measuring, educating, and treating the effects of cancer and its treatment. Moreover, nurses are key to implementing strategies to support blood cancer survivors, families, and caregivers from the day of diagnosis to the last day of life. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Molecular classification of gastric cancer: a new paradigm.

    Science.gov (United States)

    Shah, Manish A; Khanin, Raya; Tang, Laura; Janjigian, Yelena Y; Klimstra, David S; Gerdes, Hans; Kelsen, David P

    2011-05-01

    Gastric cancer may be subdivided into 3 distinct subtypes--proximal, diffuse, and distal gastric cancer--based on histopathologic and anatomic criteria. Each subtype is associated with unique epidemiology. Our aim is to test the hypothesis that these distinct gastric cancer subtypes may also be distinguished by gene expression analysis. Patients with localized gastric adenocarcinoma being screened for a phase II preoperative clinical trial (National Cancer Institute, NCI #5917) underwent endoscopic biopsy for fresh tumor procurement. Four to 6 targeted biopsies of the primary tumor were obtained. Macrodissection was carried out to ensure more than 80% carcinoma in the sample. HG-U133A GeneChip (Affymetrix) was used for cDNA expression analysis, and all arrays were processed and analyzed using the Bioconductor R-package. Between November 2003 and January 2006, 57 patients were screened to identify 36 patients with localized gastric cancer who had adequate RNA for expression analysis. Using supervised analysis, we built a classifier to distinguish the 3 gastric cancer subtypes, successfully classifying each into tightly grouped clusters. Leave-one-out cross-validation error was 0.14, suggesting that more than 85% of samples were classified correctly. Gene set analysis with the false discovery rate set at 0.25 identified several pathways that were differentially regulated when comparing each gastric cancer subtype to adjacent normal stomach. Subtypes of gastric cancer that have epidemiologic and histologic distinctions are also distinguished by gene expression data. These preliminary data suggest a new classification of gastric cancer with implications for improving our understanding of disease biology and identification of unique molecular drivers for each gastric cancer subtype. ©2011 AACR.

  11. Feature Subset Selection for Cancer Classification Using Weight Local Modularity.

    Science.gov (United States)

    Zhao, Guodong; Wu, Yan

    2016-10-05

    Microarray is recently becoming an important tool for profiling the global gene expression patterns of tissues. Gene selection is a popular technology for cancer classification that aims to identify a small number of informative genes from thousands of genes that may contribute to the occurrence of cancers to obtain a high predictive accuracy. This technique has been extensively studied in recent years. This study develops a novel feature selection (FS) method for gene subset selection by utilizing the Weight Local Modularity (WLM) in a complex network, called the WLMGS. In the proposed method, the discriminative power of gene subset is evaluated by using the weight local modularity of a weighted sample graph in the gene subset where the intra-class distance is small and the inter-class distance is large. A higher local modularity of the gene subset corresponds to a greater discriminative of the gene subset. With the use of forward search strategy, a more informative gene subset as a group can be selected for the classification process. Computational experiments show that the proposed algorithm can select a small subset of the predictive gene as a group while preserving classification accuracy.

  12. Colorectal Cancer Classification and Cell Heterogeneity: A Systems Oncology Approach

    Directory of Open Access Journals (Sweden)

    Moisés Blanco-Calvo

    2015-06-01

    Full Text Available Colorectal cancer is a heterogeneous disease that manifests through diverse clinical scenarios. During many years, our knowledge about the variability of colorectal tumors was limited to the histopathological analysis from which generic classifications associated with different clinical expectations are derived. However, currently we are beginning to understand that under the intense pathological and clinical variability of these tumors there underlies strong genetic and biological heterogeneity. Thus, with the increasing available information of inter-tumor and intra-tumor heterogeneity, the classical pathological approach is being displaced in favor of novel molecular classifications. In the present article, we summarize the most relevant proposals of molecular classifications obtained from the analysis of colorectal tumors using powerful high throughput techniques and devices. We also discuss the role that cancer systems biology may play in the integration and interpretation of the high amount of data generated and the challenges to be addressed in the future development of precision oncology. In addition, we review the current state of implementation of these novel tools in the pathological laboratory and in clinical practice.

  13. [New molecular classification of colorectal cancer, pancreatic cancer and stomach cancer: Towards "à la carte" treatment?].

    Science.gov (United States)

    Dreyer, Chantal; Afchain, Pauline; Trouilloud, Isabelle; André, Thierry

    2016-01-01

    This review reports 3 of recently published molecular classifications of the 3 main gastro-intestinal cancers: gastric, pancreatic and colorectal adenocarcinoma. In colorectal adenocarcinoma, 6 independent classifications were combined to finally hold 4 molecular sub-groups, Consensus Molecular Subtypes (CMS 1-4), linked to various clinical, molecular and survival data. CMS1 (14% MSI with immune activation); CMS2 (37%: canonical with epithelial differentiation and activation of the WNT/MYC pathway); CMS3 (13% metabolic with epithelial differentiation and RAS mutation); CMS4 (23%: mesenchymal with activation of TGFβ pathway and angiogenesis with stromal invasion). In gastric adenocarcinoma, 4 groups were established: subtype "EBV" (9%, high frequency of PIK3CA mutations, hypermetylation and amplification of JAK2, PD-L1 and PD-L2), subtype "MSI" (22%, high rate of mutation), subtype "genomically stable tumor" (20%, diffuse histology type and mutations of RAS and genes encoding integrins and adhesion proteins including CDH1) and subtype "tumors with chromosomal instability" (50%, intestinal type, aneuploidy and receptor tyrosine kinase amplification). In pancreatic adenocarcinomas, a classification in four sub-groups has been proposed, stable subtype (20%, aneuploidy), locally rearranged subtype (30%, focal event on one or two chromosoms), scattered subtype (36%,200 structural variation events, defects in DNA maintenance). Although currently away from the care of patients, these classifications open the way to "à la carte" treatment depending on molecular biology. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

  14. Pathohistological classification systems in gastric cancer: diagnostic relevance and prognostic value.

    Science.gov (United States)

    Berlth, Felix; Bollschweiler, Elfriede; Drebber, Uta; Hoelscher, Arnulf H; Moenig, Stefan

    2014-05-21

    Several pathohistological classification systems exist for the diagnosis of gastric cancer. Many studies have investigated the correlation between the pathohistological characteristics in gastric cancer and patient characteristics, disease specific criteria and overall outcome. It is still controversial as to which classification system imparts the most reliable information, and therefore, the choice of system may vary in clinical routine. In addition to the most common classification systems, such as the Laurén and the World Health Organization (WHO) classifications, other authors have tried to characterize and classify gastric cancer based on the microscopic morphology and in reference to the clinical outcome of the patients. In more than 50 years of systematic classification of the pathohistological characteristics of gastric cancer, there is no sole classification system that is consistently used worldwide in diagnostics and research. However, several national guidelines for the treatment of gastric cancer refer to the Laurén or the WHO classifications regarding therapeutic decision-making, which underlines the importance of a reliable classification system for gastric cancer. The latest results from gastric cancer studies indicate that it might be useful to integrate DNA- and RNA-based features of gastric cancer into the classification systems to establish prognostic relevance. This article reviews the diagnostic relevance and the prognostic value of different pathohistological classification systems in gastric cancer.

  15. Classification of breast cancer cytological specimen using convolutional neural network

    Science.gov (United States)

    Żejmo, Michał; Kowal, Marek; Korbicz, Józef; Monczak, Roman

    2017-01-01

    The paper presents a deep learning approach for automatic classification of breast tumors based on fine needle cytology. The main aim of the system is to distinguish benign from malignant cases based on microscopic images. Experiment was carried out on cytological samples derived from 50 patients (25 benign cases + 25 malignant cases) diagnosed in Regional Hospital in Zielona Góra. To classify microscopic images, we used convolutional neural networks (CNN) of two types: GoogLeNet and AlexNet. Due to the very large size of images of cytological specimen (on average 200000 × 100000 pixels), they were divided into smaller patches of size 256 × 256 pixels. Breast cancer classification usually is based on morphometric features of nuclei. Therefore, training and validation patches were selected using Support Vector Machine (SVM) so that suitable amount of cell material was depicted. Neural classifiers were tuned using GPU accelerated implementation of gradient descent algorithm. Training error was defined as a cross-entropy classification loss. Classification accuracy was defined as the percentage ratio of successfully classified validation patches to the total number of validation patches. The best accuracy rate of 83% was obtained by GoogLeNet model. We observed that more misclassified patches belong to malignant cases.

  16. Aging Families and Breast Cancer: Multigenerational Issues

    National Research Council Canada - National Science Library

    Raveis, Victoria

    2003-01-01

    With the continuing shift of cancer care to community-based care the necessity to develop programs that will enable the family to meet patients' needs for support and assistance is of paramount importance...

  17. Aging Families and Breast Cancer: Multigenerational Issues

    National Research Council Canada - National Science Library

    Raveis, Victoria

    2001-01-01

    With the continuing shift of cancer care to community-based care the necessity to develop programs that will enable the family to meet patients' needs for support and assistance is of paramount importance...

  18. Classification of breast cancer histology images using Convolutional Neural Networks.

    Directory of Open Access Journals (Sweden)

    Teresa Araújo

    Full Text Available Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods designed for a specific problem based on field-knowledge. To overcome the many difficulties of the feature-based approaches, deep learning methods are becoming important alternatives. A method for the classification of hematoxylin and eosin stained breast biopsy images using Convolutional Neural Networks (CNNs is proposed. Images are classified in four classes, normal tissue, benign lesion, in situ carcinoma and invasive carcinoma, and in two classes, carcinoma and non-carcinoma. The architecture of the network is designed to retrieve information at different scales, including both nuclei and overall tissue organization. This design allows the extension of the proposed system to whole-slide histology images. The features extracted by the CNN are also used for training a Support Vector Machine classifier. Accuracies of 77.8% for four class and 83.3% for carcinoma/non-carcinoma are achieved. The sensitivity of our method for cancer cases is 95.6%.

  19. Application of machine learning on brain cancer multiclass classification

    Science.gov (United States)

    Panca, V.; Rustam, Z.

    2017-07-01

    Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

  20. Molecular Classification of Gastric Cancer: A new paradigm

    Science.gov (United States)

    Shah, Manish A.; Khanin, Raya; Tang, Laura; Janjigian, Yelena Y.; Klimstra, David S.; Gerdes, Hans; Kelsen, David P.

    2011-01-01

    Purpose Gastric cancer may be subdivided into three distinct subtypes –proximal, diffuse, and distal gastric cancer– based on histopathologic and anatomic criteria. Each subtype is associated with unique epidemiology. Our aim is to test the hypothesis that these distinct gastric cancer subtypes may also be distinguished by gene expression analysis. Experimental Design Patients with localized gastric adenocarcinoma being screened for a phase II preoperative clinical trial (NCI 5917) underwent endoscopic biopsy for fresh tumor procurement. 4–6 targeted biopsies of the primary tumor were obtained. Macrodissection was performed to ensure >80% carcinoma in the sample. HG-U133A GeneChip (Affymetrix) was used for cDNA expression analysis, and all arrays were processed and analyzed using the Bioconductor R-package. Results Between November 2003 and January 2006, 57 patients were screened to identify 36 patients with localized gastric cancer who had adequate RNA for expression analysis. Using supervised analysis, we built a classifier to distinguish the three gastric cancer subtypes, successfully classifying each into tightly grouped clusters. Leave-one-out cross validation error was 0.14, suggesting that >85% of samples were classified correctly. Gene set analysis with the False Discovery Rate set at 0.25 identified several pathways that were differentially regulated when comparing each gastric cancer subtype to adjacent normal stomach. Conclusions Subtypes of gastric cancer that have epidemiologic and histologic distinction are also distinguished by gene expression data. These preliminary data suggest a new classification of gastric cancer with implications for improving our understanding of disease biology and identification of unique molecular drivers for each gastric cancer subtype. PMID:21430069

  1. Familial pancreatic cancer: Concept, management and issues

    Science.gov (United States)

    Matsubayashi, Hiroyuki; Takaori, Kyoichi; Morizane, Chigusa; Maguchi, Hiroyuki; Mizuma, Masamichi; Takahashi, Hideaki; Wada, Keita; Hosoi, Hiroko; Yachida, Shinichi; Suzuki, Masami; Usui, Risa; Furukawa, Toru; Furuse, Junji; Sato, Takamitsu; Ueno, Makoto; Kiyozumi, Yoshimi; Hijioka, Susumu; Mizuno, Nobumasa; Terashima, Takeshi; Mizumoto, Masaki; Kodama, Yuzo; Torishima, Masako; Kawaguchi, Takahisa; Ashida, Reiko; Kitano, Masayuki; Hanada, Keiji; Furukawa, Masayuki; Kawabe, Ken; Majima, Yoshiyuki; Shimosegawa, Toru

    2017-01-01

    Familial pancreatic cancer (FPC) is broadly defined as two first-degree-relatives with pancreatic cancer (PC) and accounts for 4%-10% of PC. Several genetic syndromes, including Peutz-Jeghers syndrome, hereditary pancreatitis, hereditary breast-ovarian cancer syndrome (HBOC), Lynch syndrome, and familial adenomatous polyposis (FAP), also have increased risks of PC, but the narrowest definition of FPC excludes these known syndromes. When compared with other familial tumors, proven genetic alterations are limited to a small proportion ( Caucasian) and a younger onset are common also in FPC. In European countries, “anticipation” is reported in FPC families, as with other hereditary syndromes; a trend toward younger age and worse prognosis is recognized in the late years. The resected pancreases of FPC kindred often show multiple pancreatic intraepithelial neoplasia (PanIN) foci, with various K-ras mutations, similar to colorectal polyposis seen in the FAP patients. As with HBOC patients, a patient who is a BRCA mutation carrier with unresectable pancreatic cancer (accounting for 0%-19% of FPC patients) demonstrated better outcome following platinum and Poly (ADP-ribose) polymerase inhibitor treatment. Western countries have established FPC registries since the 1990s and several surveillance projects for high-risk individuals are now ongoing to detect early PCs. Improvement in lifestyle habits, including non-smoking, is recommended for individuals at risk. In Japan, the FPC study group was initiated in 2013 and the Japanese FPC registry was established in 2014 by the Japan Pancreas Society. PMID:28246467

  2. Classification of Bladder Cancer Patients via Penalized Linear Discriminant Analysis

    Science.gov (United States)

    Raeisi Shahraki, Hadi; Bemani, Peyman; Jalali, Maryam

    2017-05-01

    Objectives: In order to identify genes with the greatest contribution to bladder cancer, we proposed a sparse model making the best discrimination from other patients. Methods: In a cross-sectional study, 22 genes with a key role in most cancers were considered in 21 bladder cancer patients and 14 participants of the same age (± 3 years) without bladder cancer in Shiraz city, Southern Iran. Real time-PCR was carried out using SYBR Green and for each of the 22 target genes 2-Δct as a quantitative index of gene expression was reported. We determined the most affective genes for the discriminant vector by applying penalized linear discriminant analysis using LASSO penalties. All the analyses were performed using SPSS version 18 and the penalized LDA package in R.3.1.3 software. Results: Using penalized linear discriminant analysis led to elimination of 13 less important genes. Considering the simultaneous effects of 22 genes with important influence on many cancers, it was found that TGFβ, IL12A, Her2, MDM2, CTLA-4 and IL-23 genes had the greatest contribution in classifying bladder cancer patients with the penalized linear discriminant vector. The receiver operating characteristic (ROC) curve revealed that the proposed vector had good performance with minimal (only 3) mis- classification. The area under the curve (AUC) of our proposed test was 96% (95% CI: 83%- 100%) and sensitivity, specificity, positive and negative predictive values were 90.5%, 85.7%, 90.5% and 85.7%, respectively. Conclusions: The penalized discriminant method can be considered as appropriate for classifying bladder cancer cases and searching for important biomarkers. Creative Commons Attribution License

  3. Classification of cancer-related death certificates using machine learning.

    Science.gov (United States)

    Butt, Luke; Zuccon, Guido; Nguyen, Anthony; Bergheim, Anton; Grayson, Narelle

    2013-01-01

    Cancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities. In this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated. A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes. Death certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM) classifier achieved best performance with an overall Fmeasure of 0.9866 when evaluated on a set of 5,000 freetext death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032) and false negative rate (0.0297) while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers. The selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with an SVM classifier.

  4. Classification of Cancer-related Death Certificates using Machine Learning

    Directory of Open Access Journals (Sweden)

    Luke Butt

    2013-05-01

    Full Text Available BackgroundCancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities.AimsIn this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated.Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes.ResultsDeath certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032 and false negative rate (0.0297 while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers.ConclusionThe selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with

  5. Treating Colon Cancer Survivability Prediction as a Classification Problem

    Directory of Open Access Journals (Sweden)

    Ana SILVA

    2016-10-01

    Full Text Available This work presents a survivability prediction model for colon cancer developed with machine learning techniques. Survivability was viewed as a classification task where it was necessary to determine if a patient would survive each of the five years following treatment. The model was based on the SEER dataset which, after preprocessing, consisted of 38,592 records of colon cancer patients. Six features were extracted from a feature selection process in order to construct the model. This model was compared with another one with 18 features indicated by a physician. The results show that the performance of the six-feature model is close to that of the model using 18 features, which indicates that the first may be a good compromise between usability and performance.

  6. [Molecular Classification of Colorectal Cancers and Clinical Application].

    Science.gov (United States)

    Jeon, So Yeon; Kim, Won Kyu; Kim, Hoguen

    2016-12-25

    The molecular genetics of colorectal cancers (CRCs) is among the best understood of common human cancers. It is difficult to predict the prognosis and/or to predict chemoresponding in CRC patients. At present, prognosis is based predominantly on the tumor stage and pathological examination of the disease. Molecular classification of CRCs, based on genomics and transcriptomics, proposed that CRCs can be classified into at least three-to-six subtypes, depending on the gene expression pattern, and groups of marker genes representing to each subtype have also been reported. Gene expression-based subtyping is now widely accepted as a relevant source of disease stratification. We reviewed the previous studies on CRC subtyping, international consortium dedicated to large-scale data sharing and analytics recently established four consensus molecular subtypes with distinguishing features. Predictive markers identified in these studies are under investigation and large-scale clinical evaluations of molecular markers are currently in progress.

  7. Classifications of multispectral colorectal cancer tissues using convolution neural network

    Directory of Open Access Journals (Sweden)

    Hawraa Haj-Hassan

    2017-01-01

    Full Text Available Background: Colorectal cancer (CRC is the third most common cancer among men and women. Its diagnosis in early stages, typically done through the analysis of colon biopsy images, can greatly improve the chances of a successful treatment. This paper proposes to use convolution neural networks (CNNs to predict three tissue types related to the progression of CRC: benign hyperplasia (BH, intraepithelial neoplasia (IN, and carcinoma (Ca. Methods: Multispectral biopsy images of thirty CRC patients were retrospectively analyzed. Images of tissue samples were divided into three groups, based on their type (10 BH, 10 IN, and 10 Ca. An active contour model was used to segment image regions containing pathological tissues. Tissue samples were classified using a CNN containing convolution, max-pooling, and fully-connected layers. Available tissue samples were split into a training set, for learning the CNN parameters, and test set, for evaluating its performance. Results: An accuracy of 99.17% was obtained from segmented image regions, outperforming existing approaches based on traditional feature extraction, and classification techniques. Conclusions: Experimental results demonstrate the effectiveness of CNN for the classification of CRC tissue types, in particular when using presegmented regions of interest.

  8. A Dataset for Breast Cancer Histopathological Image Classification.

    Science.gov (United States)

    Spanhol, Fabio A; Oliveira, Luiz S; Petitjean, Caroline; Heutte, Laurent

    2016-07-01

    Today, medical image analysis papers require solid experiments to prove the usefulness of proposed methods. However, experiments are often performed on data selected by the researchers, which may come from different institutions, scanners, and populations. Different evaluation measures may be used, making it difficult to compare the methods. In this paper, we introduce a dataset of 7909 breast cancer histopathology images acquired on 82 patients, which is now publicly available from http://web.inf.ufpr.br/vri/breast-cancer-database. The dataset includes both benign and malignant images. The task associated with this dataset is the automated classification of these images in two classes, which would be a valuable computer-aided diagnosis tool for the clinician. In order to assess the difficulty of this task, we show some preliminary results obtained with state-of-the-art image classification systems. The accuracy ranges from 80% to 85%, showing room for improvement is left. By providing this dataset and a standardized evaluation protocol to the scientific community, we hope to gather researchers in both the medical and the machine learning field to advance toward this clinical application.

  9. Contemporary Quality of Life Issues Affecting Gynecologic Cancer Survivors

    Science.gov (United States)

    Carter, Jeanne; Penson, Richard; Barakat, Richard; Wenzel, Lari

    2015-01-01

    Gynecologic cancers account for approximately 11% of the newly diagnosed cancers in women in the United States and 18% in the world.1 The most common gynecologic malignancies occur in the uterus and endometrium (53%), ovary (25%), and cervix (14%).2 Cervical cancer is most prevalent in premenopausal women, during their childbearing years, whereas uterine and ovarian cancers tend to present in the perimenopausal or menopausal period. Vaginal and vulvar cancers and malignancies arising from gestation, or gestational trophoblastic neoplasms, occur to a lesser extent. Regardless of cancer origin or age of onset, the disease and its treatment can produce short- and long-term sequelae (ie, sexual dysfunction, infertility, or lymphedema) that adversely affect quality of life (QOL). This article outlines the primary contemporary issues or concerns that may affect QOL and offers strategies to offset or mitigate QOL disruption. These contemporary issues are identified within the domains of sexual functioning, reproductive issues, lymphedema, and the contribution of health-related QOL (HRQOL) in influential gynecologic cancer clinical trials. PMID:22244668

  10. Breast cancer and depression: issues in clinical care

    Directory of Open Access Journals (Sweden)

    Thingbaijam B. Singh

    2012-11-01

    Full Text Available Many of breast-cancer patients experience distress and most of them experience depression which may lead to amplification of physical symptoms, increased functional impairment, and poor treatment adherence. We did a review on available literature from PubMed about prevalence, distress magnitudes, coping styles, and treatment methods of major depression in women with breast cancer from 1978 to 2010. Diagnosis and treatment of depressive episodes in women with breast cancer is challenging because of overlapping symptoms and co-morbid conditions. Major depression is often under-recognized and undertreated among breast cancer patients. This review highlighted the issues on identifying and managing depression in breast cancer patients in clinical settings. (Med J Indones. 2012;21:240-6Keywords: Breast cancer, coping, depression, distress

  11. Application of wavelet transformation and adaptive neighborhood based modified backpropagation (ANMBP) for classification of brain cancer

    Science.gov (United States)

    Werdiningsih, Indah; Zaman, Badrus; Nuqoba, Barry

    2017-08-01

    This paper presents classification of brain cancer using wavelet transformation and Adaptive Neighborhood Based Modified Backpropagation (ANMBP). Three stages of the processes, namely features extraction, features reduction, and classification process. Wavelet transformation is used for feature extraction and ANMBP is used for classification process. The result of features extraction is feature vectors. Features reduction used 100 energy values per feature and 10 energy values per feature. Classifications of brain cancer are normal, alzheimer, glioma, and carcinoma. Based on simulation results, 10 energy values per feature can be used to classify brain cancer correctly. The correct classification rate of proposed system is 95 %. This research demonstrated that wavelet transformation can be used for features extraction and ANMBP can be used for classification of brain cancer.

  12. Sexuality and intimacy issues facing women with breast cancer.

    Science.gov (United States)

    Huber, Carole; Ramnarace, Teresita; McCaffrey, Ruth

    2006-11-27

    To explore the sexuality and intimacy experiences facing women with breast cancer. Published articles; OVID, PsycINFO, and Florida Atlantic University databases; Web sites; and books. Patient perceptions and knowledge of mastectomy and chemotherapy-induced menopause in regard to lifelong sexual experiences are lacking. Healthcare providers must institute much-needed education and open lines of communication. The physical and psychological results of breast cancer diagnosis and treatment alter human sexuality. Breast cancer's survival rate is at an all-time high, increasing the number of people who will be living with such issues on a daily basis and shifting the focus from acute care concerns to chronic disease concerns. Healthcare providers should assess individual patients for potential issues they may face. By identifying problems, they can challenge health care to focus on the long-term problems associated with sexuality and intimacy issues facing patients.

  13. Lung Cancer: Understanding Its Molecular Pathology and the 2015 WHO Classification.

    Science.gov (United States)

    Inamura, Kentaro

    2017-01-01

    Lung cancer is the leading cause of cancer-related death worldwide due to late diagnoses and limited treatment interventions. Recently, comprehensive molecular profiles of lung cancer have been identified. These novel characteristics have enhanced the understanding of the molecular pathology of lung cancer. The identification of driver genetic alterations and potential molecular targets has resulted in molecular-targeted therapies for an increasing number of lung cancer patients. Thus, the histopathological classification of lung cancer was modified in accordance with the increased understanding of molecular profiles. This review focuses on recent developments in the molecular profiling of lung cancer and provides perspectives on updated diagnostic concepts in the new 2015 WHO classification. The WHO classification will require additional revisions to allow for reliable, clinically meaningful tumor diagnoses as we gain a better understanding of the molecular characteristics of lung cancer.

  14. Improving breast cancer classification with mammography, supported on an appropriate variable selection analysis

    Science.gov (United States)

    Pérez, Noel; Guevara, Miguel A.; Silva, Augusto

    2013-02-01

    This work addresses the issue of variable selection within the context of breast cancer classification with mammography. A comprehensive repository of feature vectors was used including a hybrid subset gathering image-based and clinical features. It aimed to gather experimental evidence of variable selection in terms of cardinality, type and find a classification scheme that provides the best performance over the Area Under Receiver Operating Characteristics Curve (AUC) scores using the ranked features subset. We evaluated and classified a total of 300 subsets of features formed by the application of Chi-Square Discretization, Information-Gain, One-Rule and RELIEF methods in association with Feed-Forward Backpropagation Neural Network (FFBP), Support Vector Machine (SVM) and Decision Tree J48 (DTJ48) Machine Learning Algorithms (MLA) for a comparative performance evaluation based on AUC scores. A variable selection analysis was performed for Single-View Ranking and Multi-View Ranking groups of features. Features subsets representing Microcalcifications (MCs), Masses and both MCs and Masses lesions achieved AUC scores of 0.91, 0.954 and 0.934 respectively. Experimental evidence demonstrated that classification performance was improved by combining image-based and clinical features. The most important clinical and image-based features were StromaDistortion and Circularity respectively. Other less important but worth to use due to its consistency were Contrast, Perimeter, Microcalcification, Correlation and Elongation.

  15. Gender Differences in Cancer Susceptibility: An Inadequately Addressed Issue

    Science.gov (United States)

    Dorak, M. Tevfik; Karpuzoglu, Ebru

    2012-01-01

    The gender difference in cancer susceptibility is one of the most consistent findings in cancer epidemiology. Hematologic malignancies are generally more common in males and this can be generalized to most other cancers. Similar gender differences in non-malignant diseases including autoimmunity, are attributed to hormonal or behavioral differences. Even in early childhood, however, where these differences would not apply, there are differences in cancer incidence between males and females. In childhood, few cancers are more common in females, but overall, males have higher susceptibility. In Hodgkin lymphoma, the gender ratio reverses toward adolescence. The pattern that autoimmune disorders are more common in females, but cancer and infections in males suggests that the known differences in immunity may be responsible for this dichotomy. Besides immune surveillance, genome surveillance mechanisms also differ in efficiency between males and females. Other obvious differences include hormonal ones and the number of X chromosomes. Some of the differences may even originate from exposures during prenatal development. This review will summarize well-documented examples of gender effect in cancer susceptibility, discuss methodological issues in exploration of gender differences, and present documented or speculated mechanisms. The gender differential in susceptibility can give important clues for the etiology of cancers and should be examined in all genetic and non-genetic association studies. PMID:23226157

  16. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  17. Nanomaterials for environmental studies: Classification, reference material issues, and strategies for physico-chemical characterisation

    Energy Technology Data Exchange (ETDEWEB)

    Stone, Vicki, E-mail: v.stone@napier.ac.uk [School of Life Sciences, Edinburgh Napier University, 10 Colinton Road, Edinburgh EH10 5DT (United Kingdom); Nowack, Bernd [Materials, Products and the Environment Group, Empa - Swiss Federal Laboratories for Materials Testing and Research, Lerchenfeldstrasse 5 CH - 9014 St. Gallen (Switzerland); Baun, Anders [Department of Environmental Engineering, Technical University of Denmark, NanoDTU, Building 113, 2800 Kgs. Lyngby (Denmark); Brink, Nico van den [Alterra, P.O. Box 47, 6700 AA Wageningen (Netherlands); Kammer, Frank von der [Department of Environmental Geosciences, Vienna University, Althanstrasse 14, Wien 1090 (Austria); Dusinska, Maria [Health Effects Laboratory, Centre for Ecological Economics, Norwegian Institute for Air Research (NILU), Instituttveien, 18, 2027 Kjeller (Norway); Handy, Richard [University of Plymouth, Davy Building, Drake Circus, Plymouth PL4 8AA (United Kingdom); Hankin, Steven [Institute of Occupational Medicine, Research Avenue North, Riccarton, Edinburgh EH14 4AP (United Kingdom); Hasselloev, Martin [Department of Chemistry, Environmental Nanoparticle Research Group, Goeteborg University, SE-412 96 Goeteborg (Sweden); Joner, Erik [Bioforsk Soil and Environment, Fredrik A Dahls vei 20, N-1432 Aas (Norway); Fernandes, Teresa F. [School of Life Sciences, Edinburgh Napier University, 10 Colinton Road, Edinburgh EH10 5DT (United Kingdom)

    2010-03-01

    NanoImpactNet is a European Commission Framework Programme 7 (FP7) funded project that provides a forum for the discussion of current opinions on nanomaterials in relation to human and environmental issues. In September 2008, in Zurich, a NanoImpactNet environmental workshop focused on three key questions: 1.What properties should be characterised for nanomaterials used in environmental and ecotoxicology studies? 2.What reference materials should be developed for use in environmental and ecotoxicological studies? 3.Is it possible to group different nanomaterials into categories for consideration in environmental studies? Such questions have been, at least partially, addressed by other projects/workshops especially in relation to human health effects. Such projects provide a useful basis on which this workshop was based, but in this particular case these questions were reformulated in order to focus specifically on environmental studies. The workshop participants, through a series of discussion and reflection sessions, generated the conclusions listed below. The physicochemical characterisation information identified as important for environmental studies included measures of aggregation/agglomeration/dispersability, size, dissolution (solubility), surface area, surface charge, surface chemistry/composition, with the assumption that chemical composition would already be known. There is a need to have test materials for ecotoxicology, and several substances are potentially useful, including TiO{sub 2} nanoparticles, polystyrene beads labelled with fluorescent dyes, and silver nanoparticles. Some of these test materials could then be developed into certified reference materials over time. No clear consensus was reached regarding the classification of nanomaterials into categories to aid environmental studies, except that a chemistry-based classification system was a reasonable starting point, with some modifications. It was suggested, that additional work may be

  18. Gene selection for microarray cancer classification using a new evolutionary method employing artificial intelligence concepts.

    Science.gov (United States)

    Dashtban, M; Balafar, Mohammadali

    2017-03-01

    Gene selection is a demanding task for microarray data analysis. The diverse complexity of different cancers makes this issue still challenging. In this study, a novel evolutionary method based on genetic algorithms and artificial intelligence is proposed to identify predictive genes for cancer classification. A filter method was first applied to reduce the dimensionality of feature space followed by employing an integer-coded genetic algorithm with dynamic-length genotype, intelligent parameter settings, and modified operators. The algorithmic behaviors including convergence trends, mutation and crossover rate changes, and running time were studied, conceptually discussed, and shown to be coherent with literature findings. Two well-known filter methods, Laplacian and Fisher score, were examined considering similarities, the quality of selected genes, and their influences on the evolutionary approach. Several statistical tests concerning choice of classifier, choice of dataset, and choice of filter method were performed, and they revealed some significant differences between the performance of different classifiers and filter methods over datasets. The proposed method was benchmarked upon five popular high-dimensional cancer datasets; for each, top explored genes were reported. Comparing the experimental results with several state-of-the-art methods revealed that the proposed method outperforms previous methods in DLBCL dataset. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Ethical issues with colorectal cancer screening-a systematic review.

    Science.gov (United States)

    Hofmann, Bjørn

    2017-06-01

    Colorectal cancer (CRC) screening is widely recommended and implemented. However, sometimes CRC screening is not implemented despite good evidence, and some types of CRC screening are implemented despite lack of evidence. The objective of this article is to expose and elucidate relevant ethical issues in the literature on CRC screening that are important for open and transparent deliberation on CRC screening. An axiological question-based method is used for exposing and elucidating ethical issues relevant in HTA. A literature search in MEDLINE, Embase, PsycINFO, PubMed Bioethics subset, ISI Web of Knowledge, Bioethics Literature Database (BELIT), Ethics in Medicine (ETHMED), SIBIL Base dati di bioetica, LEWI Bibliographic Database on Ethics in the Sciences and Humanities, and EUROETHICS identified 870 references of which 114 were found relevant according to title and abstract. The content of the included papers were subject to ethical analysis to highlight the ethical issues, concerns, and arguments. A wide range of important ethical issues were identified. The main benefits are reduced relative CRC mortality rate, and potentially incidence rate, but there is no evidence of reduced absolute mortality rate. Potential harms are bleeding, perforation, false test results, overdetection, overdiagnosis, overtreatment (including unnecessary removal of polyps), and (rarely) death. Other important issues are related to autonomy and informed choice equity, justice, medicalization, and expanding disease. A series of important ethical issues have been identified and need to be addressed in open and transparent deliberation on CRC screening. © 2016 John Wiley & Sons, Ltd.

  20. ENRICH Forum: Ethical aNd Regulatory Issues in Cancer ResearcH

    Science.gov (United States)

    ENRICH Forum: Ethical aNd Regulatory Issues in Cancer ResearcH, designed to stimulate dialogue on ethical and regulatory issues in cancer research and promote awareness of developing policies and best practices.

  1. Lesion margin analysis for automated classification of cervical cancer lesions

    Science.gov (United States)

    Van Raad, Viara; Xue, Zhiyun; Lange, Holger

    2006-03-01

    Digital colposcopy is an emerging technology, replacing the traditional colposcope for diagnosis of cervical lesions. Incorporating automated algorithms within a digital colposcopy system can improve the reliability and the diagnostic accuracy of cervical precancer and cancer. An automated computer-aided diagnosis (CAD) system can assess the three important cervical diagnostic cues: the color, the vascular patterns and the lesion margins with quantitative measures, similar to the way colposcopists use the Reid's index in traditional colposcopy. In this work we present a novel way to analyze and classify the global and the local features of one of the three major components in colposcopy diagnosis - the lesion margins. The margins of cervical lesion can be described as 'feathered,' 'geographic,' 'satellite,' 'regular or smooth' and 'margin-in-margin,' or they can be of mixed type. As margin characterization is a complex task, we use irregularity descriptors such as compactness indices and curvature descriptors. To address the complexity of the problem, the dependency of scale and the position of the lesion on the cervical image, our method use novel Fourier energy descriptors. The conceptually complex analysis of describing lesions as 'satellite' lesions or lesions with multiple margins is performed using descriptors, where the distance, the position and the local statistical estimates of image intensity play important role. We trained this new algorithm to classify and diagnose the cervix, evaluating only the lesions. The accuracy of the results is assessed against a 'ground truth' scheme, using colposcopists' annotations and pathology results. We report the resulted accuracy of the classification method assessed against this scheme.

  2. Hypogonadism and fertility issues following primary treatment for testicular cancer.

    Science.gov (United States)

    Oldenburg, Jan

    2015-09-01

    The majority of testicular cancer (TC) patients are cured and expected to live for decades after treatment, such that knowledge about hypogonadism and fertility issues is particularly important for the group of testicular cancer survivors (TCSs). Hypogonadism and fertility issues are related to treatment intensity. In order to give an overview about hypogonadism in testicular cancer survivors (TCSs) the literature was reviewed. Testicular dysfunction was defined as inadequate spermatogenesis, as reflected by increased levels of Follicle Stimulating Hormone (FSH) and reduced fertility and/with or without insufficient testosterone (T) production with or without compensatory increased Luteinizing Hormone (LH) levels. Hypogonadism may lead to reduced sexual functioning and well-being, fertility problems, muscle weakness, loss of energy, and depression. Furthermore, hypogonadism also increases the risk of osteoporosis and is associated with the metabolic syndrome and cardiovascular disease (CVD). The hypothesized "Testicular Dysgenesis Syndrome" comprising low sperm counts, hypospadias, cryptorchidism, and finally TC, probably contributes to hypogonadism independent of applied TC treatment. Recently, an increased risk of accelerated hormonal ageing has been reported in TCSs in the very long term, i.e. 20 years after TC treatment. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. On the International Agency for Research on Cancer classification of glyphosate as a probable human carcinogen.

    Science.gov (United States)

    Tarone, Robert E

    2017-11-08

    The recent classification by International Agency for Research on Cancer (IARC) of the herbicide glyphosate as a probable human carcinogen has generated considerable discussion. The classification is at variance with evaluations of the carcinogenic potential of glyphosate by several national and international regulatory bodies. The basis for the IARC classification is examined under the assumptions that the IARC criteria are reasonable and that the body of scientific studies determined by IARC staff to be relevant to the evaluation of glyphosate by the Monograph Working Group is sufficiently complete. It is shown that the classification of glyphosate as a probable human carcinogen was the result of a flawed and incomplete summary of the experimental evidence evaluated by the Working Group. Rational and effective cancer prevention activities depend on scientifically sound and unbiased assessments of the carcinogenic potential of suspected agents. Implications of the erroneous classification of glyphosate with respect to the IARC Monograph Working Group deliberative process are discussed.

  4. Proposed Special Issue: Progress of cancer research in developing countries

    Directory of Open Access Journals (Sweden)

    T.S. Jong

    2016-10-01

    % growth in the same period, with two consecutive years of decline between 2012 and 2014. This steady upward trend of publication output from developing countries shows that researchers are becoming increasingly aware of the values of evidence-based research, without which would limit funding opportunities and restrict international collaborations, as well as partnerships.Advances in Modern Oncology Research is an Open Access journal aimed at increasing the accessibility of peer-reviewed information among researchers worldwide. The journal emphasizes on equal opportunity in scientific publishing, and is committed towards bridging the existing knowledge gap in cancer research between developed and developing countries. AMOR is keen to highlight the current challenges and opportunities of cancer research in developing countries, and the creation of a special issue dedicated to this subject is especially relevant and urgent to the broad community of cancer researchers because:(i It provides a much-needed platform to clinicians and researchers from developing countries to share important region-specific data, statistics, observations, and findings with the international community. This will not only improve the visibility of researchers from developing countries, but also enrich existing medical literature with updated information on the progress of cancer research in the developing world.(ii It gives clinicians, researchers, and policy makers from developed nations the opportunity to assess the existing and projected capability of developing countries in coping with the disease burden of cancer. Moreover, it is expected to equip stakeholders with key data and information to better manage vital resources, i.e. the allocation of funding and creation of knowledge transfer programs, moving forward.It takes collective efforts to address the escalating threat of cancer mortality and morbidity in the developing world. In order to introduce effective long-term solutions, it is

  5. Involvement of Machine Learning for Breast Cancer Image Classification: A Survey

    Directory of Open Access Journals (Sweden)

    Abdullah-Al Nahid

    2017-01-01

    Full Text Available Breast cancer is one of the largest causes of women’s death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors’ and physicians’ time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN, Logic Based classifiers such as the Random Forest (RF algorithm, Support Vector Machines (SVM, Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.

  6. Ki-67 marker useful for classification of malignant invasive ductal breast cancer

    Directory of Open Access Journals (Sweden)

    Irmawati Hassan

    2015-12-01

    The study showed that invasive ductal breast cancer with high Ki-67 index was significantly associated with high grade of malignacy. The high Ki-67 marker index can be used for classification of the grade of malignancy of invasive ductal breast cancer.

  7. Automated Classification of Lung Cancer Types from Cytological Images Using Deep Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Atsushi Teramoto

    2017-01-01

    Full Text Available Lung cancer is a leading cause of death worldwide. Currently, in differential diagnosis of lung cancer, accurate classification of cancer types (adenocarcinoma, squamous cell carcinoma, and small cell carcinoma is required. However, improving the accuracy and stability of diagnosis is challenging. In this study, we developed an automated classification scheme for lung cancers presented in microscopic images using a deep convolutional neural network (DCNN, which is a major deep learning technique. The DCNN used for classification consists of three convolutional layers, three pooling layers, and two fully connected layers. In evaluation experiments conducted, the DCNN was trained using our original database with a graphics processing unit. Microscopic images were first cropped and resampled to obtain images with resolution of 256 × 256 pixels and, to prevent overfitting, collected images were augmented via rotation, flipping, and filtering. The probabilities of three types of cancers were estimated using the developed scheme and its classification accuracy was evaluated using threefold cross validation. In the results obtained, approximately 71% of the images were classified correctly, which is on par with the accuracy of cytotechnologists and pathologists. Thus, the developed scheme is useful for classification of lung cancers from microscopic images.

  8. Prognostic classifications of lymph node involvement in lung cancer and current International Association for the Study of Lung Cancer descriptive classification in zones.

    Science.gov (United States)

    Riquet, Marc; Arame, Alex; Foucault, Christophe; Le Pimpec Barthes, Françoise

    2010-09-01

    The lymphatic drainage of solid organ tumors crosses through the lymph nodes (LNs) whose tumoral involvement may still be considered as local disease. Concerning lung cancer, LN involvement may be intrapulmonary (N1), and mediastinal and/or extra-thoracic. More than 30 years ago, mediastinal involved LNs were all considered as N2, and outside the scope of surgery. In 1978, Naruke presented an original article entitled 'Lymph node mapping and curability at various levels of metastasis in resected lung cancer', demonstrating that N2 was not a contraindication to surgery in all patients. The map permitted to localize the favorable N2 on the lung cancer ipsilateral side of the mediastinum. Several maps ensued aiming to discriminate between right and left involvement (1983), and to distinguish N2 (ipsilateral) and N3 (contralateral) mediastinal LN involvement (1983, 1986). The last map (1997 regional LN classification) was recently replaced by a descriptive classification in anatomical zones. This new LN map of the TNM classification for lung cancer is a step toward using anatomical view points which might be the best way to better understand lung cancer lymphatic spread. Nowadays, the LNs are easily identified by current radiological imaging, and their resectability may be anticipated. Each LN chain may be removed by en-bloc lymphadenectomy performed during radical lung resection, a safe procedure which seems to be more oncological based than sampling, and which avoids the source of discrepancies pointed out during the labeling of LN stations by surgeons.

  9. Automated classification of histopathology images of prostate cancer using a Bag-of-Words approach

    Science.gov (United States)

    Sanghavi, Foram M.; Agaian, Sos S.

    2016-05-01

    The goals of this paper are (1) test the Computer Aided Classification of the prostate cancer histopathology images based on the Bag-of-Words (BoW) approach (2) evaluate the performance of the classification grade 3 and 4 of the proposed method using the results of the approach proposed by the authors Khurd et al. in [9] and (3) classify the different grades of cancer namely, grade 0, 3, 4, and 5 using the proposed approach. The system performance is assessed using 132 prostate cancer histopathology of different grades. The system performance of the SURF features are also analyzed by comparing the results with SIFT features using different cluster sizes. The results show 90.15% accuracy in detection of prostate cancer images using SURF features with 75 clusters for k-mean clustering. The results showed higher sensitivity for SURF based BoW classification compared to SIFT based BoW.

  10. Evolving cancer classification in the era of personalized medicine: A primer for radiologists

    Energy Technology Data Exchange (ETDEWEB)

    O' Neill, Alibhe C.; Jagannathan, Jyothi P.; Ramaiya, Nikhil H. [Dept. of of Imaging, Dana Farber Cancer Institute, Boston (United States)

    2017-01-15

    Traditionally tumors were classified based on anatomic location but now specific genetic mutations in cancers are leading to treatment of tumors with molecular targeted therapies. This has led to a paradigm shift in the classification and treatment of cancer. Tumors treated with molecular targeted therapies often show morphological changes rather than change in size and are associated with class specific and drug specific toxicities, different from those encountered with conventional chemotherapeutic agents. It is important for the radiologists to be familiar with the new cancer classification and the various treatment strategies employed, in order to effectively communicate and participate in the multi-disciplinary care. In this paper we will focus on lung cancer as a prototype of the new molecular classification.

  11. Issues in online forum administration among multi-ethnic cancer patients.

    Science.gov (United States)

    Guevara, Enrique; Lim, Hyun Ju; Tsai, Hsiu Min

    2006-01-01

    This presentation is about practical issues and challenges in conducting online forums among multi-ethnic groups of cancer patients including Whites, Asian, and Hispanics in the U.S. The issues were identified while administrating three ethnic-specific online forums for White, Asian, and Hispanic cancer patients in the U.S. The issues included authenticity issues, language difficulties, inactive participation of ethnic minority cancer patients, culturally different attitudes towards emails and email greeting cards, and Internet access issues. Despite these issues, the findings suggest that online forums are excellent research methods to reach multi-ethnic cancer patients across the nation.

  12. Classification of Dukes' B and C colorectal cancers using expression arrays

    DEFF Research Database (Denmark)

    Frederiksen, C.M.; Knudsen, Steen; Laurberg, S.

    2003-01-01

    Purpose. Colorectal cancer is one of the most common malignancies. Substaging of the cancer is of importance not only to prognosis but also to treatment. Classification of substages based on DNA microarray technology is currently the most promising approach. We therefore investigated if gene...... expression of one of the most common malignancies, colorectal cancer, now seems to be within reach. The data indicates that it is possible at least to classify Dukes' B and C colorectal tumors with microarrays....

  13. Molecular cancer classification using a meta-sample-based regularized robust coding method.

    Science.gov (United States)

    Wang, Shu-Lin; Sun, Liuchao; Fang, Jianwen

    2014-01-01

    Previous studies have demonstrated that machine learning based molecular cancer classification using gene expression profiling (GEP) data is promising for the clinic diagnosis and treatment of cancer. Novel classification methods with high efficiency and prediction accuracy are still needed to deal with high dimensionality and small sample size of typical GEP data. Recently the sparse representation (SR) method has been successfully applied to the cancer classification. Nevertheless, its efficiency needs to be improved when analyzing large-scale GEP data. In this paper we present the meta-sample-based regularized robust coding classification (MRRCC), a novel effective cancer classification technique that combines the idea of meta-sample-based cluster method with regularized robust coding (RRC) method. It assumes that the coding residual and the coding coefficient are respectively independent and identically distributed. Similar to meta-sample-based SR classification (MSRC), MRRCC extracts a set of meta-samples from the training samples, and then encodes a testing sample as the sparse linear combination of these meta-samples. The representation fidelity is measured by the l2-norm or l1-norm of the coding residual. Extensive experiments on publicly available GEP datasets demonstrate that the proposed method is more efficient while its prediction accuracy is equivalent to existing MSRC-based methods and better than other state-of-the-art dimension reduction based methods.

  14. Changes of 2015 WHO Histological Classification of Lung Cancer 
and the Clinical Significance

    Directory of Open Access Journals (Sweden)

    Xin YANG

    2016-06-01

    Full Text Available Due in part to remarkable advances over the past decade in our understanding of lung cancer, particularly in area of medical oncology, molecular biology, and radiology, there is a pressing need for a revised classification, based not on pathology alone, but rather on an integrated multidisciplinary approach to classification of lung cancer. The 2015 World Health Organization (WHO Classification of Tumors of the Lung, Pleura, Thymus and Heart has just been published with numerous important changes from the 2004 WHO classification. The revised classification has been greatly improved in helping advance the field, increasing the impact of research, improving patient care and assisting in predicting outcome. The most significant changes will be summarized in this paper as follows: (1 main changes of lung adenocarcinoma as proposed by the 2011 International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS classification, (2 reclassifying squamous cell carcinomas into keratinizing, nonkeratinizing, and basaloid subtypes with the nonkeratinizing tumors requiring immunohistochemistry proof of squamous differentiation, (3 restricting the diagnosis of large cell carcinoma only to resected tumors that lack any clear morphologic or immunohistochemical differentiation with reclassification of the remaining former large cell carcinoma subtypes into different categories, (4 grouping of neuroendocrine tumors together in one category, (5 and the current viewpoint of histologic grading of lung cancer.

  15. Efficacy of the Kyoto Classification of Gastritis in Identifying Patients at High Risk for Gastric Cancer.

    Science.gov (United States)

    Sugimoto, Mitsushige; Ban, Hiromitsu; Ichikawa, Hitomi; Sahara, Shu; Otsuka, Taketo; Inatomi, Osamu; Bamba, Shigeki; Furuta, Takahisa; Andoh, Akira

    2017-01-01

    Objective The Kyoto gastritis classification categorizes the endoscopic characteristics of Helicobacter pylori (H. pylori) infection-associated gastritis and identifies patterns associated with a high risk of gastric cancer. We investigated its efficacy, comparing scores in patients with H. pylori-associated gastritis and with gastric cancer. Methods A total of 1,200 patients with H. pylori-positive gastritis alone (n=932), early-stage H. pylori-positive gastric cancer (n=189), and successfully treated H. pylori-negative cancer (n=79) were endoscopically graded according to the Kyoto gastritis classification for atrophy, intestinal metaplasia, fold hypertrophy, nodularity, and diffuse redness. Results The prevalence of O-II/O-III-type atrophy according to the Kimura-Takemoto classification in early-stage H. pylori-positive gastric cancer and successfully treated H. pylori-negative cancer groups was 45.1%, which was significantly higher than in subjects with gastritis alone (12.7%, pgastritis scores of atrophy and intestinal metaplasia in the H. pylori-positive cancer group were significantly higher than in subjects with gastritis alone (all pgastritis classification may thus be useful for detecting these patients.

  16. A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis

    Directory of Open Access Journals (Sweden)

    Jinyu Cong

    2017-01-01

    Full Text Available Breast cancer has been one of the main diseases that threatens women’s life. Early detection and diagnosis of breast cancer play an important role in reducing mortality of breast cancer. In this paper, we propose a selective ensemble method integrated with the KNN, SVM, and Naive Bayes to diagnose the breast cancer combining ultrasound images with mammography images. Our experimental results have shown that the selective classification method with an accuracy of 88.73% and sensitivity of 97.06% is efficient for breast cancer diagnosis. And indicator R presents a new way to choose the base classifier for ensemble learning.

  17. Legal and Policy Issues for LGBT Patients with Cancer or at Elevated Risk of Cancer.

    Science.gov (United States)

    Cahill, Sean R

    2018-02-01

    To understand the major legal and policy issues for lesbian, gay, bisexual and transgender (LGBT) cancer patients. LGBT health policy research. Major policy issues include discrimination, lack of cultural competency and clinically appropriate care, insurance coverage, family recognition, and sexual orientation and gender identity data collection. Nurses play a major role in providing affirming and competent care to LGBT cancer patients. Using correct names and pronouns with transgender patients, and collecting sexual orientation and gender identity data can send an affirming message to LGBT patients, as well as inform decision support and preventive screenings, and improve treatment outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Bladder cancer: Analysis of the 2004 WHO classification in ...

    African Journals Online (AJOL)

    schistosomal associated BCA as well as compare our findings with the 2004 WHO consensus classification of urothelial neoplasms and with other publications. Patients and methods: The archival materials of 180 urinary bladder specimens were ...

  19. An enhanced topologically significant directed random walk in cancer classification using gene expression datasets

    Directory of Open Access Journals (Sweden)

    Choon Sen Seah

    2017-12-01

    Full Text Available Microarray technology has become one of the elementary tools for researchers to study the genome of organisms. As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analysis, cancerous classification is an emerging important trend. Significant directed random walk is proposed as one of the cancerous classification approach which have higher sensitivity of risk gene prediction and higher accuracy of cancer classification. In this paper, the methodology and material used for the experiment are presented. Tuning parameter selection method and weight as parameter are applied in proposed approach. Gene expression dataset is used as the input datasets while pathway dataset is used to build a directed graph, as reference datasets, to complete the bias process in random walk approach. In addition, we demonstrate that our approach can improve sensitive predictions with higher accuracy and biological meaningful classification result. Comparison result takes place between significant directed random walk and directed random walk to show the improvement in term of sensitivity of prediction and accuracy of cancer classification.

  20. Classification of breast cancer histology images using Convolutional Neural Networks

    National Research Council Canada - National Science Library

    Teresa Araújo; Guilherme Aresta; Eduardo Castro; José Rouco; Paulo Aguiar; Catarina Eloy; António Polónia; Aurélio Campilho

    2017-01-01

    Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis...

  1. Multi-category classification using an Extreme Learning Machine for microarray gene expression cancer diagnosis.

    Science.gov (United States)

    Zhang, Runxuan; Huang, Guang-Bin; Sundararajan, Narasimhan; Saratchandran, P

    2007-01-01

    In this paper, the recently developed Extreme Learning Machine (ELM) is used for direct multicategory classification problems in the cancer diagnosis area. ELM avoids problems like local minima, improper learning rate and overfitting commonly faced by iterative learning methods and completes the training very fast. We have evaluated the multi-category classification performance of ELM on three benchmark microarray datasets for cancer diagnosis, namely, the GCM dataset, the Lung dataset and the Lymphoma dataset. The results indicate that ELM produces comparable or better classification accuracies with reduced training time and implementation complexity compared to artificial neural networks methods like conventional back-propagation ANN, Linder's SANN, and Support Vector Machine methods like SVM-OVO and Ramaswamy's SVM-OVA. ELM also achieves better accuracies for classification of individual categories.

  2. Mapping Small and Medium Sized Town in Europe: Classifications, Spatial Trends and Ontological Issues

    OpenAIRE

    Russo, Antonio

    2014-01-01

    This paper presents the various analytical steps and methods which have led to the creation of a geodatabase of urban settlements in Europe based on the integration of contiguous 1x1 square km. grid cells with specific population thresholds, and the delimitation and classification of those among them that are considered "small and medium-sized towns" (SMST) in coherence with the standard classification already produced by organisms such as DG Regio and OECD. This exercise has been one of the ...

  3. A New Feature Ensemble with a Multistage Classification Scheme for Breast Cancer Diagnosis

    Directory of Open Access Journals (Sweden)

    Idil Isikli Esener

    2017-01-01

    Full Text Available A new and effective feature ensemble with a multistage classification is proposed to be implemented in a computer-aided diagnosis (CAD system for breast cancer diagnosis. A publicly available mammogram image dataset collected during the Image Retrieval in Medical Applications (IRMA project is utilized to verify the suggested feature ensemble and multistage classification. In achieving the CAD system, feature extraction is performed on the mammogram region of interest (ROI images which are preprocessed by applying a histogram equalization followed by a nonlocal means filtering. The proposed feature ensemble is formed by concatenating the local configuration pattern-based, statistical, and frequency domain features. The classification process of these features is implemented in three cases: a one-stage study, a two-stage study, and a three-stage study. Eight well-known classifiers are used in all cases of this multistage classification scheme. Additionally, the results of the classifiers that provide the top three performances are combined via a majority voting technique to improve the recognition accuracy on both two- and three-stage studies. A maximum of 85.47%, 88.79%, and 93.52% classification accuracies are attained by the one-, two-, and three-stage studies, respectively. The proposed multistage classification scheme is more effective than the single-stage classification for breast cancer diagnosis.

  4. Comparative Study of Classification Techniques on Breast Cancer FNA Biopsy Data

    Directory of Open Access Journals (Sweden)

    George Rumbe

    2010-12-01

    Full Text Available Accurate diagnostic detection of the cancerous cells in a patient is critical and may alter the subsequent treatment and increase the chances of survival rate. Machine learning techniques have been instrumental in disease detection and are currently being used in various classification problems due to their accurate prediction performance. Various techniques may provide different desired accuracies and it is therefore imperative to use the most suitable method which provides the best desired results. This research seeks to provide comparative analysis of Support Vector Machine, Bayesian classifier and other Artificial neural network classifiers (Backpropagation, linear programming, Learning vector quantization, and K nearest neighborhood on the Wisconsin breast cancer classification problem.

  5. Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

    Science.gov (United States)

    Wutsqa, D. U.; Marwah, M.

    2017-06-01

    In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

  6. Classification of treatment-related mortality in children with cancer

    DEFF Research Database (Denmark)

    Alexander, Sarah; Pole, Jason D; Gibson, Paul

    2015-01-01

    Treatment-related mortality is an important outcome in paediatric cancer clinical trials. An international group of experts in supportive care in paediatric cancer developed a consensus-based definition of treatment-related mortality and a cause-of-death attribution system. The reliability and va...

  7. Pathogenesis of Gastric Cancer: Genetics and Molecular Classification.

    Science.gov (United States)

    Figueiredo, Ceu; Camargo, M C; Leite, Marina; Fuentes-Pananá, Ezequiel M; Rabkin, Charles S; Machado, José C

    Gastric cancer is the fifth most incident and the third most common cause of cancer-related death in the world. Infection with Helicobacter pylori is the major risk factor for this disease. Gastric cancer is the final outcome of a cascade of events that takes decades to occur and results from the accumulation of multiple genetic and epigenetic alterations. These changes are crucial for tumor cells to expedite and sustain the array of pathways involved in the cancer development, such as cell cycle, DNA repair, metabolism, cell-to-cell and cell-to-matrix interactions, apoptosis, angiogenesis, and immune surveillance. Comprehensive molecular analyses of gastric cancer have disclosed the complex heterogeneity of this disease. In particular, these analyses have confirmed that Epstein-Barr virus (EBV)-positive gastric cancer is a distinct entity. The identification of gastric cancer subtypes characterized by recognizable molecular profiles may pave the way for a more personalized clinical management and to the identification of novel therapeutic targets and biomarkers for screening, prognosis, prediction of response to treatment, and monitoring of gastric cancer progression.

  8. End of Life Issues in Cancer Cases: Ethical Aspects.

    Science.gov (United States)

    Taghavi, Afsoon; Hashemi-Bahremani, Mohammad; Hosseini, Leili; Bazmi, Shabnam

    2016-01-01

    This article investigates ethical challenges cancer patients face in the end stages of life including doctors' responsibilities, patients' rights, unexpected desires of patients and their relatives, futile treatments, and communication with patients in end stages of life. These patients are taken care of through palliative rather than curative measures. In many cases, patients in the last days of life ask their physician to terminate their illness via euthanasia which has many ethical considerations. Proponents of such mercy killing (euthanasia) believe that if the patient desires, the physician must end the life, while opponents of this issue, consider it as an act of murder incompatible with the spirit of medical sciences. The related arguments presented in this paper and other ethical issues these patients face and possible solutions for dealing with them have been proposed. It should be mentioned that this paper is more human rational and empirical and the views of the legislator are not included, though in many cases human intellectual and empirical comments are compatible with those of the legislator.

  9. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks | Center for Cancer Research

    Science.gov (United States)

    The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in clinical practice. The ANNs correctly classified all samples and identified the genes most relevant to the classification.

  10. Children's Anxiety and Phobic Disorders in School Settings: Classification, Assessment, and Intervention Issues.

    Science.gov (United States)

    King, Neville J.; Ollendick, Thomas H.

    1989-01-01

    Basic features and methodological requirements of a cognitive-behavioral perspective on childhood anxieties and phobias and their social and academic implications are discussed. Topics addressed include disorder classification, multimethod problem solving, data collection treatment techniques, and the role of teachers. (TJH)

  11. Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI

    Energy Technology Data Exchange (ETDEWEB)

    Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospital, Departments of Radiology, London (United Kingdom); Alkalbani, Jokha; Sidhu, Harbir Singh [University College London, Centre for Medical Imaging, London (United Kingdom); Abd-Alazeez, Mohamed; Ahmed, Hashim U.; Emberton, Mark [University College London, Research Department of Urology, Division of Surgery and Interventional Science, London (United Kingdom); Kirkham, Alex [University College London Hospital, Departments of Radiology, London (United Kingdom); Freeman, Alex [University College London Hospital, Department of Histopathology, London (United Kingdom)

    2015-09-15

    To assess the interchangeability of zone-specific (peripheral-zone (PZ) and transition-zone (TZ)) multiparametric-MRI (mp-MRI) logistic-regression (LR) models for classification of prostate cancer. Two hundred and thirty-one patients (70 TZ training-cohort; 76 PZ training-cohort; 85 TZ temporal validation-cohort) underwent mp-MRI and transperineal-template-prostate-mapping biopsy. PZ and TZ uni/multi-variate mp-MRI LR-models for classification of significant cancer (any cancer-core-length (CCL) with Gleason > 3 + 3 or any grade with CCL ≥ 4 mm) were derived from the respective cohorts and validated within the same zone by leave-one-out analysis. Inter-zonal performance was tested by applying TZ models to the PZ training-cohort and vice-versa. Classification performance of TZ models for TZ cancer was further assessed in the TZ validation-cohort. ROC area-under-curve (ROC-AUC) analysis was used to compare models. The univariate parameters with the best classification performance were the normalised T2 signal (T2nSI) within the TZ (ROC-AUC = 0.77) and normalized early contrast-enhanced T1 signal (DCE-nSI) within the PZ (ROC-AUC = 0.79). Performance was not significantly improved by bi-variate/tri-variate modelling. PZ models that contained DCE-nSI performed poorly in classification of TZ cancer. The TZ model based solely on maximum-enhancement poorly classified PZ cancer. LR-models dependent on DCE-MRI parameters alone are not interchangeable between prostatic zones; however, models based exclusively on T2 and/or ADC are more robust for inter-zonal application. (orig.)

  12. Optimization models for cancer classification: extracting gene interaction information from microarray expression data.

    Science.gov (United States)

    Antonov, Alexey V; Tetko, Igor V; Mader, Michael T; Budczies, Jan; Mewes, Hans W

    2004-03-22

    Microarray data appear particularly useful to investigate mechanisms in cancer biology and represent one of the most powerful tools to uncover the genetic mechanisms causing loss of cell cycle control. Recently, several different methods to employ microarray data as a diagnostic tool in cancer classification have been proposed. These procedures take changes in the expression of particular genes into account but do not consider disruptions in certain gene interactions caused by the tumor. It is probable that some genes participating in tumor development do not change their expression level dramatically. Thus, they cannot be detected by simple classification approaches used previously. For these reasons, a classification procedure exploiting information related to changes in gene interactions is needed. We propose a MAximal MArgin Linear Programming (MAMA) method for the classification of tumor samples based on microarray data. This procedure detects groups of genes and constructs models (features) that strongly correlate with particular tumor types. The detected features include genes whose functional relations are changed for particular cancer types. The proposed method was tested on two publicly available datasets and demonstrated a prediction ability superior to previously employed classification schemes. The MAMA system was developed using the linear programming system LINDO http://www.lindo.com. A Perl script that specifies the optimization problem for this software is available upon request from the authors.

  13. High dimensional multiclass classification with applications to cancer diagnosis

    DEFF Research Database (Denmark)

    Vincent, Martin

    Probabilistic classifiers are introduced and it is shown that the only regular linear probabilistic classifier with convex risk is multinomial regression. Penalized empirical risk minimization is introduced and used to construct supervised learning methods for probabilistic classifiers. A sparse...... group lasso penalized approach to high dimensional multinomial classification is presented. On different real data examples it is found that this approach clearly outperforms multinomial lasso in terms of error rate and features included in the model. An efficient coordinate descent algorithm...... is developed and the convergence is established. This algorithm is implemented in the msgl R package. Examples of high dimensional multiclass problems are studied, in particular examples of multiclass classification based on gene expression measurements. One such example is the clinically important - problem...

  14. Cancer Hallmark Text Classification Using Convolutional Neural Networks

    OpenAIRE

    Baker, Simon; Korhonen, Anna-Leena; Pyysalo, S

    2017-01-01

    Methods based on deep learning approaches have recently achieved state-of-the-art performance in a range of machine learning tasks and are increasingly applied to natural language processing (NLP). Despite strong results in various established NLP tasks involving general domain texts, here is only limited work applying these models to biomedical NLP. In this paper, we consider a Convolutional Neural Network (CNN) approach to biomedical text classification. Evaluation using a recently intr...

  15. Classification of normal and abnormal images of lung cancer

    Science.gov (United States)

    Bhatnagar, Divyesh; Tiwari, Amit Kumar; Vijayarajan, V.; Krishnamoorthy, A.

    2017-11-01

    To find the exact symptoms of lung cancer is difficult, because of the formation of the most cancers tissues, wherein large structure of tissues is intersect in a different way. This problem can be evaluated with the help of digital images. In this strategy images will be examined with basic operation of PCA Algorithm. In this paper, GLCM method is used for pre-processing of the snap shots and function extraction system and to test the level of diseases of a patient in its premature stage get to know it is regular or unusual. With the help of result stage of cancer will be evaluated. With the help of dataset and result survival rate of cancer patient can be estimated. Result is based totally on the precise and wrong arrangement of the patterns of tissues.

  16. Fully automatic classification of breast cancer microarray images

    Directory of Open Access Journals (Sweden)

    Nastaran Dehghan Khalilabad

    2016-09-01

    Full Text Available A microarray image is used as an accurate method for diagnosis of cancerous diseases. The aim of this research is to provide an approach for detection of breast cancer type. First, raw data is extracted from microarray images. Determining the exact location of each gene is carried out using image processing techniques. Then, by the sum of the pixels associated with each gene, the amount of “genes expression” is extracted as raw data. To identify more effective genes, information gain method on the set of raw data is used. Finally, the type of cancer can be recognized via analyzing the obtained data using a decision tree. The proposed approach has an accuracy of 95.23% in diagnosing the breast cancer types.

  17. Comparison of linear discriminant analysis methods for the classification of cancer based on gene expression data.

    Science.gov (United States)

    Huang, Desheng; Quan, Yu; He, Miao; Zhou, Baosen

    2009-12-10

    More studies based on gene expression data have been reported in great detail, however, one major challenge for the methodologists is the choice of classification methods. The main purpose of this research was to compare the performance of linear discriminant analysis (LDA) and its modification methods for the classification of cancer based on gene expression data. The classification performance of linear discriminant analysis (LDA) and its modification methods was evaluated by applying these methods to six public cancer gene expression datasets. These methods included linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), shrinkage centroid regularized discriminant analysis (SCRDA), shrinkage linear discriminant analysis (SLDA) and shrinkage diagonal discriminant analysis (SDDA). The procedures were performed by software R 2.80. PAM picked out fewer feature genes than other methods from most datasets except from Brain dataset. For the two methods of shrinkage discriminant analysis, SLDA selected more genes than SDDA from most datasets except from 2-class lung cancer dataset. When comparing SLDA with SCRDA, SLDA selected more genes than SCRDA from 2-class lung cancer, SRBCT and Brain dataset, the result was opposite for the rest datasets. The average test error of LDA modification methods was lower than LDA method. The classification performance of LDA modification methods was superior to that of traditional LDA with respect to the average error and there was no significant difference between theses modification methods.

  18. Classification of Cancer Primary Sites Using Machine Learning and Somatic Mutations

    Directory of Open Access Journals (Sweden)

    Yukun Chen

    2015-01-01

    Full Text Available An accurate classification of human cancer, including its primary site, is important for better understanding of cancer and effective therapeutic strategies development. The available big data of somatic mutations provides us a great opportunity to investigate cancer classification using machine learning. Here, we explored the patterns of 1,760,846 somatic mutations identified from 230,255 cancer patients along with gene function information using support vector machine. Specifically, we performed a multiclass classification experiment over the 17 tumor sites using the gene symbol, somatic mutation, chromosome, and gene functional pathway as predictors for 6,751 subjects. The performance of the baseline using only gene features is 0.57 in accuracy. It was improved to 0.62 when adding the information of mutation and chromosome. Among the predictable primary tumor sites, the prediction of five primary sites (large intestine, liver, skin, pancreas, and lung could achieve the performance with more than 0.70 in F-measure. The model of the large intestine ranked the first with 0.87 in F-measure. The results demonstrate that the somatic mutation information is useful for prediction of primary tumor sites with machine learning modeling. To our knowledge, this study is the first investigation of the primary sites classification using machine learning and somatic mutation data.

  19. Classification of Cancer Primary Sites Using Machine Learning and Somatic Mutations.

    Science.gov (United States)

    Chen, Yukun; Sun, Jingchun; Huang, Liang-Chin; Xu, Hua; Zhao, Zhongming

    2015-01-01

    An accurate classification of human cancer, including its primary site, is important for better understanding of cancer and effective therapeutic strategies development. The available big data of somatic mutations provides us a great opportunity to investigate cancer classification using machine learning. Here, we explored the patterns of 1,760,846 somatic mutations identified from 230,255 cancer patients along with gene function information using support vector machine. Specifically, we performed a multiclass classification experiment over the 17 tumor sites using the gene symbol, somatic mutation, chromosome, and gene functional pathway as predictors for 6,751 subjects. The performance of the baseline using only gene features is 0.57 in accuracy. It was improved to 0.62 when adding the information of mutation and chromosome. Among the predictable primary tumor sites, the prediction of five primary sites (large intestine, liver, skin, pancreas, and lung) could achieve the performance with more than 0.70 in F-measure. The model of the large intestine ranked the first with 0.87 in F-measure. The results demonstrate that the somatic mutation information is useful for prediction of primary tumor sites with machine learning modeling. To our knowledge, this study is the first investigation of the primary sites classification using machine learning and somatic mutation data.

  20. 3rd St. Gallen EORTC Gastrointestinal Cancer Conference: Consensus recommendations on controversial issues in the primary treatment of pancreatic cancer.

    Science.gov (United States)

    Lutz, Manfred P; Zalcberg, John R; Ducreux, Michel; Aust, Daniela; Bruno, Marco J; Büchler, Markus W; Delpero, Jean-Robert; Gloor, Beat; Glynne-Jones, Rob; Hartwig, Werner; Huguet, Florence; Laurent-Puig, Pierre; Lordick, Florian; Maisonneuve, Patrick; Mayerle, Julia; Martignoni, Marc; Neoptolemos, John; Rhim, Andrew D; Schmied, Bruno M; Seufferlein, Thomas; Werner, Jens; van Laethem, Jean-Luc; Otto, Florian

    2017-07-01

    The primary treatment of pancreatic cancer was the topic of the 3rd St. Gallen Conference 2016. A multidisciplinary panel reviewed the current evidence and discussed controversial issues in a moderated consensus session. Here we report on the key expert recommendations. It was generally accepted that radical surgical resection followed by adjuvant chemotherapy offers the only evidence-based treatment with a chance for cure. Initial staging should classify localised tumours as resectable or unresectable (i.e. locally advanced pancreatic cancer) although there remains a large grey-zone of potentially resectable disease between these two categories which has recently been named as borderline resectable, a concept which was generally accepted by the panel members. However, the definition of these borderline-resectable (BR) tumours varies between classifications due to their focus on either (i) technical hurdles (e.g. the feasibility of vascular resection) or (ii) oncological outcome (e.g. predicting the risk of a R1 resection and/or occult metastases). The resulting expert discussion focussed on imaging standards as well as the value of pretherapeutic laparoscopy. Indications for biliary drainage were seen especially before neoadjuvant therapy. Following standard resection, the panel unanimously voted for the use of adjuvant chemotherapy after R0 resection and considered it as a reasonable standard of care after R1 resection, even though the optimal pathologic evaluation and the definition of R0/R1 was the issue of an ongoing debate. The general concept of BR tumours was considered as a good basis to select patients for preoperative therapy, albeit its current impact on the therapeutic strategy was far less clear. Main focus of the conference was to discuss the limits of surgical resection and to identify ways to standardise procedures and to improve curative outcome, including adjuvant and perioperative treatment. Copyright © 2017 The Authors. Published by Elsevier

  1. CAMUR: Knowledge extraction from RNA-seq cancer data through equivalent classification rules.

    Science.gov (United States)

    Cestarelli, Valerio; Fiscon, Giulia; Felici, Giovanni; Bertolazzi, Paola; Weitschek, Emanuel

    2016-03-01

    Nowadays, knowledge extraction methods from Next Generation Sequencing data are highly requested. In this work, we focus on RNA-seq gene expression analysis and specifically on case-control studies with rule-based supervised classification algorithms that build a model able to discriminate cases from controls. State of the art algorithms compute a single classification model that contains few features (genes). On the contrary, our goal is to elicit a higher amount of knowledge by computing many classification models, and therefore to identify most of the genes related to the predicted class. We propose CAMUR, a new method that extracts multiple and equivalent classification models. CAMUR iteratively computes a rule-based classification model, calculates the power set of the genes present in the rules, iteratively eliminates those combinations from the data set, and performs again the classification procedure until a stopping criterion is verified. CAMUR includes an ad-hoc knowledge repository (database) and a querying tool.We analyze three different types of RNA-seq data sets (Breast, Head and Neck, and Stomach Cancer) from The Cancer Genome Atlas (TCGA) and we validate CAMUR and its models also on non-TCGA data. Our experimental results show the efficacy of CAMUR: we obtain several reliable equivalent classification models, from which the most frequent genes, their relationships, and the relation with a particular cancer are deduced. dmb.iasi.cnr.it/camur.php emanuel@iasi.cnr.it Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  2. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

    Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

  3. Current issues and future perspectives of gastric cancer screening

    OpenAIRE

    Hamashima, Chisato

    2014-01-01

    Gastric cancer remains the second leading cause of cancer death worldwide. About half of the incidence of gastric cancer is observed in East Asian countries, which show a higher mortality than other countries. The effectiveness of 3 new gastric cancer screening techniques, namely, upper gastrointestinal endoscopy, serological testing, and “screen and treat” method were extensively reviewed. Moreover, the phases of development for cancer screening were analyzed on the basis of the biomarker de...

  4. Cancer screening in the United States, 2017: A review of current American Cancer Society guidelines and current issues in cancer screening.

    Science.gov (United States)

    Smith, Robert A; Andrews, Kimberly S; Brooks, Durado; Fedewa, Stacey A; Manassaram-Baptiste, Deana; Saslow, Debbie; Brawley, Otis W; Wender, Richard C

    2017-03-01

    Answer questions and earn CME/CNE Each year, the American Cancer Society publishes a summary of its guidelines for early cancer detection, data and trends in cancer screening rates, and select issues related to cancer screening. In this issue of the journal, the authors summarize current American Cancer Society cancer screening guidelines, describe an update of their guideline for using human papillomavirus vaccination for cancer prevention, describe updates in US Preventive Services Task Force recommendations for breast and colorectal cancer screening, discuss interim findings from the UK Collaborative Trial on Ovarian Cancer Screening, and provide the latest data on utilization of cancer screening from the National Health Interview Survey. CA Cancer J Clin 2017;67:100-121. © 2017 American Cancer Society. © 2017 American Cancer Society.

  5. Epigenetic and genetic alterations-based molecular classification of head and neck cancer.

    Science.gov (United States)

    Feng, Zhien; Xu, Qin; Chen, Wantao

    2012-04-01

    The long-term survival rates for patients diagnosed with advanced head and neck cancer (HNC) remain poor. Many perplexing factors, including etiology and comorbidity, lead to different molecular malfunctions of HNC cells and determine the prognosis of the disease. Traditional diagnostic methods are limited in that they fail to provide an effective classification diagnosis, such as a more precise prediction of prognosis and decisions for personalized treatment regimens. Recently, molecular biology techniques, especially epigenetic and genetic techniques, have been developed that have enabled us to gain a greater insight into the molecular pathways underlying the cancers. Translating the research into a format that will facilitate effective molecular classification, support personalized treatment and determine prognosis remains a challenge. In this review, the authors provide an overview of cancer epigenetic and genetic alterations, tissue banks, and several promising biomarkers or candidates that may ultimately prove to be beneficial in a clinical setting for patients with HNC.

  6. Exercise intensity classification in cancer patients undergoing allogeneic HCT.

    Science.gov (United States)

    Kuehl, Rea; Scharhag-Rosenberger, Friederike; Schommer, Kai; Schmidt, Martina E; Dreger, Peter; Huber, Gerhard; Bohus, Martin; Ulrich, Cornelia M; Wiskemann, Joachim

    2015-05-01

    Exercise intervention studies during and after cancer treatment show beneficial effects for various physical and psychosocial outcomes. Current exercise intensity guidelines for cancer patients are rather general and have been adapted from American College of Sports Medicine (ACSM) recommendations for healthy individuals. Intensive cancer treatment regimens such as allogeneic hematopoietic stem cell transplantation (allo-HCT) may change the cardiovascular response to acute exercise. Therefore, we evaluated the relationships between %V˙O2 reserve (%V˙O2R, reference) and %HRR, %HRmax, and %V˙O2max and compared calculated intensities with given intensities by ACSM. Measurements before and 180 d after allo-HCT from a randomized controlled trial were used. Only patients who reached maximal effort and at least two exercise stages in our maximal incremental cycling test were included. Before allo-HCT, 106 patients were included, and 180 d after treatment, 49 patients met our inclusion criteria. Individual regression lines were calculated with V˙O2R as the reference. Calculated exercise intensities for endurance training prescription were compared with ACSM values. Before allo-HCT, %HRR values of patients were significantly lower than ACSM values, and %HRmax and %V˙O2max values were significantly higher (except 90% HRmax, which was significantly lower, all P exercise intensity recommendations for endurance training may not be applicable for cancer patients during and 180 d after allo-HCT because they may not meet the targeted intensity class, with the exception of %HRR 180 d after allo-HCT.

  7. Update on epidemiology classification, and management of thyroid cancer

    Directory of Open Access Journals (Sweden)

    Heitham Gheriani

    2006-06-01

    Full Text Available Thyroid cancer represents approximately 0.5–1% of all human malignancy1. In the UK the incidence of thyroid cancer is 2-3 per 100,000 populations 2. In geographical areas of low iodine intake and in areas exposed to nuclear disasters the incidence of thyroid cancer is higher. Benign thyroid conditions are much more common. In the UK approximately 8 % of the population have nodular thyroid disease2. Nodular thyroid disease increases with age and is also more common in females and in geographical areas of low iodine intake. Primary thyroid malignancy can be broadly divided into 2 groups. The first group, which generally have much better prognosis, are the well-differentiated thyroid carcinoma, which includes papillary carcinoma, follicular carcinoma and Hürthle cell tumours. The second group includes the poorly differentiated thyroid carcinoma like medullary thyroid carcinoma and the anaplastic thyroid carcinoma. Other rare tumours such as sarcomas, lymphomas and the extremely rare primary squamous cell carcinoma of the thyroid should be included in the second group. Secondary or metastatic thyroid cancer can be from breast, lung, colon and kidney malignancies.

  8. Breast cancer tumor classification using LASSO method selection approach

    Energy Technology Data Exchange (ETDEWEB)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  9. Usage of case-based reasoning, neural network and adaptive neuro-fuzzy inference system classification techniques in breast cancer dataset classification diagnosis.

    Science.gov (United States)

    Huang, Mei-Ling; Hung, Yung-Hsiang; Lee, Wen-Ming; Li, R K; Wang, Tzu-Hao

    2012-04-01

    Breast cancer is a common to females worldwide. Today, technological advancements in cancer treatment innovations have increased the survival rates. Many theoretical and experimental studies have shown that a multiple classifier system is an effective technique for reducing prediction errors. This study compared the particle swarm optimizer (PSO) based artificial neural network (ANN), the adaptive neuro-fuzzy inference system (ANFIS), and a case-based reasoning (CBR) classifier with a logistic regression model and decision tree model. It also applied three classification techniques to the Mammographic Mass Data Set, and measured its improvements in accuracy and classification errors. The experimental results showed that, the best CBR-based classification accuracy is 83.60%, and the classification accuracies of the PSO-based ANN classifier and ANFIS are 91.10% and 92.80%, respectively.

  10. Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis.

    Science.gov (United States)

    Al-Rajab, Murad; Lu, Joan; Xu, Qiang

    2017-07-01

    This paper examines the accuracy and efficiency (time complexity) of high performance genetic data feature selection and classification algorithms for colon cancer diagnosis. The need for this research derives from the urgent and increasing need for accurate and efficient algorithms. Colon cancer is a leading cause of death worldwide, hence it is vitally important for the cancer tissues to be expertly identified and classified in a rapid and timely manner, to assure both a fast detection of the disease and to expedite the drug discovery process. In this research, a three-phase approach was proposed and implemented: Phases One and Two examined the feature selection algorithms and classification algorithms employed separately, and Phase Three examined the performance of the combination of these. It was found from Phase One that the Particle Swarm Optimization (PSO) algorithm performed best with the colon dataset as a feature selection (29 genes selected) and from Phase Two that the Support Vector Machine (SVM) algorithm outperformed other classifications, with an accuracy of almost 86%. It was also found from Phase Three that the combined use of PSO and SVM surpassed other algorithms in accuracy and performance, and was faster in terms of time analysis (94%). It is concluded that applying feature selection algorithms prior to classification algorithms results in better accuracy than when the latter are applied alone. This conclusion is important and significant to industry and society. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. New classification of acute myeloid leukemia and precursor-related neoplasms: changes and unsolved issues.

    Science.gov (United States)

    Falini, Brunangelo; Tiacci, Enrico; Martelli, Maria Paola; Ascani, Stefano; Pileri, Stefano A

    2010-10-01

    The World Health Organization (WHO) classification of lympho-hematopoietic neoplasms is increasingly based on genetic criteria. Here, we focus on changes that, as compared to the 2001 edition, were introduced into the 2008 WHO classification of acute myeloid leukemia (AML) and related precursor neoplasms. The category of AML with recurrent genetic abnormalities was expanded to account for 60% of AML by adding three distinct entities, i.e., AML with t(6,9), inv(3), or t(1;22), and two provisional entities, i.e., AML with mutated NPM1 or CEBPA. These changes have greatly modified the approaches to diagnosis and prognostic stratification of AML patients. To emphasize the need of various parameters for diagnosis, including myelodysplasia (MD)-related cytogenetic abnormalities, history of myelodysplasia or myelodysplasia/myeloproliferative neoplasm, and multilineage dysplasia, the category of "AML with multilineage dysplasia" was re-named AML with MD-related changes. Finally, we describe the unique characteristics of myeloid proliferations associated with Down syndrome and blastic plasmacytoid dendritic cell neoplasm.

  12. Call for a Computer-Aided Cancer Detection and Classification Research Initiative in Oman.

    Science.gov (United States)

    Mirzal, Andri; Chaudhry, Shafique Ahmad

    2016-01-01

    Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

  13. Alternative Polyadenylation Patterns for Novel Gene Discovery and Classification in Cancer

    Directory of Open Access Journals (Sweden)

    Oguzhan Begik

    2017-07-01

    Full Text Available Certain aspects of diagnosis, prognosis, and treatment of cancer patients are still important challenges to be addressed. Therefore, we propose a pipeline to uncover patterns of alternative polyadenylation (APA, a hidden complexity in cancer transcriptomes, to further accelerate efforts to discover novel cancer genes and pathways. Here, we analyzed expression data for 1045 cancer patients and found a significant shift in usage of poly(A signals in common tumor types (breast, colon, lung, prostate, gastric, and ovarian compared to normal tissues. Using machine-learning techniques, we further defined specific subsets of APA events to efficiently classify cancer types. Furthermore, APA patterns were associated with altered protein levels in patients, revealed by antibody-based profiling data, suggesting functional significance. Overall, our study offers a computational approach for use of APA in novel gene discovery and classification in common tumor types, with important implications in basic research, biomarker discovery, and precision medicine approaches.

  14. Immunogenomic Classification of Colorectal Cancer and Therapeutic Implications

    Directory of Open Access Journals (Sweden)

    Jessica Roelands

    2017-10-01

    Full Text Available The immune system has a substantial effect on colorectal cancer (CRC progression. Additionally, the response to immunotherapeutics and conventional treatment options (e.g., chemotherapy, radiotherapy and targeted therapies is influenced by the immune system. The molecular characterization of colorectal cancer (CRC has led to the identification of favorable and unfavorable immunological attributes linked to clinical outcome. With the definition of consensus molecular subtypes (CMSs based on transcriptomic profiles, multiple characteristics have been proposed to be responsible for the development of the tumor immune microenvironment and corresponding mechanisms of immune escape. In this review, a detailed description of proposed immune phenotypes as well as their interaction with different therapeutic modalities will be provided. Finally, possible strategies to shift the CRC immune phenotype towards a reactive, anti-tumor orientation are proposed per CMS.

  15. Informative Gene Selection for Cancer Classification with Microarray Data Using a Metaheuristic Framework

    Science.gov (United States)

    M, Pyingkodi; R, Thangarajan

    2018-02-26

    Objective: Cancer diagnosis is one of the most vital emerging clinical applications of microarray data. Due to the high dimensionality, gene selection is an important step for improving expression data classification performance. There is therefore a need for effective methods to select informative genes for prediction and diagnosis of cancer. The main objective of this research was to derive a heuristic approach to select highly informative genes. Methods: A metaheuristic approach with a Genetic Algorithm with Levy Flight (GA-LV) was applied for classification of cancer genes in microarrays. The experimental results were analyzed with five major cancer gene expression benchmark datasets. Result: GA-LV proved superior to GA and statistical approaches, with 100% accuracy for the dataset for Leukemia, Lung and Lymphoma. For Prostate and Colon datasets the GA-LV was 99.5% and 99.2% accurate, respectively. Conclusion: The experimental results show that the proposed approach is suitable for effective gene selection with all benchmark datasets, removing irrelevant and redundant genes to improve classification accuracy. Creative Commons Attribution License

  16. Open issues in psychiatric nosology: A conceptual framework of the American classification of mental disorders (DSM

    Directory of Open Access Journals (Sweden)

    Jović Vladimir M.

    2014-01-01

    Full Text Available New, Fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM -5 , was published In May 2013, by the American Psychiatric Association, which was expected to bring a new paradigm shift in the understanding of mental disorders. This document in its main presumptions did not depart significantly from the Third edition in 1980. The aim of this paper is to provide an overview of the conceptual framework of this classification, elements of which could be enlisted as following: mental disorders are conceptualized as a diseases by the biomedical model , and as such they are clearly separated from the 'healthy' mental functioning; they are the consequence of a pathological processes in the structure and functioning of the brain, and manifested by clusters of symptoms and signs of disease which are assumed to have a specific etiology. This paper provides an overview of the current discussions and criticism of this paradigm that is currently dominant in academic psychiatry .

  17. Nanomaterials for environmental studies: Classification, reference material issues, and strategies for physico-chemical characterisation

    NARCIS (Netherlands)

    Stone, V.; Nowack, B.; Baun, A.; Brink, van den N.W.; Kammer, von den F.; Dusinska, M.; Handy, R.; Hankin, S.; Hassellöv, M.; Joner, E.; Fernandes, T.F.

    2010-01-01

    NanoImpactNet is a European Commission Framework Programme 7 (FP7) funded project that provides a forum for the discussion of current opinions on nanomaterials in relation to human and environmental issues. In September 2008, in Zurich, a NanoImpactNet environmental workshop focused on three key

  18. AN ADABOOST OPTIMIZED CCFIS BASED CLASSIFICATION MODEL FOR BREAST CANCER DETECTION

    Directory of Open Access Journals (Sweden)

    CHANDRASEKAR RAVI

    2017-06-01

    Full Text Available Classification is a Data Mining technique used for building a prototype of the data behaviour, using which an unseen data can be classified into one of the defined classes. Several researchers have proposed classification techniques but most of them did not emphasis much on the misclassified instances and storage space. In this paper, a classification model is proposed that takes into account the misclassified instances and storage space. The classification model is efficiently developed using a tree structure for reducing the storage complexity and uses single scan of the dataset. During the training phase, Class-based Closed Frequent ItemSets (CCFIS were mined from the training dataset in the form of a tree structure. The classification model has been developed using the CCFIS and a similarity measure based on Longest Common Subsequence (LCS. Further, the Particle Swarm Optimization algorithm is applied on the generated CCFIS, which assigns weights to the itemsets and their associated classes. Most of the classifiers are correctly classifying the common instances but they misclassify the rare instances. In view of that, AdaBoost algorithm has been used to boost the weights of the misclassified instances in the previous round so as to include them in the training phase to classify the rare instances. This improves the accuracy of the classification model. During the testing phase, the classification model is used to classify the instances of the test dataset. Breast Cancer dataset from UCI repository is used for experiment. Experimental analysis shows that the accuracy of the proposed classification model outperforms the PSOAdaBoost-Sequence classifier by 7% superior to other approaches like Naïve Bayes Classifier, Support Vector Machine Classifier, Instance Based Classifier, ID3 Classifier, J48 Classifier, etc.

  19. Current issues and future perspectives of gastric cancer screening

    Science.gov (United States)

    Hamashima, Chisato

    2014-01-01

    Gastric cancer remains the second leading cause of cancer death worldwide. About half of the incidence of gastric cancer is observed in East Asian countries, which show a higher mortality than other countries. The effectiveness of 3 new gastric cancer screening techniques, namely, upper gastrointestinal endoscopy, serological testing, and “screen and treat” method were extensively reviewed. Moreover, the phases of development for cancer screening were analyzed on the basis of the biomarker development road map. Several observational studies have reported the effectiveness of endoscopic screening in reducing mortality from gastric cancer. On the other hand, serologic testing has mainly been used for targeting the high-risk group for gastric cancer. To date, the effectiveness of new techniques for gastric cancer screening has remained limited. However, endoscopic screening is presently in the last trial phase of development before their introduction to population-based screening. To effectively introduce new techniques for gastric cancer screening in a community, incidence and mortality reduction from gastric cancer must be initially and thoroughly evaluated by conducting reliable studies. In addition to effectiveness evaluation, the balance of benefits and harms must be carefully assessed before introducing these new techniques for population-based screening. PMID:25320514

  20. Current issues and future perspectives of gastric cancer screening.

    Science.gov (United States)

    Hamashima, Chisato

    2014-10-14

    Gastric cancer remains the second leading cause of cancer death worldwide. About half of the incidence of gastric cancer is observed in East Asian countries, which show a higher mortality than other countries. The effectiveness of 3 new gastric cancer screening techniques, namely, upper gastrointestinal endoscopy, serological testing, and "screen and treat" method were extensively reviewed. Moreover, the phases of development for cancer screening were analyzed on the basis of the biomarker development road map. Several observational studies have reported the effectiveness of endoscopic screening in reducing mortality from gastric cancer. On the other hand, serologic testing has mainly been used for targeting the high-risk group for gastric cancer. To date, the effectiveness of new techniques for gastric cancer screening has remained limited. However, endoscopic screening is presently in the last trial phase of development before their introduction to population-based screening. To effectively introduce new techniques for gastric cancer screening in a community, incidence and mortality reduction from gastric cancer must be initially and thoroughly evaluated by conducting reliable studies. In addition to effectiveness evaluation, the balance of benefits and harms must be carefully assessed before introducing these new techniques for population-based screening.

  1. Breast cancer cell nuclei classification in histopathology images using deep neural networks.

    Science.gov (United States)

    Feng, Yangqin; Zhang, Lei; Yi, Zhang

    2018-02-01

    Cell nuclei classification in breast cancer histopathology images plays an important role in effective diagnose since breast cancer can often be characterized by its expression in cell nuclei. However, due to the small and variant sizes of cell nuclei, and heavy noise in histopathology images, traditional machine learning methods cannot achieve desirable recognition accuracy. To address this challenge, this paper aims to present a novel deep neural network which performs representation learning and cell nuclei recognition in an end-to-end manner. The proposed model hierarchically maps raw medical images into a latent space in which robustness is achieved by employing a stacked denoising autoencoder. A supervised classifier is further developed to improve the discrimination of the model by maximizing inter-subject separability in the latent space. The proposed method involves a cascade model which jointly learns a set of nonlinear mappings and a classifier from the given raw medical images. Such an on-the-shelf learning strategy makes obtaining discriminative features possible, thus leading to better recognition performance. Extensive experiments with benign and malignant breast cancer datasets are conducted to verify the effectiveness of the proposed method. Better performance was obtained when compared with other feature extraction methods, and higher recognition rate was achieved when compared with other seven classification methods. We propose an end-to-end DNN model for cell nuclei and non-nuclei classification of histopathology images. It demonstrates that the proposed method can achieve promising performance in cell nuclei classification, and the proposed method is suitable for the cell nuclei classification task.

  2. Cross-Disciplinary Analysis of Lymph Node Classification in Lung Cancer on CT Scanning.

    Science.gov (United States)

    El-Sherief, Ahmed H; Lau, Charles T; Obuchowski, Nancy A; Mehta, Atul C; Rice, Thomas W; Blackstone, Eugene H

    2017-04-01

    Accurate and consistent regional lymph node classification is an important element in the staging and multidisciplinary management of lung cancer. Regional lymph node definition sets-lymph node maps-have been created to standardize regional lymph node classification. In 2009, the International Association for the Study of Lung Cancer (IASLC) introduced a lymph node map to supersede all preexisting lymph node maps. Our aim was to study if and how lung cancer specialists apply the IASLC lymph node map when classifying thoracic lymph nodes encountered on CT scans during lung cancer staging. From April 2013 through July 2013, invitations were distributed to all members of the Fleischner Society, Society of Thoracic Radiology, General Thoracic Surgical Club, and the American Association of Bronchology and Interventional Pulmonology to participate in an anonymous online image-based and text-based 20-question survey regarding lymph node classification for lung cancer staging on CT imaging. Three hundred thirty-seven people responded (approximately 25% participation). Respondents consisted of self-reported thoracic radiologists (n = 158), thoracic surgeons (n = 102), and pulmonologists who perform endobronchial ultrasonography (n = 77). Half of the respondents (50%; 95% CI, 44%-55%) reported using the IASLC lymph node map in daily practice, with no significant differences between subspecialties. A disparity was observed between the IASLC definition sets and their interpretation and application on CT scans, in particular for lymph nodes near the thoracic inlet, anterior to the trachea, anterior to the tracheal bifurcation, near the ligamentum arteriosum, between the bronchus intermedius and esophagus, in the internal mammary space, and adjacent to the heart. Use of older lymph node maps and inconsistencies in interpretation and application of definitions in the IASLC lymph node map may potentially lead to misclassification of stage and suboptimal management of lung

  3. Issues of hope and faith in the cancer patient.

    Science.gov (United States)

    Carni, E

    1988-12-01

    Akira Kurosawa's 1952 film about a man with a terminal gastric cancer introduces a discussion of hope and faith in the oncology patient. A psychodynamic relationship between hope and faith is explored, using Lawrence LeShan's research in cancer psychotherapy and Erik Erikson's lifespan developmental theory. LeShan describes a cancer personality characterized by hopeless despair, while Erikson formulates a psychogenetic framework for the development of hope and despair. Hope and faith are linked through the individual's earliest strivings toward basic trust in the world and his or her own self-efficacy. Accordingly, cancer psychotherapy may aim at restoring adult patients' faith in life and inner creative resources.

  4. Rough Set Soft Computing Cancer Classification and Network: One Stone, Two Birds

    Directory of Open Access Journals (Sweden)

    Yue Zhang

    2010-07-01

    Full Text Available Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.

  5. Conformational SERS Classification of K-Ras Point Mutations for Cancer Diagnostics.

    Science.gov (United States)

    Morla-Folch, Judit; Gisbert-Quilis, Patricia; Masetti, Matteo; Garcia-Rico, Eduardo; Alvarez-Puebla, Ramon A; Guerrini, Luca

    2017-02-20

    Point mutations in Ras oncogenes are routinely screened for diagnostics and treatment of tumors (especially in colorectal cancer). Here, we develop an optical approach based on direct SERS coupled with chemometrics for the study of the specific conformations that single-point mutations impose on a relatively large fragment of the K-Ras gene (141 nucleobases). Results obtained offer the unambiguous classification of different mutations providing a potentially useful insight for diagnostics and treatment of cancer in a sensitive, fast, direct and inexpensive manner. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Microscopic Image Processing Of Automated Detection And Classification For Human Cancer Cell

    Directory of Open Access Journals (Sweden)

    Laith Muayyad Abdul-Hameed Al-Hayali

    2015-08-01

    Full Text Available Automated Detection for Human Cancer Cell is one of the most effective applications of image processing and has obtained great attention in latest years therefore. In this study we propose an automated detection system for human cancer cells based on breast cancer cells. This study was conducted on a set of Fine Needle Aspiration FNA biopsy microscopic images that have been obtained from the Pathology Center - Faculty of Medicine - Mansoura University Hospital - Egypt is made up of 72 microscope image samples of benign 72 microscope image samples of malignant. The purpose of this study is to detect and classify the benign and malignant cells in the breast biopsy. The images are exposed to a series of pre-processing steps which include resizing image such as 10241024 512512 enhance images by remove noise through Median Filter and contrast enhancement through Unsharp Masking Adjust Intensity. The system depends on breast cancer cells detection using clustering-based segmentation K-means clustering Fuzzy C-means clustering and region-based segmentation Watershed. Shape Texture and Color features are extracted for Detection. The results show high Detection Rate for breast cancer cells images either Benign or Malignant. Finally classification stage by using Support Vector Machine K-Nearest Neighbors and Back-Propagation Neural Networks. The final classification with the best accuracy in SVM is 97.22 in K-NN and BPNNs is 98.61.

  7. Cancer pain: A critical review of mechanism-based classification and physical therapy management in palliative care

    Directory of Open Access Journals (Sweden)

    Senthil P Kumar

    2011-01-01

    Full Text Available Mechanism-based classification and physical therapy management of pain is essential to effectively manage painful symptoms in patients attending palliative care. The objective of this review is to provide a detailed review of mechanism-based classification and physical therapy management of patients with cancer pain. Cancer pain can be classified based upon pain symptoms, pain mechanisms and pain syndromes. Classification based upon mechanisms not only addresses the underlying pathophysiology but also provides us with an understanding behind patient′s symptoms and treatment responses. Existing evidence suggests that the five mechanisms - central sensitization, peripheral sensitization, sympathetically maintained pain, nociceptive and cognitive-affective - operate in patients with cancer pain. Summary of studies showing evidence for physical therapy treatment methods for cancer pain follows with suggested therapeutic implications. Effective palliative physical therapy care using a mechanism-based classification model should be tailored to suit each patient′s findings, using a biopsychosocial model of pain.

  8. Training ANFIS structure using genetic algorithm for liver cancer classification based on microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Bülent Haznedar

    2017-02-01

    Full Text Available Classification is an important data mining technique, which is used in many fields mostly exemplified as medicine, genetics and biomedical engineering. The number of studies about classification of the datum on DNA microarray gene expression is specifically increased in recent years. However, because of the reasons as the abundance of gene numbers in the datum as microarray gene expressions and the nonlinear relations mostly across those datum, the success of conventional classification algorithms can be limited. Because of these reasons, the interest on classification methods which are based on artificial intelligence to solve the problem on classification has been gradually increased in recent times. In this study, a hybrid approach which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS and Genetic Algorithm (GA are suggested in order to classify liver microarray cancer data set. Simulation results are compared with the results of other methods. According to the results obtained, it is seen that the recommended method is better than the other methods.

  9. Classification and Clinical Management of Variants of Uncertain Significance in High Penetrance Cancer Predisposition Genes.

    Science.gov (United States)

    Moghadasi, Setareh; Eccles, Diana M; Devilee, Peter; Vreeswijk, Maaike P G; van Asperen, Christi J

    2016-04-01

    In 2008, the International Agency for Research on Cancer (IARC) proposed a system for classifying sequence variants in highly penetrant breast and colon cancer susceptibility genes, linked to clinical actions. This system uses a multifactorial likelihood model to calculate the posterior probability that an altered DNA sequence is pathogenic. Variants between 5%-94.9% (class 3) are categorized as variants of uncertain significance (VUS). This interval is wide and might include variants with a substantial difference in pathogenicity at either end of the spectrum. We think that carriers of class 3 variants would benefit from a fine-tuning of this classification. Classification of VUS to a category with a defined clinical significance is very important because for carriers of a pathogenic mutation full surveillance and risk-reducing surgery can reduce cancer incidence. Counselees who are not carriers of a pathogenic mutation can be discharged from intensive follow-up and avoid unnecessary risk-reducing surgery. By means of examples, we show how, in selected cases, additional data can lead to reclassification of some variants to a different class with different recommendations for surveillance and therapy. To improve the clinical utility of this classification system, we suggest a pragmatic adaptation to clinical practice. © 2016 WILEY PERIODICALS, INC.

  10. Setting a generalized functional linear model (GFLM for the classification of different types of cancer

    Directory of Open Access Journals (Sweden)

    Miguel Flores

    2016-11-01

    Full Text Available This work aims to classify the DNA sequences of healthy and malignant cancer respectively. For this, supervised and unsupervised classification methods from a functional context are used; i.e. each strand of DNA is an observation. The observations are discretized, for that reason different ways to represent these observations with functions are evaluated. In addition, an exploratory study is done: estimating the mean and variance of each functional type of cancer. For the unsupervised classification method, hierarchical clustering with different measures of functional distance is used. On the other hand, for the supervised classification method, a functional generalized linear model is used. For this model the first and second derivatives are used which are included as discriminating variables. It has been verified that one of the advantages of working in the functional context is to obtain a model to correctly classify cancers by 100%. For the implementation of the methods it has been used the fda.usc R package that includes all the techniques of functional data analysis used in this work. In addition, some that have been developed in recent decades. For more details of these techniques can be consulted Ramsay, J. O. and Silverman (2005 and Ferraty et al. (2006.

  11. Psychological Issues in Cancer Genetics: Current Research and Future Priorities.

    Science.gov (United States)

    Hopwood, Penelope

    1997-01-01

    Data concerning the psychological impact of high risk of cancer are reviewed, including implications of genetic testing, breast screening,and accuracy of women's risk estimates. Work in progress on prophylactic mastectomy and chemoprevention is reviewed. Research on cancer families, and interventions and prevention strategies for high-risk…

  12. Clinical issues in the surgical treatment of colon cancer

    NARCIS (Netherlands)

    Amri, R.

    2015-01-01

    More than half of colon cancer patients will eventually die of their disease. Early detection is crucial to maximize chances of cure, as five-year survival can range from 97% to as low as 8% depending on disease stage at diagnosis. Since colon cancer is associated with both old age and obesity,

  13. Breast cancer in Mongolia: an increasingly important health policy issue.

    Science.gov (United States)

    Demchig, Delgermaa; Mello-Thoms, Claudia; Brennan, Patrick C

    2017-01-01

    Breast cancer is a leading cause of cancer-related death for women in both developed and developing countries. The incidence and mortality of breast cancer in Mongolia, while low compared with other counties, has been increasing on an annual basis. In addition, in Mongolia, approximately 90% of the patients are diagnosed at a late stage, resulting in high mortality, with the majority of individuals diagnosed with breast cancer dying within 5 years of diagnosis. Breast cancer screening plays an important role in reducing mortality in Western countries and has been adopted by a number of Asian countries; however, no such approach exists in Mongolia. In a country of limited resources, implementation of expensive health strategies such as screening requires effective allocations of resources and the identification of the most effective imaging methods. This requirement relies on recent accurate data; however, at this time, there is a paucity of information around breast cancer in Mongolia. Until data around features of the disease are available, effective strategies to diagnose breast cancer that recognize the economic climate in Mongolia cannot be implemented and the impact of breast cancer is likely to increase.

  14. Breast cancer in Mongolia: an increasingly important health policy issue

    Directory of Open Access Journals (Sweden)

    Demchig D

    2017-01-01

    Full Text Available Delgermaa Demchig, Claudia Mello-Thoms, Patrick C Brennan Medical Image Optimization and Perception Group (MIOPeG, Faculty of Health Science, The University of Sydney, Sydney, NSW, Australia Abstract: Breast cancer is a leading cause of cancer-related death for women in both developed and developing countries. The incidence and mortality of breast cancer in Mongolia, while low compared with other counties, has been increasing on an annual basis. In addition, in Mongolia, approximately 90% of the patients are diagnosed at a late stage, resulting in high mortality, with the majority of individuals diagnosed with breast cancer dying within 5 years of diagnosis. Breast cancer screening plays an important role in reducing mortality in Western countries and has been adopted by a number of Asian countries; however, no such approach exists in Mongolia. In a country of limited resources, implementation of expensive health strategies such as screening requires effective allocations of resources and the identification of the most effective imaging methods. This requirement relies on recent accurate data; however, at this time, there is a paucity of information around breast cancer in Mongolia. Until data around features of the disease are available, effective strategies to diagnose breast cancer that recognize the economic climate in Mongolia cannot be implemented and the impact of breast cancer is likely to increase. Keywords: incidence, mortality, breast screening, Mongolia

  15. Apparent diffusion coefficient value of gastric cancer by diffusion-weighted imaging: Correlations with the histological differentiation and Lauren classification

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Song, E-mail: songliu532909756@gmail.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Guan, Wenxian, E-mail: wenxianguan123@126.com [Department of Gastrointestinal Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Wang, Hao, E-mail: wanghao20140525@126.com [Department of Gastrointestinal Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Pan, Liang, E-mail: panliang2014@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Zhou, Zhuping, E-mail: zhupingzhou@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Yu, Haiping, E-mail: haipingyu2012@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Liu, Tian, E-mail: tianliu2014@126.com [Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322 (United States); Yang, Xiaofeng, E-mail: xiaofengyang2014@126.com [Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322 (United States); He, Jian, E-mail: hjxueren@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Zhou, Zhengyang, E-mail: zyzhou@nju.edu.cn [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China)

    2014-12-15

    Highlights: • Gastric cancers’ ADC values were significantly lower than normal gastric wall. • Gastric adenocarcinomas with different differentiation had different ADC values. • Gastric adenocarcinomas’ ADC values correlated with histologic differentiations. • Gastric cancers’ ADC values correlated with Lauren classifications. • Mean ADC value was better than min ADC value in characterizing gastric cancers. - Abstract: Objective: The purpose of this study was to evaluate the correlations between histological differentiation and Lauren classification of gastric cancer and the apparent diffusion coefficient (ADC) value of diffusion weighted imaging (DWI). Materials and methods: Sixty-nine patients with gastric cancer lesions underwent preoperative magnetic resonance imaging (MRI) (3.0T) and surgical resection. DWI was obtained with a single-shot, echo-planar imaging sequence in the axial plane (b values: 0 and 1000 s/mm{sup 2}). Mean and minimum ADC values were obtained for each gastric cancer and normal gastric walls by two radiologists, who were blinded to the histological findings. Histological type, degree of differentiation and Lauren classification of each resected specimen were determined by one pathologist. Mean and minimum ADC values of gastric cancers with different histological types, degrees of differentiation and Lauren classifications were compared. Correlations between ADC values and histological differentiation and Lauren classification were analyzed. Results: The mean and minimum ADC values of gastric cancers, as a whole and separately, were significantly lower than those of normal gastric walls (all p values <0.001). There were significant differences in the mean and minimum ADC values among gastric cancers with different histological types, degrees of differentiation and Lauren classifications (p < 0.05). Mean and minimum ADC values correlated significantly (all p < 0.001) with histological differentiation (r = 0.564, 0.578) and

  16. Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT (Conference Presentation)

    Science.gov (United States)

    Yao, Xinwen; Gan, Yu; Chang, Ernest W.; Hibshoosh, Hanina; Feldman, Sheldon; Hendon, Christine P.

    2017-02-01

    We employed a home-built ultrahigh resolution (UHR) OCT system at 800nm to image human breast cancer sample ex vivo. The system has an axial resolution of 2.72µm and a lateral resolution of 5.52µm with an extended imaging range of 1.78mm. Over 900 UHR OCT volumes were generated on specimens from 23 breast cancer cases. With better spatial resolution, detailed structures in the breast tissue were better defined. Different types of breast cancer as well as healthy breast tissue can be well delineated from the UHR OCT images. To quantitatively evaluate the advantages of UHR OCT imaging of breast cancer, features derived from OCT intensity images were used as inputs to a machine learning model, the relevance vector machine. A trained machine learning model was employed to evaluate the performance of tissue classification based on UHR OCT images for differentiating tissue types in the breast samples, including adipose tissue, healthy stroma and cancerous region. For adipose tissue, grid-based local features were extracted from OCT intensity data, including standard deviation, entropy, and homogeneity. We showed that it was possible to enhance the classification performance on distinguishing fat tissue from non-fat tissue by using the UHR images when compared with the results based on OCT images from a commercial 1300 nm OCT system. For invasive ductal carcinoma (IDC) and normal stroma differentiation, the classification was based on frame-based features that portray signal penetration depth and tissue reflectivity. The confusing matrix indicated a sensitivity of 97.5% and a sensitivity of 77.8%.

  17. Mediterranean Diet and cancer risk: an open issue.

    Science.gov (United States)

    D'Alessandro, Annunziata; De Pergola, Giovanni; Silvestris, Franco

    2016-09-01

    The traditional Mediterranean Diet of the early 1960s meets the characteristics of an anticancer diet defined by the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AIRC). A diet rich of whole grains, pulses, vegetables and fruits, limited in high-calorie foods (foods high in sugar or fat), red meat and foods high in salt, without sugary drinks and processed meat is recommended by the WCRF/AIRC experts to reduce the risk of cancer. The aim of this review was to examine whether Mediterranean Diet is protective or not against cancer risk. Three meta-analyses of cohort studies reported that a high adherence to the Mediterranean Diet significantly reduces the risk of cancer incidence and/or mortality. Nevertheless, the Mediterranean dietary pattern defined in the studies' part of the meta-analyses has qualitative and/or quantitative differences compared to the Mediterranean Diet of the early 1960s. Therefore, the protective role of the Mediterranean Diet against cancer has not definitely been established. In epidemiological studies, a universal definition of the Mediterranean Diet, possibly the traditional Mediterranean Diet of the early 1960s, could be useful to understand the role of this dietary pattern in cancer prevention.

  18. Hematological issues in critically ill patients with cancer.

    Science.gov (United States)

    Carlson, Karen S; DeSancho, Maria T

    2010-01-01

    Patients with solid and hematologic malignancies presenting with major bleeding or thrombotic complications, potentially life-ending events in a cancer patient's clinical course, usually require admission to an intensive care unit (ICU), making their diagnosis and management even more important for the intensivist. Given the significant advances in the diagnosis and treatment of almost all types of cancers in recent years, the intensivist is likely to encounter an ever-increasing number of cancer patients in the ICU setting with these complications. Abnormal hemostasis can occur as a consequence of both the pathology and treatment of cancer. Because cancer can have multiple effects on hemostatic equilibrium, treatment of these complications can be more complex than in the general population. This article reviews the physiology of coagulation and fibrinolysis, with special attention to those aspects that are most frequently altered in the setting of malignancy. The pathophysiology of bleeding and thrombotic complications specific to critically ill cancer patients are then detailed, and the diagnostic and therapeutic strategies are discussed. Special emphasis is placed on new cancer medications that have an effect on hemostasis, and on novel clotting and anticoagulant agents that are available to the intensivist for the management of these patients.

  19. Improving accuracy for cancer classification with a new algorithm for genes selection

    Directory of Open Access Journals (Sweden)

    Zhang Hongyan

    2012-11-01

    Full Text Available Abstract Background Even though the classification of cancer tissue samples based on gene expression data has advanced considerably in recent years, it faces great challenges to improve accuracy. One of the challenges is to establish an effective method that can select a parsimonious set of relevant genes. So far, most methods for gene selection in literature focus on screening individual or pairs of genes without considering the possible interactions among genes. Here we introduce a new computational method named the Binary Matrix Shuffling Filter (BMSF. It not only overcomes the difficulty associated with the search schemes of traditional wrapper methods and overfitting problem in large dimensional search space but also takes potential gene interactions into account during gene selection. This method, coupled with Support Vector Machine (SVM for implementation, often selects very small number of genes for easy model interpretability. Results We applied our method to 9 two-class gene expression datasets involving human cancers. During the gene selection process, the set of genes to be kept in the model was recursively refined and repeatedly updated according to the effect of a given gene on the contributions of other genes in reference to their usefulness in cancer classification. The small number of informative genes selected from each dataset leads to significantly improved leave-one-out (LOOCV classification accuracy across all 9 datasets for multiple classifiers. Our method also exhibits broad generalization in the genes selected since multiple commonly used classifiers achieved either equivalent or much higher LOOCV accuracy than those reported in literature. Conclusions Evaluation of a gene’s contribution to binary cancer classification is better to be considered after adjusting for the joint effect of a large number of other genes. A computationally efficient search scheme was provided to perform effective search in the extensive

  20. Molecular classification of breast cancer: what the pathologist needs to know.

    Science.gov (United States)

    Rakha, Emad A; Green, Andrew R

    2017-02-01

    Breast cancer is a heterogeneous disease featuring distinct histological, molecular and clinical phenotypes. Although traditional classification systems utilising clinicopathological and few molecular markers are well established and validated, they remain insufficient to reflect the diverse biological and clinical heterogeneity of breast cancer. Advancements in high-throughput molecular techniques and bioinformatics have contributed to the improved understanding of breast cancer biology, refinement of molecular taxonomies and the development of novel prognostic and predictive molecular assays. Application of such technologies is already underway, and is expected to change the way we manage breast cancer. Despite the enormous amount of work that has been carried out to develop and refine breast cancer molecular prognostic and predictive assays, molecular testing is still in evolution. Pathologists should be aware of the new technology and be ready for the challenge. In this review, we provide an update on the application of molecular techniques with regard to breast cancer diagnosis, prognosis and outcome prediction. The current contribution of emerging technology to our understanding of breast cancer is also highlighted. Copyright © 2016 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.

  1. Aging Families and Breast Cancer: Multi-generational Issues

    National Research Council Canada - National Science Library

    Raveis, Victoria

    2002-01-01

    With the continuing shift of cancer care to community-based care the necessity to develop programs that enable the family to meet patients' needs for support and assistance is of paramount importance...

  2. State of the science: molecular classifications of breast cancer for clinical diagnostics.

    Science.gov (United States)

    Robison, John E; Perreard, Laurent; Bernard, Philip S

    2004-07-01

    Over the past few years, the study of genomics has embarked on developing gene expression-based classifications for tumors-an initiative that promises to revolutionize cancer medicine. High-throughput genomic platforms, such as microarray and SAGE, have found gene expression signatures that correlate to important clinical parameters used in current staging and are providing additional information that will improve standard of care. Although implementing a molecular taxonomy for prognosis and treatment would likely benefit cancer patients, there remain significant obstacles to using these assays within the current diagnostic framework. Since most genomic assays are being performed from fresh tissue, there is a need to either change the practice of formalin-fixing and paraffin-embedding tissue or adapting the assays for use on degraded RNA specimens. To date, even the most mature data sets, such as molecular classifications for breast cancer, still fall short of the number of patients needed to generalize the results to treating large populations. To implement these assays in large scale, there will need to be standardization of sample procurement, preparation, and analysis. Certainly, the greatest improvements in patient care will come through tailored therapies as genomics is coupled with clinical trials that randomize cohorts to different treatments. This manuscript reviews the current standards of care, presents progress that is being made in the development of genomic assays for breast cancer and discusses options for implementing these new tests into the clinical setting.

  3. Introduction to the Toxins Special Issue on Dietary and Non-Dietary Phytochemicals and Cancer.

    Science.gov (United States)

    Fimognari, Carmela

    2016-12-28

    The role of many phytochemicals in the modulation of the carcinogenesis process has been well documented by combining in vitro and animal studies, as well as epidemiological evidence. When acting in synergy, phytochemicals exert potential anti-cancer properties, and much progress has been made in defining their many biological activities at the molecular level. However, an interesting feature in the field of phytochemicals and cancer is the role of some phytochemicals in promoting cancer development. This Special Issue of Toxins aims to provide a comprehensive look at the contribution of dietary and non-dietary phytochemicals to cancer development and at the molecular mechanisms by which phytochemicals inhibit or promote cancer.[...].

  4. Clinical audit on "evaluation of special issues in adolescents with cancer treated in an adult cancer setting": an Indian experience.

    Science.gov (United States)

    Salins, Naveen S; Vallath, Nandini; Varkey, Prince; Ranganath, Kavya; Nayak, Malathi G

    2012-09-01

    Adolescents with cancer form a distinct group with special care needs. These patients are often cared in an adult supportive care setting where the special needs of adolescents are not met. To identify special issues in adolescents with cancer and to determine whether special needs of adolescents are met in an adult cancer setting 10 adolescents with cancer were randomly chosen and retrospectively studied for physical, psychoscocial and emotional issues using an internally validated tool. Pain was the most common physical symptom seen in all 10 patients. 3 out of 10 patients were involved in decision making, 3 out of 10 patients had identity issues and 4 out of 10 patients had peer group isolation issues. Only 3 were aware of diagnosis and none were aware of treatment outcomes and mortality. 4 out of 10 had anxiety and depression and 3 out of 10 had body image issues. Sexuality, spiritual and existential issues were not explored in any of the patients studied. The outcomes of the study were in an adult oncology setting there was a poor recognition of key adolescent issues such as sexuality, body image, identity and peer group isolation. The psychosocial supports to these adolescents were minimal and spiritual and existential issues were not explored. The inferences drawn from this study suggested a need for multidisciplinary team approach oriented in handling adolescent care needs and preferably to have a dedicated space that will help the peer group to interact, bond and cope better with the illness.

  5. A review on biomass classification and composition, cofiring issues and pretreatment methods

    Energy Technology Data Exchange (ETDEWEB)

    Jaya Shankar Tumuluru; Shahab Sokhansanj; Christopher T. Wright; Richard D. Boardman

    2011-08-01

    Presently around the globe there is a significant interest in using biomass for power generation as power generation from coal continues to raise environmental concerns. Biomass alone can be used for generation of power which can bring lot of environmental benefits. However the constraints of using biomass alone can include high investments costs for biomass feed systems and also uncertainty in the security of the feedstock supply due to seasonal variations and in most of the countries biomass is dispersed and the infrastructure for biomass supply is not well established. Alternatively cofiring biomass along with coal offer advantages like (a) reducing the issues related to biomass quality and buffers the system when there is insufficient feedstock quantity and (b) costs of adapting the existing coal power plants will be lower than building new systems dedicated only to biomass. However with the above said advantages there exists some technical constrains including low heating and energy density values, low bulk density, lower grindability index, higher moisture and ash content to successfully cofire biomass with coal. In order to successfully cofire biomass with coal, biomass feedstock specifications need to be established to direct pretreatment options that may include increasing the energy density, bulk density, stability during storage and grindability. Impacts on particle transport systems, flame stability, pollutant formation and boiler tube fouling/corrosion must also be minimized by setting feedstock specifications including composition and blend ratios if necessary. Some of these limitations can be overcome by using pretreatment methods. This paper discusses the impact of feedstock pretreatment methods like sizing, baling, pelletizing, briquetting, washing/leaching, torrefaction, torrefaction and pelletization and steam explosion in attainment of optimum feedstock characteristics to successfully cofire biomass with coal.

  6. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks

    Science.gov (United States)

    Khan, Javed; Wei, Jun S.; Ringnér, Markus; Saal, Lao H.; Ladanyi, Marc; Westermann, Frank; Berthold, Frank; Schwab, Manfred; Antonescu, Cristina R.; Peterson, Carsten; Meltzer, Paul S.

    2005-01-01

    The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in clinical practice. The ANNs correctly classified all samples and identified the genes most relevant to the classification. Expression of several of these genes has been reported in SRBCTs, but most have not been associated with these cancers. To test the ability of the trained ANN models to recognize SRBCTs, we analyzed additional blinded samples that were not previously used for the training procedure, and correctly classified them in all cases. This study demonstrates the potential applications of these methods for tumor diagnosis and the identification of candidate targets for therapy. PMID:11385503

  7. Artificial neural networks as classification and diagnostic tools for lymph node-negative breast cancers

    Energy Technology Data Exchange (ETDEWEB)

    Eswari J, Satya; Chandrakar, Neha [National Institute of Technology Raipur, Raipur (India)

    2016-04-15

    Artificial neural networks (ANNs) can be used to develop a technique to classify lymph node negative breast cancer that is prone to distant metastases based on gene expression signatures. The neural network used is a multilayered feed forward network that employs back propagation algorithm. Once trained with DNA microarraybased gene expression profiles of genes that were predictive of distant metastasis recurrence of lymph node negative breast cancer, the ANNs became capable of correctly classifying all samples and recognizing the genes most appropriate to the classification. To test the ability of the trained ANN models in recognizing lymph node negative breast cancer, we analyzed additional idle samples that were not used beforehand for the training procedure and obtained the correctly classified result in the validation set. For more substantial result, bootstrapping of training and testing dataset was performed as external validation. This study illustrates the potential application of ANN for breast tumor diagnosis and the identification of candidate targets in patients for therapy.

  8. [Classification and characteristics of interval cancers in the Principality of Asturias's Breast Cancer Screening Program].

    Science.gov (United States)

    Prieto García, M A; Delgado Sevillano, R; Baldó Sierra, C; González Díaz, E; López Secades, A; Llavona Amor, J A; Vidal Marín, B

    2013-09-01

    To review and classify the interval cancers found in the Principality of Asturias's Breast Cancer Screening Program (PDPCM). A secondary objective was to determine the histological characteristics, size, and stage of the interval cancers at the time of diagnosis. We included the interval cancers in the PDPCM in the period 2003-2007. Interval cancers were classified according to the breast cancer screening program protocol, with double reading without consensus, without blinding, with arbitration. Mammograms were interpreted by 10 radiologists in the PDPCM. A total of 33.7% of the interval cancers could not be classified; of the interval cancers that could be classified, 40.67% were labeled true interval cancers, 31.4% were labeled false negatives on screening, 23.7% had minimal signs, and 4.23% were considered occult. A total of 70% of the interval cancers were diagnosed in the year of the period between screening examinations and 71.7% were diagnosed after subsequent screening. A total of 76.9% were invasive ductal carcinomas, 61.1% were stage II when detected, and 78.7% were larger than 10mm when detected. The rate of interval cancers and the rate of false negatives in the PDPCM are higher than those recommended in the European guidelines. Interval cancers are diagnosed later than the tumors detected at screening. Studying interval cancers provides significant training for the radiologists in the PDPCM. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.

  9. Dermatologist-level classification of skin cancer with deep neural networks.

    Science.gov (United States)

    Esteva, Andre; Kuprel, Brett; Novoa, Roberto A; Ko, Justin; Swetter, Susan M; Blau, Helen M; Thrun, Sebastian

    2017-02-02

    Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of skin lesions using images is a challenging task owing to the fine-grained variability in the appearance of skin lesions. Deep convolutional neural networks (CNNs) show potential for general and highly variable tasks across many fine-grained object categories. Here we demonstrate classification of skin lesions using a single CNN, trained end-to-end from images directly, using only pixels and disease labels as inputs. We train a CNN using a dataset of 129,450 clinical images-two orders of magnitude larger than previous datasets-consisting of 2,032 different diseases. We test its performance against 21 board-certified dermatologists on biopsy-proven clinical images with two critical binary classification use cases: keratinocyte carcinomas versus benign seborrheic keratoses; and malignant melanomas versus benign nevi. The first case represents the identification of the most common cancers, the second represents the identification of the deadliest skin cancer. The CNN achieves performance on par with all tested experts across both tasks, demonstrating an artificial intelligence capable of classifying skin cancer with a level of competence comparable to dermatologists. Outfitted with deep neural networks, mobile devices can potentially extend the reach of dermatologists outside of the clinic. It is projected that 6.3 billion smartphone subscriptions will exist by the year 2021 (ref. 13) and can therefore potentially provide low-cost universal access to vital diagnostic care.

  10. Polyphenols: Key Issues Involved in Chemoprevention of Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Sebastiano Cimino

    2012-01-01

    Full Text Available Prostate cancer is is the most common solid neoplasm and it is now recognized as one of the most important medical problems facing the male population. Due to its long latency and its identifiable preneoplastic lesions, prostate cancer is an ideal target tumor for chemoprevention. Different compounds are available and certainly polyphenols represent those with efficacy against prostate cancer. This review take a look at activity and properties of major polyphenolic substances, such as epigallocatechin-3-gallate, curcumin, resveratrol and the flavonoids quercetin and genistein. Although the current studies are limited, mechanisms of action of polyphenols added with the lack of side effects show a a start for future strategies in prostate chemoprevention.

  11. Prediction of Depression in Cancer Patients With Different Classification Criteria, Linear Discriminant Analysis versus Logistic Regression.

    Science.gov (United States)

    Shayan, Zahra; Mohammad Gholi Mezerji, Naser; Shayan, Leila; Naseri, Parisa

    2015-11-03

    Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups.

  12. Prediction of Depression in Cancer Patients With Different Classification Criteria, Linear Discriminant Analysis versus Logistic Regression

    Science.gov (United States)

    Shayan, Zahra; Mezerji, Naser Mohammad Gholi; Shayan, Leila; Naseri, Parisa

    2016-01-01

    Background: Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. Methods: This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. Results: CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. Conclusion: The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups. PMID:26925900

  13. Classification of lung cancer patients and controls by chromatography of modified nucleosides in serum

    Science.gov (United States)

    McEntire, John E.; Kuo, Kenneth C.; Smith, Mark E.; Stalling, David L.; Richens, Jack W.; Zumwalt, Robert W.; Gehrke, Charles W.; Papermaster, Ben W.

    1989-01-01

    A wide spectrum of modified nucleosides has been quantified by high-performance liquid chromatography in serum of 49 male lung cancer patients, 35 patients with other cancers, and 48 patients hospitalized for nonneoplastic diseases. Data for 29 modified nucleoside peaks were normalized to an internal standard and analyzed by discriminant analysis and stepwise discriminant analysis. A model based on peaks selected by a stepwise discriminant procedure correctly classified 79% of the cancer and 75% of the noncancer subjects. It also demonstrated 84% sensitivity and 79% specificity when comparing lung cancer to noncancer subjects, and 80% sensitivity and 55% specificity in comparing lung cancer to other cancers. The nucleoside peaks having the greatest influence on the models varied dependent on the subgroups compared, confirming the importance of quantifying a wide array of nucleosides. These data support and expand previous studies which reported the utility of measuring modified nucleoside levels in serum and show that precise measurement of an array of 29 modified nucleosides in serum by high-performance liquid chromatography with UV scanning with subsequent data modeling may provide a clinically useful approach to patient classification in diagnosis and subsequent therapeutic monitoring.

  14. Lung cancer and renal insufficiency: prevalence and anticancer drug issues.

    Science.gov (United States)

    Launay-Vacher, Vincent; Etessami, Reza; Janus, Nicolas; Spano, Jean-Philippe; Ray-Coquard, Isabelle; Oudard, Stéphane; Gligorov, Joseph; Pourrat, Xavier; Beuzeboc, Philippe; Deray, Gilbert; Morere, Jean-François

    2009-01-01

    The Renal Insufficiency and Anticancer Medications (IRMA) study reported the high prevalence of renal insufficiency in cancer patients. In this special report, we focused on patients with lung cancer, emphasizing some specific findings in this population of patients. Data on patients with lung cancer who were in the IRMA study were analyzed. Renal function was calculated using Cockcroft-Gault and abbreviated Modification of Diet in Renal Disease (aMDRD) formulas to estimate the prevalence of renal insufficiency (RI) according to the KDOQI-KDIGO definition. Anticancer drugs were studied with regard to their potential renal toxicity and need for dosage adjustment. Of the 445 IRMA lung cancer patients, 14.4% had a serum creatinine (SCR) level > or =110 micromol/L. However, when they were assessed using the formulas, 62.1 and 55.9% had abnormal renal function. Of the 644 anticancer drug prescriptions, 67.5% required dose adjustments for RI or were drugs with no available data, and 78.3% of the patients received at least one such drug. Furthermore, 71.6% received potentially nephrotoxic drugs. Seventy percent of the patients had anemia but prevalence was not significantly associated with the existence of associated renal insufficiency. In the 445 IRMA patients with lung cancer, the prevalence of RI was high in spite of a normal SCR in most cases. Some anticancer drugs such as platinum salts may be nephrotoxic and need dosage adjustment. However, other important drugs such as gemcitabine do not require dose reduction and do not present with a high potential for nephrotoxicity. Lung cancer patients often present with anemia, which was not associated with the presence of RI.

  15. Applicability of the Proposed Japanese Model for the Classification of Gastric Cancer Location: The "PROTRADIST" Retrospective Study.

    Science.gov (United States)

    Marano, Luigi; Petrillo, Marianna; Pezzella, Modestino; Patriti, Alberto; Braccio, Bartolomeo; Esposito, Giuseppe; Grassia, Michele; Romano, Angela; Torelli, Francesco; De Luca, Raffaele; Fabozzi, Alessio; Falco, Giuseppe; Di Martino, Natale

    2017-06-01

    The extension of lymphadenectomy for surgical treatment of gastric cancer remains discordant among European and Japanese surgeons. Kinami et al. (Kinami S, Fujimura T, Ojima E, et al. PTD classification: proposal for a new classification of gastric cancer location based on physiological lymphatic flow. Int. J. Clin. Oncol. 2008;13:320-329) proposed a new experimental classification, the "Proximal zone, Transitional zone, Distal zone" (PTD) classification, based on the physiological lymphatic flow of gastric cancer site. The aim of the present retrospective study is to assess the applicability of PTD Japanese model in gastric cancer patients of our Western surgical department. Two groups of patients with histologically documented adenocarcinoma of the stomach were retrospectively obtained: In the first group were categorized 89 patients with T1a-T1b tumor invasion; and in the second group were 157 patients with T2-T3 category. The data collected were then categorized according to the PTD classification. In the T1a-T1b group there were no lymph node metastases within the r-GA or r-GEA compartments for tumors located in the P portion, and similarly there were no lymphatic metastases within the l-GEA or p-GA compartments for tumors located in the D portion. On the contrary, in the T2-T3 group the lymph node metastases presented a diffused spreading with no statistical significance between the two classification models. Our results show that the PTD classification based on physiological lymphatic flow of the gastric cancer site is a more physiological and clinical version than the Upper, Medium And Lower classification. It represents a valuable and applicable model of cancer location that could be a guide to a tailored surgical approach in Italian patients with neoplasm confined to submucosa. Nevertheless, in order to confirm our findings, larger and prospective studies are needed.

  16. Geochemical assessments and classification of coal mine spoils for better understanding of potential salinity issues at closure.

    Science.gov (United States)

    Park, Jin Hee; Li, Xiaofang; Edraki, Mansour; Baumgartl, Thomas; Kirsch, Bernie

    2013-06-01

    Coal mining wastes in the form of spoils, rejects and tailings deposited on a mine lease can cause various environmental issues including contamination by toxic metals, acid mine drainage and salinity. Dissolution of salt from saline mine spoil, in particular, during rainfall events may result in local or regional dispersion of salts through leaching or in the accumulation of dissolved salts in soil pore water and inhibition of plant growth. The salinity in coal mine environments is from the geogenic salt accumulations and weathering of spoils upon surface exposure. The salts are mainly sulfates and chlorides of calcium, magnesium and sodium. The objective of the research is to investigate and assess the source and mobility of salts and trace elements in various spoil types, thereby predicting the leaching behavior of the salts and trace elements from spoils which have similar geochemical properties. X-ray diffraction analysis, total digestion, sequential extraction and column experiments were conducted to achieve the objectives. Sodium and chloride concentrations best represented salinity of the spoils, which might originate from halite. Electrical conductivity, sodium and chloride concentrations in the leachate decreased sharply with increasing leaching cycles. Leaching of trace elements was not significant in the studied area. Geochemical classification of spoil/waste defined for rehabilitation purposes was useful to predict potential salinity, which corresponded with the classification from cluster analysis based on leaching data of major elements. Certain spoil groups showed high potential salinity by releasing high sodium and chloride concentrations. Therefore, the leaching characteristics of sites having saline susceptible spoils require monitoring, and suitable remediation technologies have to be applied.

  17. Cancer Biochemistry and Host-Tumor Interactions: A Decimal Classification, (Categories 51.6, 51.7, and 51.8).

    Science.gov (United States)

    Schneider, John H.

    This is a hierarchical decimal classification of information related to cancer biochemistry, to host-tumor interactions (including cancer immunology), and to occurrence of cancer in special types of animals and plants. It is a working draft of categories taken from an extensive classification of many fields of biomedical information. Because the…

  18. Cervical cancer, quality issues in early detection and prognostic factors

    NARCIS (Netherlands)

    Zaal, A.|info:eu-repo/dai/nl/31441911X

    2014-01-01

    It is expected that cervical cancer incidence will reduce in The Netherlands over the next decades, as a result of hrHPV vaccination and hrHPV-based screening. Untill then, quality of care could need some improvements as suggested by the work described in this thesis. Novel tools are being indicated

  19. Atrophic Vaginitis in Breast Cancer Survivors: A Difficult Survivorship Issue

    Directory of Open Access Journals (Sweden)

    Joanne Lester

    2015-03-01

    Full Text Available Management of breast cancer includes systematic therapies including chemotherapy and endocrine therapy can lead to a variety of symptoms that can impair the quality of life of many breast cancer survivors. Atrophic vaginitis, caused by decreased levels of circulating estrogen to urinary and vaginal receptors, is commonly experienced by this group. Chemotherapy induced ovarian failure and endocrine therapies including aromatase inhibitors and selective estrogen receptor modulators can trigger the onset of atrophic vaginitis or exacerbate existing symptoms. Symptoms of atrophic vaginitis include vaginal dryness, dyspareunia, and irritation of genital skin, pruritus, burning, vaginal discharge, and soreness. The diagnosis of atrophic vaginitis is confirmed through patient-reported symptoms and gynecological examination of external structures, introitus, and vaginal mucosa. Lifestyle modifications can be helpful but are usually insufficient to significantly improve symptoms. Non-hormonal vaginal therapies may provide additional relief by increasing vaginal moisture and fluid. Systemic estrogen therapy is contraindicated in breast cancer survivors. Continued investigations of various treatments for atrophic vaginitis are necessary. Local estrogen-based therapies, DHEA, testosterone, and pH-balanced gels continue to be evaluated in ongoing studies. Definitive results are needed pertaining to the safety of topical estrogens in breast cancer survivors.

  20. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

    Directory of Open Access Journals (Sweden)

    Liu Qingzhong

    2011-12-01

    Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

  1. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Validation of TNM classification for metastatic prostatic cancer treated using primary androgen deprivation therapy.

    Science.gov (United States)

    Kadono, Yoshifumi; Nohara, Takahiro; Ueno, Satoru; Izumi, Kouji; Kitagawa, Yasuhide; Konaka, Hiroyuki; Mizokami, Atsushi; Onozawa, Mizuki; Hinotsu, Shiro; Akaza, Hideyuki; Namiki, Mikio

    2016-02-01

    The current tumor-node-metastasis (TNM) classification system has been used for many years. The prognosis of patients with metastatic prostate cancer (mPC) treated using primary androgen deprivation therapy (PADT) was analyzed according to the TNM classification. A total of 5618 cases with lymph node metastases only (N1M0), non-regional lymph node metastasis (M1a), bone metastasis (M1b), and distant metastasis (M1c) were selected from the Japanese Study Group of Prostate Cancer database. Overall survival (OS), cancer-specific survival (CSS), and progression-free survival (PFS) rates were calculated using Kaplan-Meier analysis. The influence of clinical variables on patient prognosis was evaluated using the Cox proportional hazard regression model. The 5-year OS, CSS, and PFS were 76.0, 83.2, and 38.8% in N1M0, 57.5, 69.0, and 23.0% in M1a, 54.0, 63.1, and 23.0% in M1b, and 40.0, 51.5, and 16.6% in M1c, respectively. OS, CSS, and PFS worsened as the stages progressed. OS, CSS, and PFS were all significantly worse in N1M1b compared with N0M1b. Multivariate analysis revealed that OS and CSS were worse in patients with a Gleason score ≥8 and that combined androgen blockade (CAB) treatment provided better OS than non-CAB treatments at any tumor stage. However, OS and CSS were worse in individuals with a prostate-specific antigen >100 ng/ml only in M1b. Patient prognosis worsened with stage progression; therefore, current TNM classification system of mPC for PADT was shown to be trustworthy. Each PC cell that develops bone or lymphoid metastasis may exhibit different characteristics.

  3. Contribution of Multiparameter Flow Cytometry Immunophenotyping to the Diagnostic Screening and Classification of Pediatric Cancer

    Science.gov (United States)

    Ferreira-Facio, Cristiane S.; Milito, Cristiane; Botafogo, Vitor; Fontana, Marcela; Thiago, Leandro S.; Oliveira, Elen; da Rocha-Filho, Ariovaldo S.; Werneck, Fernando; Forny, Danielle N.; Dekermacher, Samuel; de Azambuja, Ana Paula; Ferman, Sima Esther; de Faria, Paulo Antônio Silvestre; Land, Marcelo G. P.; Orfao, Alberto; Costa, Elaine S.

    2013-01-01

    Pediatric cancer is a relatively rare and heterogeneous group of hematological and non-hematological malignancies which require multiple procedures for its diagnostic screening and classification. Until now, flow cytometry (FC) has not been systematically applied to the diagnostic work-up of such malignancies, particularly for solid tumors. Here we evaluated a FC panel of markers for the diagnostic screening of pediatric cancer and further classification of pediatric solid tumors. The proposed strategy aims at the differential diagnosis between tumoral vs. reactive samples, and hematological vs. non-hematological malignancies, and the subclassification of solid tumors. In total, 52 samples from 40 patients suspicious of containing tumor cells were analyzed by FC in parallel to conventional diagnostic procedures. The overall concordance rate between both approaches was of 96% (50/52 diagnostic samples), with 100% agreement for all reactive/inflammatory and non-infiltrated samples as well as for those corresponding to solid tumors (n = 35), with only two false negative cases diagnosed with Hodgkin lymphoma and anaplastic lymphoma, respectively. Moreover, clear discrimination between samples infiltrated by hematopoietic vs. non-hematopoietic tumor cells was systematically achieved. Distinct subtypes of solid tumors showed different protein expression profiles, allowing for the differential diagnosis of neuroblastoma (CD56hi/GD2+/CD81hi), primitive neuroectodermal tumors (CD271hi/CD99+), Wilms tumors (>1 cell population), rhabdomyosarcoma (nuMYOD1+/numyogenin+), carcinomas (CD45−/EpCAM+), germ cell tumors (CD56+/CD45−/NG2+/CD10+) and eventually also hemangiopericytomas (CD45−/CD34+). In summary, our results show that multiparameter FC provides fast and useful complementary data to routine histopathology for the diagnostic screening and classification of pediatric cancer. PMID:23472067

  4. Contribution of multiparameter flow cytometry immunophenotyping to the diagnostic screening and classification of pediatric cancer.

    Directory of Open Access Journals (Sweden)

    Cristiane S Ferreira-Facio

    Full Text Available Pediatric cancer is a relatively rare and heterogeneous group of hematological and non-hematological malignancies which require multiple procedures for its diagnostic screening and classification. Until now, flow cytometry (FC has not been systematically applied to the diagnostic work-up of such malignancies, particularly for solid tumors. Here we evaluated a FC panel of markers for the diagnostic screening of pediatric cancer and further classification of pediatric solid tumors. The proposed strategy aims at the differential diagnosis between tumoral vs. reactive samples, and hematological vs. non-hematological malignancies, and the subclassification of solid tumors. In total, 52 samples from 40 patients suspicious of containing tumor cells were analyzed by FC in parallel to conventional diagnostic procedures. The overall concordance rate between both approaches was of 96% (50/52 diagnostic samples, with 100% agreement for all reactive/inflammatory and non-infiltrated samples as well as for those corresponding to solid tumors (n = 35, with only two false negative cases diagnosed with Hodgkin lymphoma and anaplastic lymphoma, respectively. Moreover, clear discrimination between samples infiltrated by hematopoietic vs. non-hematopoietic tumor cells was systematically achieved. Distinct subtypes of solid tumors showed different protein expression profiles, allowing for the differential diagnosis of neuroblastoma (CD56(hi/GD2(+/CD81(hi, primitive neuroectodermal tumors (CD271(hi/CD99(+, Wilms tumors (>1 cell population, rhabdomyosarcoma (nuMYOD1(+/numyogenin(+, carcinomas (CD45(-/EpCAM(+, germ cell tumors (CD56(+/CD45(-/NG2(+/CD10(+ and eventually also hemangiopericytomas (CD45(-/CD34(+. In summary, our results show that multiparameter FC provides fast and useful complementary data to routine histopathology for the diagnostic screening and classification of pediatric cancer.

  5. [Full attention to several key issues in surgical treatment for the elderly patients with gastrointestinal cancer].

    Science.gov (United States)

    Zhu, Zhenggang

    2016-05-01

    With the development of population aging in our country, the incidence of gastrointestinal cancer is increasing. The risk of developing gastrointestinal cancer in elderly over 75 years was 5-6 times and the risk of death of gastrointestinal cancer was 7-8 times of the general population. As compared to non-elderly, the incidence of gastric cancer was not decreased obviously but the total incidence of colorectal cancer was increased more quickly. Therefore, screening of gastrointestinal cancer should be performed in the elderly for early discovery, diagnosis and treatment. Because of the insidious onset of the illness in elderly patients, gastrointestinal cancers are mostly diagnosed at advanced or late stage (stage III or IV). Well differentiated cancer is more common, such as papillary or tubular adenocarcinoma. Lauren type, Borrmann II or III are more common in gastric cancer, which are relatively favorable. Compared with non-elderly patients, many elderly patients also suffer from comorbid diseases with higher operation risk and postoperative complication rates. Therefore, we must pay great attention to the perioperative management and the surgical operation for the elderly patients. In this paper, several key issues involved the development trend of incidence and mortality of gastrointestinal cancer, the clinicopathological characteristics, the comorbidity and surgical treatment in the elderly patients with gastrointestinal cancer will be elaborated, aiming at promoting further attention to the clinical therapeutic strategies, management measures and prognostic factors for the elderly patients with gastrointestinal cancer.

  6. Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT.

    Science.gov (United States)

    Yao, Xinwen; Gan, Yu; Chang, Ernest; Hibshoosh, Hanina; Feldman, Sheldon; Hendon, Christine

    2017-03-01

    Breast cancer is one of the most common cancers, and recognized as the third leading cause of mortality in women. Optical coherence tomography (OCT) enables three dimensional visualization of biological tissue with micrometer level resolution at high speed, and can play an important role in early diagnosis and treatment guidance of breast cancer. In particular, ultra-high resolution (UHR) OCT provides images with better histological correlation. This paper compared UHR OCT performance with standard OCT in breast cancer imaging qualitatively and quantitatively. Automatic tissue classification algorithms were used to automatically detect invasive ductal carcinoma in ex vivo human breast tissue. Human breast tissues, including non-neoplastic/normal tissues from breast reduction and tumor samples from mastectomy specimens, were excised from patients at Columbia University Medical Center. The tissue specimens were imaged by two spectral domain OCT systems at different wavelengths: a home-built ultra-high resolution (UHR) OCT system at 800 nm (measured as 2.72 μm axial and 5.52 μm lateral) and a commercial OCT system at 1,300 nm with standard resolution (measured as 6.5 μm axial and 15 μm lateral), and their imaging performances were analyzed qualitatively. Using regional features derived from OCT images produced by the two systems, we developed an automated classification algorithm based on relevance vector machine (RVM) to differentiate hollow-structured adipose tissue against solid tissue. We further developed B-scan based features for RVM to classify invasive ductal carcinoma (IDC) against normal fibrous stroma tissue among OCT datasets produced by the two systems. For adipose classification, 32 UHR OCT B-scans from 9 normal specimens, and 28 standard OCT B-scans from 6 normal and 4 IDC specimens were employed. For IDC classification, 152 UHR OCT B-scans from 6 normal and 13 IDC specimens, and 104 standard OCT B-scans from 5 normal and 8 IDC specimens

  7. Statistical Analysis of Tissue Images for Detection and Classification of Cervical Cancer

    CERN Document Server

    Jagtap, Jaidip; Pandey, Kiran; Agarwa, Asha; Panigrahi, Prasanta K; Pradhan, Asima

    2011-01-01

    Cervical cancer is one of the major health threats in women worldwide. The current "gold standard" for detecting cancer of the epithelial tissue is the histopathology analysis of biopsy samples. However it relies on the pathologist's judgment of the disease. We investigate the utility of statistical parameters as a potential tool for detection and discrimination of the stages of dysplasia. Digital images of the tissue slides are captured with the help of a digital camera plugged to a microscope. Statistical data analysis is performed with the help of software to evaluate parameters such as mean, maxima, full width half maxima, skewness, kurtosis etc. for the images. We believe that these parameters can help effectively to improve the diagnosis and further classify normal and abnormal tissue sections. These parameters can be used independently as well as in tandem with other parameters as features in classification algorithms that involve the use of Neural networks or Principal component analysis.

  8. Disclosure of information to adult cancer patients: issues and update.

    Science.gov (United States)

    Goldberg, R J

    1984-08-01

    Clinicians are regularly faced with decisions regarding disclosure of information to cancer patients. Many of these decisions constitute a dilemma between the physician's paternalistic concern for the patient and the patient's right to know as much as possible. This paper reviews changes in the attitudes of physicians over the last several decades, elaborates on the problems that confront the clinician in the process of disclosure, and reviews the available data concerning the documented impact on the patient from receiving or not receiving information. The arguments both supporting and challenging the paternalistic view are discussed, and the necessity for viewing the disclosure of clinical information as a clinical process is offered.

  9. Pooling breast cancer datasets has a synergetic effect on classification performance and improves signature stability

    Directory of Open Access Journals (Sweden)

    van de Vijver Marc J

    2008-08-01

    Full Text Available Abstract Background Michiels et al. (Lancet 2005; 365: 488–92 employed a resampling strategy to show that the genes identified as predictors of prognosis from resamplings of a single gene expression dataset are highly variable. The genes most frequently identified in the separate resamplings were put forward as a 'gold standard'. On a higher level, breast cancer datasets collected by different institutions can be considered as resamplings from the underlying breast cancer population. The limited overlap between published prognostic signatures confirms the trend of signature instability identified by the resampling strategy. Six breast cancer datasets, totaling 947 samples, all measured on the Affymetrix platform, are currently available. This provides a unique opportunity to employ a substantial dataset to investigate the effects of pooling datasets on classifier accuracy, signature stability and enrichment of functional categories. Results We show that the resampling strategy produces a suboptimal ranking of genes, which can not be considered to be a 'gold standard'. When pooling breast cancer datasets, we observed a synergetic effect on the classification performance in 73% of the cases. We also observe a significant positive correlation between the number of datasets that is pooled, the validation performance, the number of genes selected, and the enrichment of specific functional categories. In addition, we have evaluated the support for five explanations that have been postulated for the limited overlap of signatures. Conclusion The limited overlap of current signature genes can be attributed to small sample size. Pooling datasets results in more accurate classification and a convergence of signature genes. We therefore advocate the analysis of new data within the context of a compendium, rather than analysis in isolation.

  10. Classification of lung cancer tumors based on structural and physicochemical properties of proteins by bioinformatics models.

    Directory of Open Access Journals (Sweden)

    Faezeh Hosseinzadeh

    Full Text Available Rapid distinction between small cell lung cancer (SCLC and non-small cell lung cancer (NSCLC tumors is very important in diagnosis of this disease. Furthermore sequence-derived structural and physicochemical descriptors are very useful for machine learning prediction of protein structural and functional classes, classifying proteins and the prediction performance. Herein, in this study is the classification of lung tumors based on 1497 attributes derived from structural and physicochemical properties of protein sequences (based on genes defined by microarray analysis investigated through a combination of attribute weighting, supervised and unsupervised clustering algorithms. Eighty percent of the weighting methods selected features such as autocorrelation, dipeptide composition and distribution of hydrophobicity as the most important protein attributes in classification of SCLC, NSCLC and COMMON classes of lung tumors. The same results were observed by most tree induction algorithms while descriptors of hydrophobicity distribution were high in protein sequences COMMON in both groups and distribution of charge in these proteins was very low; showing COMMON proteins were very hydrophobic. Furthermore, compositions of polar dipeptide in SCLC proteins were higher than NSCLC proteins. Some clustering models (alone or in combination with attribute weighting algorithms were able to nearly classify SCLC and NSCLC proteins. Random Forest tree induction algorithm, calculated on leaves one-out and 10-fold cross validation shows more than 86% accuracy in clustering and predicting three different lung cancer tumors. Here for the first time the application of data mining tools to effectively classify three classes of lung cancer tumors regarding the importance of dipeptide composition, autocorrelation and distribution descriptor has been reported.

  11. Natural compounds to overcome cancer chemoresistance: toxicological and clinical issues.

    Science.gov (United States)

    Turrini, Eleonora; Ferruzzi, Lorenzo; Fimognari, Carmela

    2014-12-01

    Defects in initiating or executing cell death programs are responsible for cancer chemoresistance. The growing understanding of apoptotic programs suggests that compounds simultaneously inhibiting multiple signaling pathways might provide a better therapeutic outcome than that of individual inhibitors. Natural compounds can modulate different survival pathways, thus enhancing the therapeutic effects of anticancer treatments. This review provides an overview of the preclinical and clinical relevance of chemosensitization, giving special reference to curcumin (CUR) and sulforaphane (SFN) as agents to overcome apoptosis resistance against chemotherapy. Even if CUR and SFN are common dietary constituents, they are characterized by several problems still unresolved and hampering their development as anticancer drugs. For a drug to be safe, it must be devoid of toxicity, and some studies conducted to date raises concern about CUR and SFN safety. Moreover, the efficacy of a drug, alone or in association, is usually determined by randomized, placebo-controlled, double-blind clinical trials. No such trials have shown CUR and SFN to be effective so far. Thus, caution should be exercised when suggesting the use of CUR or SFN for cancer-related therapeutic purpose, especially for very early stage of malignancy, or in patients who are undergoing chemotherapy.

  12. Gene Therapy for Pancreatic Cancer: Specificity, Issues and Hopes

    Directory of Open Access Journals (Sweden)

    Marie Rouanet

    2017-06-01

    Full Text Available A recent death projection has placed pancreatic ductal adenocarcinoma as the second cause of death by cancer in 2030. The prognosis for pancreatic cancer is very poor and there is a great need for new treatments that can change this poor outcome. Developments of therapeutic innovations in combination with conventional chemotherapy are needed urgently. Among innovative treatments the gene therapy offers a promising avenue. The present review gives an overview of the general strategy of gene therapy as well as the limitations and stakes of the different experimental in vivo models, expression vectors (synthetic and viral, molecular tools (interference RNA, genome editing and therapeutic genes (tumor suppressor genes, antiangiogenic and pro-apoptotic genes, suicide genes. The latest developments in pancreatic carcinoma gene therapy are described including gene-based tumor cell sensitization to chemotherapy, vaccination and adoptive immunotherapy (chimeric antigen receptor T-cells strategy. Nowadays, there is a specific development of oncolytic virus therapies including oncolytic adenoviruses, herpes virus, parvovirus or reovirus. A summary of all published and on-going phase-1 trials is given. Most of them associate gene therapy and chemotherapy or radiochemotherapy. The first results are encouraging for most of the trials but remain to be confirmed in phase 2 trials.

  13. Efficient molecular subtype classification of high-grade serous ovarian cancer.

    Science.gov (United States)

    Leong, Huei San; Galletta, Laura; Etemadmoghadam, Dariush; George, Joshy; Köbel, Martin; Ramus, Susan J; Bowtell, David

    2015-07-01

    High-grade serous carcinomas (HGSCs) account for approximately 70% of all epithelial ovarian cancers diagnosed. Using microarray gene expression profiling, we previously identified four molecular subtypes of HGSC: C1 (mesenchymal), C2 (immunoreactive), C4 (differentiated), and C5 (proliferative), which correlate with patient survival and have distinct biological features. Here, we describe molecular classification of HGSC based on a limited number of genes to allow cost-effective and high-throughput subtype analysis. We determined a minimal signature for accurate classification, including 39 differentially expressed and nine control genes from microarray experiments. Taqman-based (low-density arrays and Fluidigm), fluorescent oligonucleotides (Nanostring), and targeted RNA sequencing (Illumina) assays were then compared for their ability to correctly classify fresh and formalin-fixed, paraffin-embedded samples. All platforms achieved > 90% classification accuracy with RNA from fresh frozen samples. The Illumina and Nanostring assays were superior with fixed material. We found that the C1, C2, and C4 molecular subtypes were largely consistent across multiple surgical deposits from individual chemo-naive patients. In contrast, we observed substantial subtype heterogeneity in patients whose primary ovarian sample was classified as C5. The development of an efficient molecular classifier of HGSC should enable further biological characterization of molecular subtypes and the development of targeted clinical trials. Copyright © 2015 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

  14. Factors influencing the discrimination and classification of prostate cancer cell lines by FTIR microspectroscopy.

    Science.gov (United States)

    Harvey, T J; Gazi, E; Henderson, A; Snook, R D; Clarke, N W; Brown, M; Gardner, P

    2009-06-01

    In this study we obtained Fourier transform infrared (FTIR) spectra of fixed prostate cell lines of differing types as well as the primary epithelial cells from benign prostatic hyperplasia (BPH). Results showed that by using multivariate chemometric analysis it was possible to discriminate and classify these cell lines, which gave rise to sensitivity and specificity values of >94% and >98%, respectively. Following on from these results the possible influences of different factors on the discrimination and classification of the prostate cell lines were examined. Firstly, the effect of using different growth media during cell culturing was investigated, with results indicating that this did not influence chemometric discrimination. Secondly, differences in the nucleus-to-cytoplasm (N/C) ratio were examined, and it was concluded that this factor was not the main reason for the discrimination and classification of the prostate cancer (CaP) cell lines. In conclusion, given the fact that neither growth media nor N/C ratio could totally explain the classification it is likely that actual biochemical differences between the cell lines is the major contributing factor.

  15. Les cancers de la cavité buccale et de l’oropharynx dans le monde : incidence internationale et classification TNM dans les registres du cancer

    OpenAIRE

    De Camargo Cancela, Marianna

    2010-01-01

    Oral cavity and oropharynx cancers : International incidence and TNM classification in population-based cancer registries The aim of this work was to know and to evaluate the epidemiological patterns of oral cavity and ororpharynx cancers. These topographies share some common risk factors and they are often grouped in epidemiological studies. However, the implication of the human papilloma virus in oropharyngeal tumors lead us to provide incidence rates according to the anatomical classificat...

  16. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Maolong Xi

    2016-01-01

    Full Text Available This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO for cancer feature gene selection, coupling support vector machine (SVM for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV. Finally, the BQPSO coupling SVM (BQPSO/SVM, binary PSO coupling SVM (BPSO/SVM, and genetic algorithm coupling SVM (GA/SVM are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms.

  17. Parotid cancer: Impact of changes from the 1997 to the 2002 American Joint Committee on Cancer classification on outcome prediction.

    Science.gov (United States)

    Schroeder, Ursula; Groppe, Daniela; Mueller, Rolf-Peter; Guntinas-Lichius, Orlando

    2008-08-15

    The TNM classification [American Joint Committee on Cancer (AJCC)] of salivary gland cancer was revised again in 2002. In the present study, the outcome prediction of the new TNM system was compared with the old 1997 TNM system in 202 patients with primary parotid cancer. All patients treated from 1986 to 2006 were reclassified in both TNM systems. Disease-free survival (DFS) rates were calculated. The prognostic validity of both the TNM system and other factors were analyzed univariately (log-rank test) and multivariately (Cox regression). AJCC TNM stage changes from 1997 to 2002 altered the disease staging in 35% of the patients. Concerning DFS, the new TNM 2002 staging allowed significantly better separation of stage III, but not of stage I versus stage II. The TNM 2002 staging was the most powerful predictor for DFS according to multivariate analysis. The 1997 system showed no independent significance. The subclassification of the new stage IV was not satisfactory; no clear distinction of IVA versus III, and IVA versus IVB was possible. The TNM 2002 staging is more valid than the 1997 system, but a significant problem was observed in separating stage I from stage II, and within the stage IV subgroups. 2008 American Cancer Society

  18. Linking the integrated management of childhood illness (IMCI) and health information system (HIS) classifications: issues and options.

    Science.gov (United States)

    Rowe, A. K.; Hirnschall, G.; Lambrechts, T.; Bryce, J.

    1999-01-01

    Differences in the terms used to classify diseases in the Integrated Management of Childhood Illness (IMCI) guidelines and for health information system (HIS) disease surveillance could easily create confusion among health care workers. If the equivalent terms in the two classifications are not clear to health workers who are following the guidelines, they may have problems in performing the dual activities of case management and disease surveillance. These difficulties could adversely affect an individual's performance as well as the overall effectiveness of the IMCI strategy or HIS surveillance, or both. We interviewed key informants to determine the effect of these differences between the IMCI and HIS classifications on the countries that were implementing the IMCI guidelines. Four general approaches for addressing the problem were identified: translating the IMCI classifications into HIS classifications; changing the HIS list to include the IMCI classifications; using both the IMCI and HIS classification systems at the time of consultations; and doing nothing. No single approach can satisfy the needs of all countries. However, if the short-term or medium-term goal of IMCI planners is to find a solution that will reduce the problem for health workers and is also easy to implement, the approach most likely to succeed is translation of IMCI classifications into HIS classifications. Where feasible, a modification of the health information system to include the IMCI classifications may also be considered. PMID:10680246

  19. Classification of Individual Lung Cancer Cell Lines Based on DNA Methylation Markers

    Science.gov (United States)

    Marchevsky, Alberto M.; Tsou, Jeffrey A.; Laird-Offringa, Ite A.

    2004-01-01

    The classification of small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) can pose diagnostic problems due to inter-observer variability and other limitations of histopathology. There is an interest in developing classificatory models of lung neoplasms based on the analysis of multivariate molecular data with statistical methods and/or neural networks. DNA methylation levels at 20 loci were measured in 41 SCLC and 46 NSCLC cell lines with the quantitative real-time PCR method MethyLight. The data were analyzed with artificial neural networks (ANN) and linear discriminant analysis (LDA) to classify the cell lines into SCLC or into NSCLC. Models used either data from all 20 loci, or from five significant DNA methylation loci that were selected by a step-wise back-propagation procedure (PTGS2, CALCA, MTHFR, ESR1, and CDKN2A). The data were sorted randomly by cell line into 10 different data sets, each with training and testing subsets composed of 71 and 16 of the cases, respectively. Ten ANN models were trained using the 10 data sets: five using 20 variables, and five using the five variables selected by step-wise back-propagation. The ANN models with 20 input variables correctly classified 100% of the cell lines, while the models with only five variables correctly classified 87 to 100% of cases. For comparison, 10 different LDA models were trained and tested using the same data sets with either the original data or with logarithmically transformed data. Again, half of the models used all 20 variables while the others used only the five significant variables. LDA models provided correct classifications in 62.5% to 87.5% of cases. The classifications provided by all of the different models were compared with kappa statistics, yielding kappa values ranging from 0.25 to 1.0. We conclude that ANN models based on DNA methylation profiles can objectively classify SCLC and NSCLC cells lines with substantial to perfect concordance, while LDA models based on

  20. Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value.

    Directory of Open Access Journals (Sweden)

    Laetitia Marisa

    Full Text Available Colon cancer (CC pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.Fresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like, and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after

  1. Actionable gene-based classification toward precision medicine in gastric cancer

    Directory of Open Access Journals (Sweden)

    Hiroshi Ichikawa

    2017-10-01

    Full Text Available Abstract Background Intertumoral heterogeneity represents a significant hurdle to identifying optimized targeted therapies in gastric cancer (GC. To realize precision medicine for GC patients, an actionable gene alteration-based molecular classification that directly associates GCs with targeted therapies is needed. Methods A total of 207 Japanese patients with GC were included in this study. Formalin-fixed, paraffin-embedded (FFPE tumor tissues were obtained from surgical or biopsy specimens and were subjected to DNA extraction. We generated comprehensive genomic profiling data using a 435-gene panel including 69 actionable genes paired with US Food and Drug Administration-approved targeted therapies, and the evaluation of Epstein-Barr virus (EBV infection and microsatellite instability (MSI status. Results Comprehensive genomic sequencing detected at least one alteration of 435 cancer-related genes in 194 GCs (93.7% and of 69 actionable genes in 141 GCs (68.1%. We classified the 207 GCs into four The Cancer Genome Atlas (TCGA subtypes using the genomic profiling data; EBV (N = 9, MSI (N = 17, chromosomal instability (N = 119, and genomically stable subtype (N = 62. Actionable gene alterations were not specific and were widely observed throughout all TCGA subtypes. To discover a novel classification which more precisely selects candidates for targeted therapies, 207 GCs were classified using hypermutated phenotype and the mutation profile of 69 actionable genes. We identified a hypermutated group (N = 32, while the others (N = 175 were sub-divided into six clusters including five with actionable gene alterations: ERBB2 (N = 25, CDKN2A, and CDKN2B (N = 10, KRAS (N = 10, BRCA2 (N = 9, and ATM cluster (N = 12. The clinical utility of this classification was demonstrated by a case of unresectable GC with a remarkable response to anti-HER2 therapy in the ERBB2 cluster. Conclusions This actionable gene

  2. Automatic classification of acetowhite temporal patterns to identify precursor lesions of cervical cancer

    Science.gov (United States)

    Gutiérrez-Fragoso, K.; Acosta-Mesa, H. G.; Cruz-Ramírez, N.; Hernández-Jiménez, R.

    2013-12-01

    Cervical cancer has remained, until now, as a serious public health problem in developing countries. The most common method of screening is the Pap test or cytology. When abnormalities are reported in the result, the patient is referred to a dysplasia clinic for colposcopy. During this test, a solution of acetic acid is applied, which produces a color change in the tissue and is known as acetowhitening phenomenon. This reaction aims to obtaining a sample of tissue and its histological analysis let to establish a final diagnosis. During the colposcopy test, digital images can be acquired to analyze the behavior of the acetowhitening reaction from a temporal approach. In this way, we try to identify precursor lesions of cervical cancer through a process of automatic classification of acetowhite temporal patterns. In this paper, we present the performance analysis of three classification methods: kNN, Naïve Bayes and C4.5. The results showed that there is similarity between some acetowhite temporal patterns of normal and abnormal tissues. Therefore we conclude that it is not sufficient to only consider the temporal dynamic of the acetowhitening reaction to establish a diagnosis by an automatic method. Information from cytologic, colposcopic and histopathologic disciplines should be integrated as well.

  3. Critical issues on opioids in chronic non-cancer pain

    DEFF Research Database (Denmark)

    Eriksen, Jørgen; Sjøgren, Per; Bruera, Eduardo

    2006-01-01

    The aim of the study was epidemiologically to evaluate the long-term effects of opioids on pain relief, quality of life and functional capacity in long-term/chronic non-cancer pain. The study was based on data from the 2000 Danish Health and Morbidity Survey. As part of a representative National......-related quality of life (SF-36), use of the health care system, functional capabilities, satisfaction with medical pain treatment and regular or continuous use of medications. Participants reporting pain were divided into opioid and non-opioid users. The analyses were adjusted for age, gender, concomitant use...... of anxiolytics and antidepressants and pain intensity. Pain relief, quality of life and functional capacity among opioid users were compared with non-opioid users. Opioid usage was significantly associated with reporting of moderate/severe or very severe pain, poor self-rated health, not being engaged...

  4. Lung cancer patients frequently visit the emergency room for cancer-related and -unrelated issues

    OpenAIRE

    KOTAJIMA, FUTOSHI; KOBAYASHI, KUNIHIKO; SAKAGUCHI, HIROZO; NEMOTO, MANABU

    2014-01-01

    Lung cancer patients visit the emergency room (ER) for cancer-related and -unrelated reasons more often compared to patients with other types of cancer. This results in increased admissions and deaths in the ER. In this study, we retrospectively reviewed the characteristics of lung cancer patients visiting the ER in order to optimize the utilization of emergency medical services and improve the patients’ quality of life. Lung cancer patients visiting the ER of a single institution over a 2-ye...

  5. An overview of pregnancy and fertility issues in breast cancer patients.

    Science.gov (United States)

    Dabrosin, Charlotta

    2015-01-01

    Breast cancer is one of the most common malignancies of women in the reproductive years. In the Western world there is a trend towards delaying pregnancy to later in life, and in combination with an increased incidence of breast cancer an increased number of women are diagnosed with breast cancer before they have completed their reproductive plans. In addition, breast cancer during pregnancy may affect an increased number of women as the childbearing years are delayed. The survival rate after breast cancer has improved during the last decades, and many young breast cancer survivors will consider a pregnancy subsequent to the completion of adjuvant breast cancer therapy. Traditionally, many women are advised against a pregnancy due to a fear of increased risk of recurrence, especially women with estrogen receptor-positive breast cancer. Due to feasibility issues, evidence from large prospective randomized trials is missing regarding the safety of pregnancy after breast cancer. Today guidelines are based on cohort studies and population-based registry evidence with its limitations. Overall, data suggest that pregnancy after breast cancer therapy is safe, and the current evidence is summarized in this overview.

  6. Fertility Preservation: A Key Survivorship Issue for Young Women with Cancer

    OpenAIRE

    Ana M Angarita; Cynae Alonia Lillian Johnson; Amanda eNickles Fader; Christianson, Mindy S.

    2016-01-01

    Fertility preservation in the young cancer survivor is recognized as a key survivorship issue by the American Society of Clinical Oncology and the American Society of Reproductive Medicine. Thus, health-care providers should inform women about the effects of cancer therapy on fertility and should discuss the different fertility preservation options available. It is also recommended to refer women expeditiously to a fertility specialist in order to improve counseling. Women’s age, diagnosis, p...

  7. Breast Cancer Survivorship: A Comprehensive Review of Long-Term Medical Issues and Lifestyle Recommendations

    Science.gov (United States)

    Bodai, Balazs I; Tuso, Phillip

    2015-01-01

    Long-term survival rates after a diagnosis of breast cancer are steadily rising. This is good news, but clinicians must also recognize that this brings new challenges to the medical community. As breast cancer becomes a chronic condition rather than a life-threatening illness owing to advances in early diagnosis and more effective treatments, health care practitioners must recognize and manage the long-term sequelae of the constellation of therapeutic modalities. Survivors of breast cancer represent a unique and extremely complex group of patients; not only do they have the challenge of dealing with multiple long-term side effects of treatment protocols, but many are also forced to address the preexisting comorbidities of their therapies, which often include multiple other issues. Therapies have additional and/or additive side effects that may interfere with treatments directed toward the new primary diagnosis of breast cancer. Our mandate is to establish a smooth transition from patient with breast cancer to survivor of breast cancer while providing ongoing and future guidance. Certainly, the information and resources to accomplish this transition are readily available; however, they are scattered throughout the literature and therefore are not easily accessible or available to the primary care physician. It is imperative that the information available regarding survivorship issues be accessible in an organized and useful format. This article is a modest attempt to provide a comprehensive review of the long-term medical issues relevant to survivorship after the diagnosis and treatment of breast cancer. A predicted shortage of oncologists by 2020 is well-recognized. Therefore, the bulk of long-term care will become dependent on the primary care physician. This shift of care means that these physicians will need to be well educated in the long-term medical issues related to breast cancer treatment. PMID:25902343

  8. Fertility and pregnancy issues in BRCA-mutated breast cancer patients.

    Science.gov (United States)

    Lambertini, Matteo; Goldrat, Oranite; Toss, Angela; Azim, Hatem A; Peccatori, Fedro A; Ignatiadis, Michail; Del Mastro, Lucia; Demeestere, Isabelle

    2017-09-01

    Fertility and pregnancy-related issues represent one of the main areas of concerns for young women with breast cancer. Carrying a germline deleterious BRCA mutation adds additional burden on this regard due to the specific issues that should be considered during the oncofertility counseling of this special patient group. Despite the availability of a growing amount of data in the general breast cancer population on the feasibility and safety of fertility preservation and pregnancy after diagnosis, numerous challenges remain for BRCA-mutated breast cancer patients in whom very limited studies have been performed so far. Therefore, studies aiming to address the specific issues of these patients, including the impact of the mutation on their fertility potential, the safety and efficacy of the different strategies for fertility preservation, and the feasibility of having a pregnancy after diagnosis, should be considered a research priority. The aim of the present manuscript is to perform an in depth overview on the role of BRCA mutations in breast cancer with a specific focus on their impact on reproductive potential, and to discuss the fertility and pregnancy issues faced by BRCA-mutated breast cancer patients. The final goal of this manuscript is to highlight current and upcoming knowledge in this field for trying to help physicians dealing with these patients during oncofertility counseling. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. 3rd St. Gallen EORTC Gastrointestinal Cancer Conference: Consensus recommendations on controversial issues in the primary treatment of pancreatic cancer

    NARCIS (Netherlands)

    Lutz, M.P. (Manfred P.); J. Zalcberg (John); M. Ducreux (Michel); G. Aust (Gabriela); M.J. Bruno (Marco); M.W. Buchler (M.); Delpero, J.-R. (Jean-Robert); Gloor, B. (Beat); R. Glynne-Jones; Hartwig, W. (Werner); Huguet, F. (Florence); P. Laurent-Puig (Pierre); F. Lordick (Florian); P. Maisonneuve (Patrick); J. Mayerle (Julia); Martignoni, M. (Marc); J.P. Neoptolemos (John); Rhim, A.D. (Andrew D.); Schmied, B.M. (Bruno M.); T. Seufferlein (Thomas); Werner, J. (Jens); van Laethem, J.-L. (Jean-Luc); F. Otto (Florian)

    2017-01-01

    textabstractThe primary treatment of pancreatic cancer was the topic of the 3rd St. Gallen Conference 2016. A multidisciplinary panel reviewed the current evidence and discussed controversial issues in a moderated consensus session. Here we report on the key expert recommendations. It was generally

  10. The Obesity-Breast Cancer Conundrum: An Analysis of the Issues.

    Science.gov (United States)

    Matthews, Shawna B; Thompson, Henry J

    2016-06-22

    Breast cancer develops over a timeframe of 2-3 decades prior to clinical detection. Given this prolonged latency, it is somewhat unexpected from a biological perspective that obesity has no effect or reduces the risk for breast cancer in premenopausal women yet increases the risk for breast cancer in postmenopausal women. This conundrum is particularly striking in light of the generally negative effects of obesity on breast cancer outcomes, including larger tumor size at diagnosis and poorer prognosis in both pre- and postmenopausal women. This review and analysis identifies factors that may contribute to this apparent conundrum, issues that merit further investigation, and characteristics of preclinical models for breast cancer and obesity that should be considered if animal models are used to deconstruct the conundrum.

  11. MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

    Energy Technology Data Exchange (ETDEWEB)

    Young, M; Craft, D [Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)

    2016-06-15

    Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchical clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve

  12. Proteomic-Based Biosignatures in Breast Cancer Classification and Prediction of Therapeutic Response

    Science.gov (United States)

    He, Jianbo; Whelan, Stephen A.; Lu, Ming; Shen, Dejun; Chung, Debra U.; Saxton, Romaine E.; Faull, Kym F.; Whitelegge, Julian P.; Chang, Helena R.

    2011-01-01

    Protein-based markers that classify tumor subtypes and predict therapeutic response would be clinically useful in guiding patient treatment. We investigated the LC-MS/MS-identified protein biosignatures in 39 baseline breast cancer specimens including 28 HER2-positive and 11 triple-negative (TNBC) tumors. Twenty proteins were found to correctly classify all HER2 positive and 7 of the 11 TNBC tumors. Among them, galectin-3-binding protein and ALDH1A1 were found preferentially elevated in TNBC, whereas CK19, transferrin, transketolase, and thymosin β4 and β10 were elevated in HER2-positive cancers. In addition, several proteins such as enolase, vimentin, peroxiredoxin 5, Hsp 70, periostin precursor, RhoA, cathepsin D preproprotein, and annexin 1 were found to be associated with the tumor responses to treatment within each subtype. The MS-based proteomic findings appear promising in guiding tumor classification and predicting response. When sufficiently validated, some of these candidate protein markers could have great potential in improving breast cancer treatment. PMID:22110952

  13. Hormone replacement therapy and women with premature menopause--a cancer survivorship issue.

    Science.gov (United States)

    King, Judy; Wynne, Catherine Harper; Assersohn, Laura; Jones, Alison

    2011-07-01

    The importance of addressing survivorship issues has been emphasised in recent years. As cancer therapies improve there is a growing population of cancer survivors, which includes many women with premature menopause. Women who are premenopausal at the time of their cancer diagnosis may have specific survivorship issues to be addressed, including infertility, early menopause and sexual dysfunction. These factors can continue have a significant impact on the quality of life of these patients at long term follow up. Data for this Review were identified by searches of MEDLINE, PubMed, and references from relevant articles using the search terms 'HRT', 'women/female cancer/tumour', 'menopause' and 'survivorship'. Abstracts and reports from meetings were excluded. Only papers published in English between 1980 and 2010 were included. The aims of this review are to: • Address the hormonal factors which impact on cancer survivorship for premenopausal women • Review the debate for the role of hormone replacement therapy (HRT) in cancer survivors • Provide information for physicians and patients regarding the management of hormonally driven survivorship issues (for different tumour types), based on current evidence The recommendations for practice are that HRT may be offered for the alleviation of vasomotor symptoms in cancer survivors who undergo premature menopause up to the age of natural menopause (51 years in the UK). HRT (including vaginal oestrogen preparations) is contraindicated in survivors of oestrogen receptor positive breast cancer and low grade endometrial leiomyosarcoma, where non-HRT alternatives should be considered to alleviate symptoms. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

  14. Evaluation issues in the Swedish Two-County Trial of breast cancer screening: An historical review.

    Science.gov (United States)

    Tabar, Laszlo; Chen, Tony Hsiu-Hsi; Hsu, Chen-Yang; Wu, Wendy Yi-Ying; Yen, Amy Ming-Fang; Chen, Sam Li-Sheng; Chiu, Sherry Yueh-Hsia; Fann, Jean Ching-Yuan; Beckmann, Kerri; Smith, Robert A; Duffy, Stephen W

    2017-03-01

    Objectives To summarize debate and research in the Swedish Two-County Trial of mammographic screening on key issues of trial design, endpoint evaluation, and overdiagnosis, and from these to infer promising directions for the future. Methods A cluster-randomized controlled trial of the offer of breast cancer screening in Sweden, with a single screen of the control group at the end of the screening phase forms the setting for a historical review of investigations and debate on issues of design, analysis, and interpretation of results of the trial. Results There has been considerable commentary on the closure screen of the control group, ascertainment of cause of death, and cluster randomization. The issues raised were researched in detail and the main questions answered in publications between 1989 and 2003. Overdiagnosis issues still remain, but methods of estimation taking full account of lead time and of non-screening influences on incidence (taking place mainly before 2005) suggest that it is a minor phenomenon. Conclusion Despite resolution of issues relating to this trial in peer-reviewed publications dating from years, or even decades ago, issues that already have been addressed continue to be raised. We suggest that it would be more profitable to concentrate efforts on current research issues in breast cancer diagnosis, treatment, and prevention.

  15. Finding Combination of Features from Promoter Regions for Ovarian Cancer-related Gene Group Classification

    KAUST Repository

    Olayan, Rawan S.

    2012-12-01

    In classification problems, it is always important to use the suitable combination of features that will be employed by classifiers. Generating the right combination of features usually results in good classifiers. In the situation when the problem is not well understood, data items are usually described by many features in the hope that some of these may be the relevant or most relevant ones. In this study, we focus on one such problem related to genes implicated in ovarian cancer (OC). We try to recognize two important OC-related gene groups: oncogenes, which support the development and progression of OC, and oncosuppressors, which oppose such tendencies. For this, we use the properties of promoters of these genes. We identified potential “regulatory features” that characterize OC-related oncogenes and oncosuppressors promoters. In our study, we used 211 oncogenes and 39 oncosuppressors. For these, we identified 538 characteristic sequence motifs from their promoters. Promoters are annotated by these motifs and derived feature vectors used to develop classification models. We made a comparison of a number of classification models in their ability to distinguish oncogenes from oncosuppressors. Based on 10-fold cross-validation, the resultant model was able to separate the two classes with sensitivity of 96% and specificity of 100% with the complete set of features. Moreover, we developed another recognition model where we attempted to distinguish oncogenes and oncosuppressors as one group from other OC-related genes. That model achieved accuracy of 82%. We believe that the results of this study will help in discovering other OC-related oncogenes and oncosuppressors not identified as yet.

  16. Trial designs for personalizing cancer care: a systematic review and classification.

    Science.gov (United States)

    Tajik, Parvin; Zwinderman, Aleiko H; Mol, Ben W; Bossuyt, Patrick M

    2013-09-01

    There is an increasing interest in the evaluation of prognostic and predictive biomarkers for personalizing cancer care. The literature on the trial designs for evaluation of these markers is diverse and there is no consensus in the classification or nomenclature. We set this study to review the literature systematically, to identify the proposed trial designs, and to develop a classification scheme. We searched MEDLINE, EMBASE, Cochrane Methodology Register, and MathSciNet up to January 2013 for articles describing these trial designs. In each eligible article, we identified the trial designs presented and extracted the term used for labeling the design, components of patient flow (marker status of eligible participants, intervention, and comparator), study questions, and analysis plan. Our search strategy resulted in 88 eligible articles, wherein 315 labels had been used by authors in presenting trial designs; 134 of these were unique. By analyzing patient flow components, we could classify the 134 unique design labels into four basic patient flow categories, which we labeled with the most frequently used term: single-arm, enrichment, randomize-all, and biomarker-strategy designs. A fifth category consists of combinations of the other four patient flow categories. Our review showed that a considerable number of labels has been proposed for trial designs evaluating prognostic and predictive biomarkers which, based on patient flow elements, can be classified into five basic categories. The classification system proposed here could help clinicians and researchers in designing and interpreting trials evaluating predictive biomarkers, and could reduce confusion in labeling and reporting. ©2013 AACR.

  17. Gene Expression Profiles for Predicting Metastasis in Breast Cancer: A Cross-Study Comparison of Classification Methods

    Directory of Open Access Journals (Sweden)

    Mark Burton

    2012-01-01

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

  18. Long-term Prostate-specific Antigen Velocity in Improved Classification of Prostate Cancer Risk and Mortality

    DEFF Research Database (Denmark)

    Ørsted, David Dynnes; Bojesen, Stig E; Kamstrup, Pia R

    2013-01-01

    BACKGROUND: It remains unclear whether adding long-term prostate-specific antigen velocity (PSAV) to baseline PSA values improves classification of prostate cancer (PCa) risk and mortality in the general population. OBJECTIVE: To determine whether long-term PSAV improves classification of PCa risk...... classification was assessed using the net reclassification index (NRI). RESULTS: Age-adjusted hazard ratios for PCa risk and mortality were 2.7-5.3 and 2.3-3.4, respectively, for long-term PSAV when added to models already including baseline PSA values. For PCa risk and mortality, adding long-term PSAV to models....... Correspondingly, inappropriately reclassified were 49 of 10 000 men with PCa and 1658 of 10 000 men with no PCa. CONCLUSIONS: Long-term PSAV in addition to baseline PSA value improves classification of PCa risk and mortality. Applying long-term PSAV nationwide, the ratio of appropriately to inappropriately...

  19. Breast tomosynthesis and digital mammography: a comparison of breast cancer visibility and BIRADS classification in a population of cancers with subtle mammographic findings

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Ingvar; Zackrisson, Sophia [Malmoe University Hospital, Diagnostic Centre of Imaging and Functional Medicine, Malmoe (Sweden); Ikeda, Debra M. [Stanford University, Stanford Advanced Medicine Center, Department of Radiology, Stanford, CA (United States); Ruschin, Mark [Lund University, Malmoe University Hospital, Department of Medical Radiation Physics, Malmoe (Sweden); University Health Network/Princess Margaret Hospital, Department of Radiation Physics, Toronto, ON (Canada); Svahn, Tony; Timberg, Pontus; Tingberg, Anders [Lund University, Malmoe University Hospital, Department of Medical Radiation Physics, Malmoe (Sweden)

    2008-12-15

    The main purpose was to compare breast cancer visibility in one-view breast tomosynthesis (BT) to cancer visibility in one- or two-view digital mammography (DM). Thirty-six patients were selected on the basis of subtle signs of breast cancer on DM. One-view BT was performed with the same compression angle as the DM image in which the finding was least/not visible. On BT, 25 projections images were acquired over an angular range of 50 degrees, with double the dose of one-view DM. Two expert breast imagers classified one- and two-view DM, and BT findings for cancer visibility and BIRADS cancer probability in a non-blinded consensus study. Forty breast cancers were found in 37 breasts. The cancers were rated more visible on BT compared to one-view and two-view DM in 22 and 11 cases, respectively, (p<0.01 for both comparisons). Comparing one-view DM to one-view BT, 21 patients were upgraded on BIRADS classification (p<0.01). Comparing two-view DM to one-view BT, 12 patients were upgraded on BIRADS classification (p<0.01). The results indicate that the cancer visibility on BT is superior to DM, which suggests that BT may have a higher sensitivity for breast cancer detection. (orig.)

  20. Rising Cost of Cancer Pharmaceuticals: Cost Issues and Interventions to Control Costs.

    Science.gov (United States)

    Glode, Ashley E; May, Megan Brafford

    2017-01-01

    The rising cost of pharmaceuticals and, in particular, cancer drugs has made headline news in recent years. Several factors contribute to increasing costs and the burden this places on the health care system and patients. Some of these factors include costly cancer pharmaceutical research and development, longer clinical trials required to achieve drug approval, manufacturing costs for complex compounds, and the economic principles surrounding oncology drug pricing. Strategies to control costs have been proposed, and some have already been implemented to mitigate cancer drug costs such as the use of clinical treatment pathways and tools to facilitate cost discussions with patients. In this article, we briefly review some of the potential factors contributing to increasing cancer pharmaceutical costs and interventions to mitigate costs, and touch on the role of health care providers in addressing this important issue. © 2016 Pharmacotherapy Publications, Inc.

  1. Barriers and facilitators for oncology nurses discussing sexual issues with men diagnosed with testicular cancer.

    LENUS (Irish Health Repository)

    Moore, Annamarie

    2013-01-02

    PURPOSE: Testicular cancer occurs at a time in a man\\'s life when major social life changes are occurring and when body image, fertility, sexual desire and performance can be central issues. Oncology nurses, as members of the multidisciplinary team, are in an ideal position to address men\\'s concerns. The aim of this study was to investigate oncology nurses\\' self-perceived knowledge and comfort in relation to discussing sexuality concerns with men diagnosed with testicular cancer and to identify the barriers and facilitators to such discussions. METHODS: This study employed a self-completion, anonymous survey design with a sample of registered nurses working in five, randomly chosen, oncology centres in Ireland. RESULTS: In total, 89 questionnaires (45% response rate) were included for analysis. Findings suggest that although nurses were open to addressing concerns, few informed patients they were available to discuss sexual concerns. Nurses reported lacking knowledge of, and discomfort in, discussing the more intimate aspects of sexuality, including: ejaculatory difficulties, erectile dysfunction, impotence, prosthesis options and testicular self examination. CONCLUSIONS: Findings reinforce the need for more comprehensive education on sexuality issues and testicular cancer. Nurses need to take a more proactive approach to sexuality care, as opposed to the \\'passive waiting stance\\' that permeates the current culture of care. Education programmes need to include specific information on sexual issues associated with testicular cancer, and oncology nurses must subsume sexuality as an essential aspect of their role through changes in policies and nursing care planning.

  2. Controversies about fertility and pregnancy issues in young breast cancer patients: current state of the art.

    Science.gov (United States)

    Lambertini, Matteo; Goldrat, Oranite; Clatot, Florian; Demeestere, Isabelle; Awada, Ahmad

    2017-07-01

    For trying to help physicians in counseling their young patients with breast cancer interested in fertility preservation and future reproductive plans, this manuscript aims to perform an overview of the main available data on 10 controversies in this field. Thanks to the improvement in patients' prognosis, a growing attention towards fertility and pregnancy issues has been given over the past years and is currently provided to young breast cancer patients. However, several grey zones persist in many domains of this field and some physicians are still uncomfortable to deal with these issues. Despite the great number of breast cancer patients experiencing fertility and pregnancy concerns at the time of diagnosis, the pursuit of fertility preserving strategies is realized only for a small proportion of them. The lack of adequate oncofertility counseling at the time of anticancer treatment decisions and the high costs of fertility preserving procedures can be considered the main explanations for these findings. The several ongoing registries and prospective studies investigating fertility and pregnancy issues in young breast cancer patients are crucial to acquire more robust data and try to address and solve the still unmet controversies in this field.

  3. Classification of samples into two or more ordered populations with application to a cancer trial.

    Science.gov (United States)

    Conde, D; Fernández, M A; Rueda, C; Salvador, B

    2012-12-10

    In many applications, especially in cancer treatment and diagnosis, investigators are interested in classifying patients into various diagnosis groups on the basis of molecular data such as gene expression or proteomic data. Often, some of the diagnosis groups are known to be related to higher or lower values of some of the predictors. The standard methods of classifying patients into various groups do not take into account the underlying order. This could potentially result in high misclassification rates, especially when the number of groups is larger than two. In this article, we develop classification procedures that exploit the underlying order among the mean values of the predictor variables and the diagnostic groups by using ideas from order-restricted inference. We generalize the existing methodology on discrimination under restrictions and provide empirical evidence to demonstrate that the proposed methodology improves over the existing unrestricted methodology. The proposed methodology is applied to a bladder cancer data set where the researchers are interested in classifying patients into various groups. Copyright © 2012 John Wiley & Sons, Ltd.

  4. Assessing the prognostic features of a pain classification system in advanced cancer patients.

    Science.gov (United States)

    Arthur, Joseph; Tanco, Kimberson; Haider, Ali; Maligi, Courtney; Park, Minjeong; Liu, Diane; Bruera, Eduardo

    2017-09-01

    The Edmonton Classification System for Cancer Pain (ECS-CP) has been shown to predict pain management complexity based on five features: pain mechanism, incident pain, psychological distress, addictive behavior, and cognitive function. The main objective of our study was to explore the association between ECS-CP features and pain treatment outcomes among outpatients managed by a palliative care specialist-led interdisciplinary team. Initial and follow-up clinical information of 386 eligible supportive care outpatients were retrospectively reviewed and analyzed. Between the initial consultation and the first follow-up visit, the median ESAS pain intensity improved from 6 to 4.5 (p feature (p = 0.006) used a higher number of adjuvant medications. At follow-up, patients with neuropathic pain were less likely to achieve their personalized pain goal (PPG) (29 vs 72%, p = 0.015). No statistically significant association was found between increasing sum of ECS-CP features and any of the pain treatment outcomes at follow-up. Neuropathy was found to be a poor prognostic feature in advanced cancer pain management. Increasing sum of ECS-CP features was not predictive of pain management complexity at the follow-up visit when pain was managed by a palliative medicine specialist. Further research is needed to further explore these observations.

  5. Clinical classification of cancer cachexia: phenotypic correlates in human skeletal muscle.

    Science.gov (United States)

    Johns, Neil; Hatakeyama, Shinji; Stephens, Nathan A; Degen, Martin; Degen, Simone; Frieauff, Wilfried; Lambert, Christian; Ross, James A; Roubenoff, Ronenn; Glass, David J; Jacobi, Carsten; Fearon, Kenneth C H

    2014-01-01

    Cachexia affects the majority of patients with advanced cancer and is associated with a reduction in treatment tolerance, response to therapy, and duration of survival. One impediment towards the effective treatment of cachexia is a validated classification system. 41 patients with resectable upper gastrointestinal (GI) or pancreatic cancer underwent characterisation for cachexia based on weight-loss (WL) and/or low muscularity (LM). Four diagnostic criteria were used >5%WL, >10%WL, LM, and LM+>2%WL. All patients underwent biopsy of the rectus muscle. Analysis included immunohistochemistry for fibre size and type, protein and nucleic acid concentration, Western blots for markers of autophagy, SMAD signalling, and inflammation. Compared with non-cachectic cancer patients, patients with LM or LM+>2%WL, mean muscle fibre diameter was reduced by about 25% (p = 0.02 and p = 0.001 respectively). No significant difference in fibre diameter was observed if patients had WL alone. Regardless of classification, there was no difference in fibre number or proportion of fibre type across all myosin heavy chain isoforms. Mean muscle protein content was reduced and the ratio of RNA/DNA decreased in patients with either >5%WL or LM+>2%WL. Compared with non-cachectic patients, SMAD3 protein levels were increased in patients with >5%WL (p = 0.022) and with >10%WL, beclin (p = 0.05) and ATG5 (p = 0.01) protein levels were increased. There were no differences in phospho-NFkB or phospho-STAT3 levels across any of the groups. Muscle fibre size, biochemical composition and pathway phenotype can vary according to whether the diagnostic criteria for cachexia are based on weight loss alone, a measure of low muscularity alone or a combination of the two. For intervention trials where the primary end-point is a change in muscle mass or function, use of combined diagnostic criteria may allow identification of a more homogeneous patient cohort, reduce the sample size required

  6. Clinical classification of cancer cachexia: phenotypic correlates in human skeletal muscle.

    Directory of Open Access Journals (Sweden)

    Neil Johns

    Full Text Available BACKGROUND: Cachexia affects the majority of patients with advanced cancer and is associated with a reduction in treatment tolerance, response to therapy, and duration of survival. One impediment towards the effective treatment of cachexia is a validated classification system. METHODS: 41 patients with resectable upper gastrointestinal (GI or pancreatic cancer underwent characterisation for cachexia based on weight-loss (WL and/or low muscularity (LM. Four diagnostic criteria were used >5%WL, >10%WL, LM, and LM+>2%WL. All patients underwent biopsy of the rectus muscle. Analysis included immunohistochemistry for fibre size and type, protein and nucleic acid concentration, Western blots for markers of autophagy, SMAD signalling, and inflammation. FINDINGS: Compared with non-cachectic cancer patients, patients with LM or LM+>2%WL, mean muscle fibre diameter was reduced by about 25% (p = 0.02 and p = 0.001 respectively. No significant difference in fibre diameter was observed if patients had WL alone. Regardless of classification, there was no difference in fibre number or proportion of fibre type across all myosin heavy chain isoforms. Mean muscle protein content was reduced and the ratio of RNA/DNA decreased in patients with either >5%WL or LM+>2%WL. Compared with non-cachectic patients, SMAD3 protein levels were increased in patients with >5%WL (p = 0.022 and with >10%WL, beclin (p = 0.05 and ATG5 (p = 0.01 protein levels were increased. There were no differences in phospho-NFkB or phospho-STAT3 levels across any of the groups. CONCLUSION: Muscle fibre size, biochemical composition and pathway phenotype can vary according to whether the diagnostic criteria for cachexia are based on weight loss alone, a measure of low muscularity alone or a combination of the two. For intervention trials where the primary end-point is a change in muscle mass or function, use of combined diagnostic criteria may allow identification of a more

  7. Ethical issues in the geriatric patient with advanced cancer 'living to the end'.

    Science.gov (United States)

    Daher, M

    2013-10-01

    Cancer incidence will increase as the population ages; there will be a 50% increase in new cancer cases over the next 20 years, and the biggest rates of increase will occur in the developing world. Owing to technical advances in the care of critical illness, as it is the case in elderly people with advanced cancer, physicians, patients and families are often confronted with ambiguous circumstances in which medical advances may inadvertently prolong suffering and the dying process rather than bring healing and recovery. In this review of the ethical issues confronting physicians who care for patients with advanced life-limiting illnesses like cancer, a philosophical debate continues in the medical community regarding the rightness or wrongness of certain actions (e.g. physician-assisted death, euthanasia), while at the same time there is a strong desire to find a common ground for moral discourse that could guide medical decision-making in this difficult period in the lives of our patients. We will discuss how a good palliative care can be an alternative to these ethical dilemmas. Although some issues (e.g. the role of physician-assisted death in addressing suffering) remain very controversial, there is much common ground based on the application of the four major principles of medical ethics, no malfeasance, beneficence, autonomy and justice. Thus, the physician's primary commitment must always be the patient's welfare and best interests, whether the physician is treating illness or helping patients to cope with illness, disability and death. A key skill here is the communication of bad news and to negotiate a treatment plan that is acceptable to the patient, the family and the healthcare team. Attention to psychosocial issues demands involvement of the patients and their families as partners. Physicians should be sensitive to the range of psychosocial distress and social disruption common to dying patients and their families. Spiritual issues often come to the

  8. Patient-reported symptom distress, and most bothersome issues, before and during cancer treatment

    Directory of Open Access Journals (Sweden)

    Hong F

    2016-09-01

    Full Text Available Fangxin Hong,1,2 Traci M Blonquist,1 Barbara Halpenny,3 Donna L Berry,3,4 1Department of Biostatistics and Computational Biology, Dana‑Farber Cancer Institute, Boston, MA, USA;2Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA; 3Department of Nursing and Patient Care Services, The Phyllis F. Cantor Center, Dana-Farber Cancer Institute, Boston, MA, USA; 4Department of Medicine, Harvard Medical School, Boston, MA, USA Introduction: Frequently reported symptoms and treatment side effects may not be the most bothersome issues to patients with cancer. The purpose of this study was to investigate patient-reported symptom distress and bothersome issues among participants with cancer. Methods: Participants completed the Symptom Distress Scale-15 before treatment (T1 and during cancer treatment (T2 and reported up to two most bothersome issues among symptoms rated with moderate-to-severe distress. We compared symptom ratings and perceived bother and explored two approaches predicting patients’ most bothersome issues: worst absolute symptom score or worst change from pretreatment. Results: Significantly, (P≤0.0002 more patients reported moderate-to-severe distress at T2 for eight of 13 symptoms. At T1, 81% of patients reported one and 56% reported multiple symptoms with moderate-to-severe distress, while at T2, 89% reported one and 69% reported multiple symptoms with moderate-to-severe distress. Impact on sexual activity/interest, pain, fatigue, and insomnia were the most prevalent symptoms with moderate-to-severe distress. Fatigue, pain, and insomnia were perceived most often as bothersome. When one symptom was rated moderate-to-severe, predictive accuracy of the absolute score was 46% and 48% (T1 & T2 and 38% with the change score (T2–T1. When two or more symptoms were rated moderate-to-severe, predictive accuracy of the absolute score was 76% and 79% (T1 & T2 and 70% with the change score (T2–T1. Conclusion: More

  9. Laser Raman detection for oral cancer based on a Gaussian process classification method

    Science.gov (United States)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Zhang, Chijun; Chen, He; Luo, Yusheng; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

    2013-06-01

    Oral squamous cell carcinoma is the most common neoplasm of the oral cavity. The incidence rate accounts for 80% of total oral cancer and shows an upward trend in recent years. It has a high degree of malignancy and is difficult to detect in terms of differential diagnosis, as a consequence of which the timing of treatment is always delayed. In this work, Raman spectroscopy was adopted to differentially diagnose oral squamous cell carcinoma and oral gland carcinoma. In total, 852 entries of raw spectral data which consisted of 631 items from 36 oral squamous cell carcinoma patients, 87 items from four oral gland carcinoma patients and 134 items from five normal people were collected by utilizing an optical method on oral tissues. The probability distribution of the datasets corresponding to the spectral peaks of the oral squamous cell carcinoma tissue was analyzed and the experimental result showed that the data obeyed a normal distribution. Moreover, the distribution characteristic of the noise was also in compliance with a Gaussian distribution. A Gaussian process (GP) classification method was utilized to distinguish the normal people and the oral gland carcinoma patients from the oral squamous cell carcinoma patients. The experimental results showed that all the normal people could be recognized. 83.33% of the oral squamous cell carcinoma patients could be correctly diagnosed and the remaining ones would be diagnosed as having oral gland carcinoma. For the classification process of oral gland carcinoma and oral squamous cell carcinoma, the correct ratio was 66.67% and the erroneously diagnosed percentage was 33.33%. The total sensitivity was 80% and the specificity was 100% with the Matthews correlation coefficient (MCC) set to 0.447 213 595. Considering the numerical results above, the application prospects and clinical value of this technique are significantly impressive.

  10. Sentinel Node Biopsy for Breast Cancer Patients: Issues for Discussion and Our Practice

    Directory of Open Access Journals (Sweden)

    Georgios Pechlivanides

    2011-01-01

    Full Text Available Sentinel node biopsy has been established for several years now as a standard procedure of breast cancer surgery, but there are several variations of the indications and the technique used. This paper provides information regarding several issues of debate for its application as are the selection criteria, the application to patients with multifocal/multicentric breast cancer or DCIS, postneoadjuvant chemotherapy, the necessary number of nodes to be biopsied, the need for lymphoscintigraphy, the technique for frozen section, the factors that may predict nonsentinel nodes (NSNs involvement, the value of micrometastasis and isolated tumour cells, the internal mammary chain sentinel nodes, and finally the axillary recurrence after SLNB. Our view for these issues is included together with our experience of 430 SLNBs.

  11. International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma.

    Science.gov (United States)

    Travis, William D; Brambilla, Elisabeth; Noguchi, Masayuki; Nicholson, Andrew G; Geisinger, Kim R; Yatabe, Yasushi; Beer, David G; Powell, Charles A; Riely, Gregory J; Van Schil, Paul E; Garg, Kavita; Austin, John H M; Asamura, Hisao; Rusch, Valerie W; Hirsch, Fred R; Scagliotti, Giorgio; Mitsudomi, Tetsuya; Huber, Rudolf M; Ishikawa, Yuichi; Jett, James; Sanchez-Cespedes, Montserrat; Sculier, Jean-Paul; Takahashi, Takashi; Tsuboi, Masahiro; Vansteenkiste, Johan; Wistuba, Ignacio; Yang, Pan-Chyr; Aberle, Denise; Brambilla, Christian; Flieder, Douglas; Franklin, Wilbur; Gazdar, Adi; Gould, Michael; Hasleton, Philip; Henderson, Douglas; Johnson, Bruce; Johnson, David; Kerr, Keith; Kuriyama, Keiko; Lee, Jin Soo; Miller, Vincent A; Petersen, Iver; Roggli, Victor; Rosell, Rafael; Saijo, Nagahiro; Thunnissen, Erik; Tsao, Ming; Yankelewitz, David

    2011-02-01

    % disease-specific survival, respectively. AIS and MIA are usually nonmucinous but rarely may be mucinous. Invasive adenocarcinomas are classified by predominant pattern after using comprehensive histologic subtyping with lepidic (formerly most mixed subtype tumors with nonmucinous BAC), acinar, papillary, and solid patterns; micropapillary is added as a new histologic subtype. Variants include invasive mucinous adenocarcinoma (formerly mucinous BAC), colloid, fetal, and enteric adenocarcinoma. This classification provides guidance for small biopsies and cytology specimens, as approximately 70% of lung cancers are diagnosed in such samples. Non-small cell lung carcinomas (NSCLCs), in patients with advanced-stage disease, are to be classified into more specific types such as adenocarcinoma or squamous cell carcinoma, whenever possible for several reasons: (1) adenocarcinoma or NSCLC not otherwise specified should be tested for epidermal growth factor receptor (EGFR) mutations as the presence of these mutations is predictive of responsiveness to EGFR tyrosine kinase inhibitors, (2) adenocarcinoma histology is a strong predictor for improved outcome with pemetrexed therapy compared with squamous cell carcinoma, and (3) potential life-threatening hemorrhage may occur in patients with squamous cell carcinoma who receive bevacizumab. If the tumor cannot be classified based on light microscopy alone, special studies such as immunohistochemistry and/or mucin stains should be applied to classify the tumor further. Use of the term NSCLC not otherwise specified should be minimized. This new classification strategy is based on a multidisciplinary approach to diagnosis of lung adenocarcinoma that incorporates clinical, molecular, radiologic, and surgical issues, but it is primarily based on histology. This classification is intended to support clinical practice, and research investigation and clinical trials. As EGFR mutation is a validated predictive marker for response and progression

  12. International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Classification of Lung Adenocarcinoma

    Science.gov (United States)

    Travis, William D.; Brambilla, Elisabeth; Noguchi, Masayuki; Nicholson, Andrew G.; Geisinger, Kim R.; Yatabe, Yasushi; Beer, David G.; Powell, Charles A.; Riely, Gregory J.; Van Schil, Paul E.; Garg, Kavita; Austin, John H. M.; Asamura, Hisao; Rusch, Valerie W.; Hirsch, Fred R.; Scagliotti, Giorgio; Mitsudomi, Tetsuya; Huber, Rudolf M.; Ishikawa, Yuichi; Jett, James; Sanchez-Cespedes, Montserrat; Sculier, Jean-Paul; Takahashi, Takashi; Tsuboi, Masahiro; Vansteenkiste, Johan; Wistuba, Ignacio; Yang, Pan-Chyr; Aberle, Denise; Brambilla, Christian; Flieder, Douglas; Franklin, Wilbur; Gazdar, Adi; Gould, Michael; Hasleton, Philip; Henderson, Douglas; Johnson, Bruce; Johnson, David; Kerr, Keith; Kuriyama, Keiko; Lee, Jin Soo; Miller, Vincent A.; Petersen, Iver; Roggli, Victor; Rosell, Rafael; Saijo, Nagahiro; Thunnissen, Erik; Tsao, Ming; Yankelewitz, David

    2015-01-01

    , will have 100% or near 100% disease-specific survival, respectively. AIS and MIA are usually nonmucinous but rarely may be mucinous. Invasive adenocarcinomas are classified by predominant pattern after using comprehensive histologic subtyping with lepidic (formerly most mixed subtype tumors with nonmucinous BAC), acinar, papillary, and solid patterns; micropapillary is added as a new histologic subtype. Variants include invasive mucinous adenocarcinoma (formerly mucinous BAC), colloid, fetal, and enteric adenocarcinoma. This classification provides guidance for small biopsies and cytology specimens, as approximately 70% of lung cancers are diagnosed in such samples. Non-small cell lung carcinomas (NSCLCs), in patients with advanced-stage disease, are to be classified into more specific types such as adenocarcinoma or squamous cell carcinoma, whenever possible for several reasons: (1) adenocarcinoma or NSCLC not otherwise specified should be tested for epidermal growth factor receptor (EGFR) mutations as the presence of these mutations is predictive of responsiveness to EGFR tyrosine kinase inhibitors, (2) adenocarcinoma histology is a strong predictor for improved outcome with pemetrexed therapy compared with squamous cell carcinoma, and (3) potential life-threatening hemorrhage may occur in patients with squamous cell carcinoma who receive bevacizumab. If the tumor cannot be classified based on light microscopy alone, special studies such as immunohistochemistry and/or mucin stains should be applied to classify the tumor further. Use of the term NSCLC not otherwise specified should be minimized. Conclusions This new classification strategy is based on a multidisciplinary approach to diagnosis of lung adenocarcinoma that incorporates clinical, molecular, radiologic, and surgical issues, but it is primarily based on histology. This classification is intended to support clinical practice, and research investigation and clinical trials. As EGFR mutation is a validated

  13. 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

  14. A meta-synthesis of filicide classification systems: psychosocial and psychodynamic issues in women who kill their children.

    Science.gov (United States)

    Mugavin, Marie E

    2005-01-01

    Filicide is the killing of a child by a parent. To protect potential homicide victims, it is necessary to examine and identify intrapsychic and interpersonal dynamics that result in filicide. The current filicide classification systems have intended to yield better etiological understanding of the crime and ultimately lead to prevention strategies and accurate death certification. A framework of motives and precipitating factors that lead to filicide by mothers offers a starting point to examine this emotionally evocative and complex phenomenon.

  15. Cell nuclei attributed relational graphs for efficient representation and classification of gastric cancer in digital histopathology

    Science.gov (United States)

    Sharma, Harshita; Zerbe, Norman; Heim, Daniel; Wienert, Stephan; Lohmann, Sebastian; Hellwich, Olaf; Hufnagl, Peter

    2016-03-01

    This paper describes a novel graph-based method for efficient representation and subsequent classification in histological whole slide images of gastric cancer. Her2/neu immunohistochemically stained and haematoxylin and eosin stained histological sections of gastric carcinoma are digitized. Immunohistochemical staining is used in practice by pathologists to determine extent of malignancy, however, it is laborious to visually discriminate the corresponding malignancy levels in the more commonly used haematoxylin and eosin stain, and this study attempts to solve this problem using a computer-based method. Cell nuclei are first isolated at high magnification using an automatic cell nuclei segmentation strategy, followed by construction of cell nuclei attributed relational graphs of the tissue regions. These graphs represent tissue architecture comprehensively, as they contain information about cell nuclei morphology as vertex attributes, along with knowledge of neighborhood in the form of edge linking and edge attributes. Global graph characteristics are derived and ensemble learning is used to discriminate between three types of malignancy levels, namely, non-tumor, Her2/neu positive tumor and Her2/neu negative tumor. Performance is compared with state of the art methods including four texture feature groups (Haralick, Gabor, Local Binary Patterns and Varma Zisserman features), color and intensity features, and Voronoi diagram and Delaunay triangulation. Texture, color and intensity information is also combined with graph-based knowledge, followed by correlation analysis. Quantitative assessment is performed using two cross validation strategies. On investigating the experimental results, it can be concluded that the proposed method provides a promising way for computer-based analysis of histopathological images of gastric cancer.

  16. A fast gene selection method for multi-cancer classification using multiple support vector data description.

    Science.gov (United States)

    Cao, Jin; Zhang, Li; Wang, Bangjun; Li, Fanzhang; Yang, Jiwen

    2015-02-01

    For cancer classification problems based on gene expression, the data usually has only a few dozen sizes but has thousands to tens of thousands of genes which could contain a large number of irrelevant genes. A robust feature selection algorithm is required to remove irrelevant genes and choose the informative ones. Support vector data description (SVDD) has been applied to gene selection for many years. However, SVDD cannot address the problems with multiple classes since it only considers the target class. In addition, it is time-consuming when applying SVDD to gene selection. This paper proposes a novel fast feature selection method based on multiple SVDD and applies it to multi-class microarray data. A recursive feature elimination (RFE) scheme is introduced to iteratively remove irrelevant features, so the proposed method is called multiple SVDD-RFE (MSVDD-RFE). To make full use of all classes for a given task, MSVDD-RFE independently selects a relevant gene subset for each class. The final selected gene subset is the union of these relevant gene subsets. The effectiveness and accuracy of MSVDD-RFE are validated by experiments on five publicly available microarray datasets. Our proposed method is faster and more effective than other methods. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. Integration of data mining classification techniques and ensemble learning to identify risk factors and diagnose ovarian cancer recurrence.

    Science.gov (United States)

    Tseng, Chih-Jen; Lu, Chi-Jie; Chang, Chi-Chang; Chen, Gin-Den; Cheewakriangkrai, Chalong

    2017-05-01

    Ovarian cancer is the second leading cause of deaths among gynecologic cancers in the world. Approximately 90% of women with ovarian cancer reported having symptoms long before a diagnosis was made. Literature shows that recurrence should be predicted with regard to their personal risk factors and the clinical symptoms of this devastating cancer. In this study, ensemble learning and five data mining approaches, including support vector machine (SVM), C5.0, extreme learning machine (ELM), multivariate adaptive regression splines (MARS), and random forest (RF), were integrated to rank the importance of risk factors and diagnose the recurrence of ovarian cancer. The medical records and pathologic status were extracted from the Chung Shan Medical University Hospital Tumor Registry. Experimental results illustrated that the integrated C5.0 model is a superior approach in predicting the recurrence of ovarian cancer. Moreover, the classification accuracies of C5.0, ELM, MARS, RF, and SVM indeed increased after using the selected important risk factors as predictors. Our findings suggest that The International Federation of Gynecology and Obstetrics (FIGO), Pathologic M, Age, and Pathologic T were the four most critical risk factors for ovarian cancer recurrence. In summary, the above information can support the important influence of personality and clinical symptom representations on all phases of guide interventions, with the complexities of multiple symptoms associated with ovarian cancer in all phases of the recurrent trajectory. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Beyond treatment – Psychosocial and behavioural issues in cancer survivorship research and practice

    Directory of Open Access Journals (Sweden)

    Neil K. Aaronson

    2014-06-01

    Full Text Available The population of cancer survivors has grown steadily over the past several decades. Surviving cancer, however, is not synonymous with a life free of problems related to the disease and its treatment. In this paper we provide a brief overview of selected physical and psychosocial health problems prevalent among cancer survivors, namely pain, fatigue, psychological distress and work participation. We also address issues surrounding self-management and e-Health interventions for cancer survivors, and programmes to encourage survivors to adopt healthier lifestyles. Finally, we discuss approaches to assessing health-related quality of life in cancer survivors, and the use of cancer registries in conducting psychosocial survivorship research. We highlight research and practice priorities in each of these areas. While the priorities vary per topic, common themes that emerged included: (1 Symptoms should not be viewed in isolation, but rather as part of a cluster of interrelated symptoms. This has implications for both understanding the aetiology of symptoms and for their treatment; (2 Psychosocial interventions need to be evidence-based, and where possible should be tailored to the needs of the individual cancer survivor. Relatively low cost interventions with self-management and e-Health elements may be appropriate for the majority of survivors, with resource intensive interventions being reserved for those most in need; (3 More effort should be devoted to disseminating and implementing interventions in practice, and to evaluating their cost-effectiveness; and (4 Greater attention should be paid to the needs of vulnerable and high-risk populations of survivors, including the socioeconomically disadvantaged and the elderly.

  19. Genetic Fuzzy System (GFS based wavelet co-occurrence feature selection in mammogram classification for breast cancer diagnosis

    Directory of Open Access Journals (Sweden)

    Meenakshi M. Pawar

    2016-09-01

    Full Text Available Breast cancer is significant health problem diagnosed mostly in women worldwide. Therefore, early detection of breast cancer is performed with the help of digital mammography, which can reduce mortality rate. This paper presents wrapper based feature selection approach for wavelet co-occurrence feature (WCF using Genetic Fuzzy System (GFS in mammogram classification problem. The performance of GFS algorithm is explained using mini-MIAS database. WCF features are obtained from detail wavelet coefficients at each level of decomposition of mammogram image. At first level of decomposition, 18 features are applied to GFS algorithm, which selects 5 features with an average classification success rate of 39.64%. Subsequently, at second level it selects 9 features from 36 features and the classification success rate is improved to 56.75%. For third level, 16 features are selected from 54 features and average success rate is improved to 64.98%. Lastly, at fourth level 72 features are applied to GFS, which selects 16 features and thereby increasing average success rate to 89.47%. Hence, GFS algorithm is the effective way of obtaining optimal set of feature in breast cancer diagnosis.

  20. Biomarker Discovery Based on Hybrid Optimization Algorithm and Artificial Neural Networks on Microarray Data for Cancer Classification.

    Science.gov (United States)

    Moteghaed, Niloofar Yousefi; Maghooli, Keivan; Pirhadi, Shiva; Garshasbi, Masoud

    2015-01-01

    The improvement of high-through-put gene profiling based microarrays technology has provided monitoring the expression value of thousands of genes simultaneously. Detailed examination of changes in expression levels of genes can help physicians to have efficient diagnosing, classification of tumors and cancer's types as well as effective treatments. Finding genes that can classify the group of cancers correctly based on hybrid optimization algorithms is the main purpose of this paper. In this paper, a hybrid particle swarm optimization and genetic algorithm method are used for gene selection and also artificial neural network (ANN) is adopted as the classifier. In this work, we have improved the ability of the algorithm for the classification problem by finding small group of biomarkers and also best parameters of the classifier. The proposed approach is tested on three benchmark gene expression data sets: Blood (acute myeloid leukemia, acute lymphoblastic leukemia), colon and breast datasets. We used 10-fold cross-validation to achieve accuracy and also decision tree algorithm to find the relation between the biomarkers for biological point of view. To test the ability of the trained ANN models to categorize the cancers, we analyzed additional blinded samples that were not previously used for the training procedure. Experimental results show that the proposed method can reduce the dimension of the data set and confirm the most informative gene subset and improve classification accuracy with best parameters based on datasets.

  1. Web-based survey of fertility issues in young women with breast cancer.

    Science.gov (United States)

    Partridge, Ann H; Gelber, Shari; Peppercorn, Jeffrey; Sampson, Ebonie; Knudsen, Katherine; Laufer, Marc; Rosenberg, Randi; Przypyszny, Michele; Rein, Alison; Winer, Eric P

    2004-10-15

    Young women with breast cancer often seek advice about whether treatment will affect their fertility. We sought to gain a better understanding of women's attitudes about fertility and how these concerns affect decision making. We developed a survey about fertility issues for young women with a history of early-stage breast cancer. The survey was e-mailed to all registered Young Survival Coalition survivor members (N = 1,702). E-mail reminders were used. Six hundred fifty-seven eligible respondents completed the survey. Mean age at breast cancer diagnosis was 32.9 years; mean current age was 35.8 years. Ninety percent of women were white; 62% were married; 76% were college graduates. Stages at diagnosis were as follows: 0, 10%; I, 27%; II, 47%; III, 13%. Sixty-two percent of women were within 2 years of diagnosis. Fifty-seven percent recalled substantial concern at diagnosis about becoming infertile with treatment. In multivariate logistic regression, greater concern about infertility was associated with wish for children/more children (odds ratio [OR], 120; P conceiving (OR, 1.86; P = .08). Twenty-nine percent of women reported that infertility concerns influenced treatment decisions. Seventy-two percent of women reported discussing fertility concerns with their doctors; 51% felt their concerns were addressed adequately. Women seemed to overestimate their risk of becoming postmenopausal with treatment. Fertility after treatment is a major concern for young women with breast cancer. There is a need to communicate with and educate young patients regarding fertility issues at diagnosis and a need for future research directed at preserving fertility for young breast cancer survivors.

  2. Programmatic issues in the implementation of an HPV vaccination program to prevent cervical cancer.

    Science.gov (United States)

    Ault, Kevin; Reisinger, Keith

    2007-11-01

    Cervical cancer remains an important health problem even in countries with effective cervical screening programs. HPV vaccines offer great potential for primary prevention of cervical cancer and other HPV-related diseases. Eventual implementation of an HPV vaccination program raises several key issues, including universal vs. targeted vaccinations, the age and gender of vaccine recipients, the acceptability of this vaccine to health care providers, adolescents, and parents, and the effect of this vaccine on cervical cancer screening. These issues were explored among symposium attendees during an interactive question-and-answer session using computerized voting pads. Preventative HPV vaccination programs should ideally be executed universally in both women and men with an emphasis on children and adolescents prior to their first sexual experience. Parent education on HPV disease and vaccine efficacy and safety will be critical to the acceptability of HPV vaccination for their children. HPV vaccination will not eliminate the need for Pap screening. Further research will be needed to develop rational and cost-effective cervical surveillance programs for women protected by HPV vaccines.

  3. Towards optimised information about clinical trials; identification and validation of key issues in collaboration with cancer patient advocates

    DEFF Research Database (Denmark)

    Dellson, P; Nilbert, M; Bendahl, P-O

    2011-01-01

    for improvements, 21 key issues were defined and validated through a questionnaire in an independent group of breast cancer patient advocates. Clear messages, emotionally neutral expressions, careful descriptions of side effects, clear comparisons between different treatment alternatives and information about...

  4. Self-Image and Sexuality Issues among Young Women with Breast Cancer: Practical Recommendations.

    Science.gov (United States)

    Hungr, Clara; Sanchez-Varela, Veronica; Bober, Sharon L

    2017-01-01

    Younger breast cancer survivors face a unique set of treatment-related issues that have enormous impact on quality of life and psychological well-being. Although there is often a profound and distressing impact of treatment on self-image and sexual function, women rarely receive any attention for these issues. Unfortunately, most clinicians receive no training on how to inquire about these problems and most clinicians feel unprepared to discuss them. Often this silence is due to a lack of ready resources and uncertainty of appropriate strategies for rehabilitation. Cultural barriers may also contribute to lack of attention to these issues. The aim of this paper is to not only elucidate common problems regarding self-image and sexual dysfunction, but to also offer concrete guidance about inquiry using a simple checklist approach as well as tips for resources and other evidence-based intervention strategies. Samples of a checklist and resource sheet for women written in Spanish are included, and cultural considerations within a Hispanic/Latina framework will be noted. As the great majority of young breast cancer patients are now becoming long-term survivors, it is essential for clinicians to learn how to address distressing treatment-related late effects including diminished self-image and sexual dysfunction.

  5. Oncologists' confidence in knowledge of fertility issues for young women with cancer.

    Science.gov (United States)

    Duffy, Christine; Allen, Susan M; Dube, Catherine; Dickersin, Kay

    2012-06-01

    We sought to identify factors associated with greater cancer-related fertility knowledge in a national survey of oncologists. We surveyed 344 oncologists from a sampling pool drawn randomly from the AMA Masterfile. We conducted multiple linear regression to determine the relationship between confidence in knowledge and oncologists' characteristics. Respondents' average age was 48.5, and 75.3% were male. The average confidence in knowledge summary score was 23.8 (SD 6.4, range 8-40). In multivariable regression, confidence was higher among oncologists with more information resources, a sense of responsibility to discuss fertility issues and among gynecologic oncologists vs. other oncology specialties. Physician age, gender, and practice setting were not associated with fertility-related knowledge. Oncologists lack confidence in their knowledge of fertility issues in young women with breast cancer. Increasing professional responsibility to discuss fertility and greater information access could improve the depth and breadth of education regarding fertility issues among oncologists and their young patients.

  6. Comparison of Computational Algorithms for the Classification of Liver Cancer using SELDI Mass Spectrometry: A Case Study

    Directory of Open Access Journals (Sweden)

    Robert J Hickey

    2007-01-01

    Full Text Available Introduction: As an alternative to DNA microarrays, mass spectrometry based analysis of proteomic patterns has shown great potential in cancer diagnosis. The ultimate application of this technique in clinical settings relies on the advancement of the technology itself and the maturity of the computational tools used to analyze the data. A number of computational algorithms constructed on different principles are available for the classification of disease status based on proteomic patterns. Nevertheless, few studies have addressed the difference in the performance of these approaches. In this report, we describe a comparative case study on the classification accuracy of hepatocellular carcinoma based on the serum proteomic pattern generated from a Surface Enhanced Laser Desorption/Ionization (SELDI mass spectrometer.Methods: Nine supervised classifi cation algorithms are implemented in R software and compared for the classification accuracy.Results: We found that the support vector machine with radial function is preferable as a tool for classification of hepatocellular carcinoma using features in SELDI mass spectra. Among the rest of the methods, random forest and prediction analysis of microarrays have better performance. A permutation-based technique reveals that the support vector machine with a radial function seems intrinsically superior in learning from the training data since it has a lower prediction error than others when there is essentially no differential signal. On the other hand, the performance of the random forest and prediction analysis of microarrays rely on their capability of capturing the signals with substantial differentiation between groups.Conclusions: Our finding is similar to a previous study, where classification methods based on the Matrix Assisted Laser Desorption/Ionization (MALDI mass spectrometry are compared for the prediction accuracy of ovarian cancer. The support vector machine, random forest and prediction

  7. One-class kernel subspace ensemble for medical image classification

    Science.gov (United States)

    Zhang, Yungang; Zhang, Bailing; Coenen, Frans; Xiao, Jimin; Lu, Wenjin

    2014-12-01

    Classification of medical images is an important issue in computer-assisted diagnosis. In this paper, a classification scheme based on a one-class kernel principle component analysis (KPCA) model ensemble has been proposed for the classification of medical images. The ensemble consists of one-class KPCA models trained using different image features from each image class, and a proposed product combining rule was used for combining the KPCA models to produce classification confidence scores for assigning an image to each class. The effectiveness of the proposed classification scheme was verified using a breast cancer biopsy image dataset and a 3D optical coherence tomography (OCT) retinal image set. The combination of different image features exploits the complementary strengths of these different feature extractors. The proposed classification scheme obtained promising results on the two medical image sets. The proposed method was also evaluated on the UCI breast cancer dataset (diagnostic), and a competitive result was obtained.

  8. Breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution.

    Science.gov (United States)

    Pak, Fatemeh; Kanan, Hamidreza Rashidy; Alikhassi, Afsaneh

    2015-11-01

    Breast cancer is one of the most perilous diseases among women. Breast screening is a method of detecting breast cancer at a very early stage which can reduce the mortality rate. Mammography is a standard method for the early diagnosis of breast cancer. In this paper, a new algorithm is proposed for breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution (SR). The presented algorithm includes three main parts including pre-processing, feature extraction and classification. In the pre-processing stage, after determining the region of interest (ROI) by an automatic technique, the quality of image is improved using NSCT and SR algorithm. In the feature extraction part, several features of the image components are extracted and skewness of each feature is calculated. Finally, AdaBoost algorithm is used to classify and determine the probability of benign and malign disease. The obtained results on Mammographic Image Analysis Society (MIAS) database indicate the significant performance and superiority of the proposed method in comparison with the state of the art approaches. According to the obtained results, the proposed technique achieves 91.43% and 6.42% as a mean accuracy and FPR, respectively. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  9. The study of a patient's immune system may prove to be a useful noninvasive tool for stage classification in colon cancer.

    Science.gov (United States)

    Pellegrini, Patrizia; Berghella, Anna Maria; Contasta, Ida; Del Beato, Tiziana; Adorno, Domenico

    2006-10-01

    Therapy, and, therefore, prognosis, is strictly related to cancer stage, and hence, screening tests that can contribute to the early classification of disease stage represent a step forward in treatment. Unfortunately, few prognostic indices are available, especially noninvasive ones. Our study of the physiological network of the immune response, however, leads us to believe that it may well be possible to define immunological indices for the classification of cancer stage using blood parameters. In this paper, we show how the study of a patient's immune system can be used as a noninvasive tool for early-stage classification.

  10. Classification of follicular cell-derived thyroid cancer by global RNA profiling

    DEFF Research Database (Denmark)

    Rossing, Maria

    2013-01-01

    classification will not only contribute to our biological insight but also improve clinical and pathological examinations, thus advancing thyroid tumour diagnosis and ultimately preventing superfluous surgery. This review evaluates the status of classification and biological insights gained from molecular...... classifiers that may differentiate malignant from benign thyroid nodules. Molecular classification models based on global RNA profiles from fine-needle aspirations are currently being evaluated; results are preliminary and lack validation in prospective clinical trials. There is no doubt that molecular...

  11. Dealing with symptoms and issues of hospitalized patients with cancer in indonesia: the role of families, nurses, and physicians

    NARCIS (Netherlands)

    Effendy, C.; Vissers, K.; Tejawinata, S.; Vernooij-Dassen, M.; Engels, Y.M.

    2015-01-01

    OBJECTIVE: Patients with cancer often face physical, psychological, social, spiritual, and emotional symptoms. Our aim was to study symptoms and issues of hospitalized patients with cancer in Indonesia, a country with strong family ties, and how family members, nurses, and physicians deal with them.

  12. Towards optimised information about clinical trials; identification and validation of key issues in collaboration with cancer patient advocates

    DEFF Research Database (Denmark)

    Dellson, P; Nilbert, M; Bendahl, P-O

    2011-01-01

    in three clinical trials for breast cancer. Primary data collection was done in focus group interviews with breast cancer patient advocates. Content analysis identified three major themes: comprehensibility, emotions and associations, and decision making. Based on the advocates' suggestions...... for improvements, 21 key issues were defined and validated through a questionnaire in an independent group of breast cancer patient advocates. Clear messages, emotionally neutral expressions, careful descriptions of side effects, clear comparisons between different treatment alternatives and information about...

  13. Borderline resectable pancreatic cancer: conceptual evolution and current approach to image-based classification.

    Science.gov (United States)

    Gilbert, J W; Wolpin, B; Clancy, T; Wang, J; Mamon, H; Shinagare, A B; Jagannathan, J; Rosenthal, M

    2017-09-01

    Diagnostic imaging plays a critical role in the initial diagnosis and therapeutic monitoring of pancreatic adenocarcinoma. Over the past decade, the concept of 'borderline resectable' pancreatic cancer has emerged to describe a distinct subset of patients existing along the spectrum from resectable to locally advanced disease for whom a microscopically margin-positive (R1) resection is considered relatively more likely, primarily due to the relationship of the primary tumor with surrounding vasculature. This review traces the conceptual evolution of borderline resectability from a radiological perspective, including the debates over the key imaging criteria that define the thresholds between resectable, borderline resectable, and locally advanced or metastatic disease. This review also addresses the data supporting neoadjuvant therapy in this population and discusses current imaging practices before and during treatment. A growing body of evidence suggests that the borderline resectable group of patients may particularly benefit from neoadjuvant therapy to increase the likelihood of an ultimately margin-negative (R0) resection. Unfortunately, anatomic and imaging criteria to define borderline resectability are not yet universally agreed upon, with several classification systems proposed in the literature and considerable variance in institution-by-institution practice. As a result of this lack of consensus, as well as overall small patient numbers and lack of established clinical trials dedicated to borderline resectable patients, accurate evidence-based diagnostic categorization and treatment selection for this subset of patients remains a significant challenge. Clinicians and radiologists alike should be cognizant of evolving imaging criteria for borderline resectability given their profound implications for treatment strategy, follow-up recommendations, and prognosis.

  14. An Expression Signature as an Aid to the Histologic Classification of Non-Small Cell Lung Cancer

    Science.gov (United States)

    Girard, Luc; Rodriguez-Canales, Jaime; Behrens, Carmen; Thompson, Debrah M.; Botros, Ihab W.; Tang, Hao; Xie, Yang; Rekhtman, Natasha; Travis, William D.; Wistuba, Ignacio I.; Minna, John D.; Gazdar, Adi F.

    2017-01-01

    Purpose Most non-small cell lung cancers (NSCLCs) are now diagnosed from small specimens, and classification using standard pathology methods can be difficult. This is of clinical relevance as many therapy regimens and clinical trials are histology dependent. The purpose of this study was to develop an mRNA expression signature as an adjunct test for routine histo-pathological classification of NSCLCs. Experimental Design A microarray dataset of resected adenocarcinomas (ADC) and squamous cell carcinomas (SCC) was used as the learning set for an ADC-SCC signature. The Cancer Genome Atlas (TCGA) lung RNAseq dataset was used for validation. Another microarray dataset of ADCs and matched non-malignant lung was used as the learning set for a Tumor vs. Nonmalignant signature. The classifiers were selected as the most differentially expressed genes and sample classification was determined by a nearest distance approach. Results We developed a 62-gene expression signature that contained many genes used in immunostains for NSCLC typing. It includes 42 genes that distinguish ADC from SCC and 20 genes differentiating non-malignant lung from lung cancer. Testing of the TCGA and other public datasets resulted in high prediction accuracies (93–95%). Additionally, a prediction score was derived that correlates both with histologic grading and prognosis. We developed a practical version of the Classifier using the HTG EdgeSeq nuclease protection-based technology in combination with next-generation sequencing that can be applied to formalin-fixed paraffin-embedded (FFPE) tissues and small biopsies. Conclusions Our RNA classifier provides an objective, quantitative method to aid in the pathological diagnosis of lung cancer. PMID:27354471

  15. Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method

    Directory of Open Access Journals (Sweden)

    Huang Desheng

    2009-07-01

    Full Text Available Abstract Background A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification. Methods Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80. Results The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set. Conclusion The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.

  16. Non-Gaussian Distributions Affect Identification of Expression Patterns, Functional Annotation, and Prospective Classification in Human Cancer Genomes

    Science.gov (United States)

    Marko, Nicholas F.; Weil, Robert J.

    2012-01-01

    Introduction Gene expression data is often assumed to be normally-distributed, but this assumption has not been tested rigorously. We investigate the distribution of expression data in human cancer genomes and study the implications of deviations from the normal distribution for translational molecular oncology research. Methods We conducted a central moments analysis of five cancer genomes and performed empiric distribution fitting to examine the true distribution of expression data both on the complete-experiment and on the individual-gene levels. We used a variety of parametric and nonparametric methods to test the effects of deviations from normality on gene calling, functional annotation, and prospective molecular classification using a sixth cancer genome. Results Central moments analyses reveal statistically-significant deviations from normality in all of the analyzed cancer genomes. We observe as much as 37% variability in gene calling, 39% variability in functional annotation, and 30% variability in prospective, molecular tumor subclassification associated with this effect. Conclusions Cancer gene expression profiles are not normally-distributed, either on the complete-experiment or on the individual-gene level. Instead, they exhibit complex, heavy-tailed distributions characterized by statistically-significant skewness and kurtosis. The non-Gaussian distribution of this data affects identification of differentially-expressed genes, functional annotation, and prospective molecular classification. These effects may be reduced in some circumstances, although not completely eliminated, by using nonparametric analytics. This analysis highlights two unreliable assumptions of translational cancer gene expression analysis: that “small” departures from normality in the expression data distributions are analytically-insignificant and that “robust” gene-calling algorithms can fully compensate for these effects. PMID:23118863

  17. Non-gaussian distributions affect identification of expression patterns, functional annotation, and prospective classification in human cancer genomes.

    Directory of Open Access Journals (Sweden)

    Nicholas F Marko

    Full Text Available INTRODUCTION: Gene expression data is often assumed to be normally-distributed, but this assumption has not been tested rigorously. We investigate the distribution of expression data in human cancer genomes and study the implications of deviations from the normal distribution for translational molecular oncology research. METHODS: We conducted a central moments analysis of five cancer genomes and performed empiric distribution fitting to examine the true distribution of expression data both on the complete-experiment and on the individual-gene levels. We used a variety of parametric and nonparametric methods to test the effects of deviations from normality on gene calling, functional annotation, and prospective molecular classification using a sixth cancer genome. RESULTS: Central moments analyses reveal statistically-significant deviations from normality in all of the analyzed cancer genomes. We observe as much as 37% variability in gene calling, 39% variability in functional annotation, and 30% variability in prospective, molecular tumor subclassification associated with this effect. CONCLUSIONS: Cancer gene expression profiles are not normally-distributed, either on the complete-experiment or on the individual-gene level. Instead, they exhibit complex, heavy-tailed distributions characterized by statistically-significant skewness and kurtosis. The non-Gaussian distribution of this data affects identification of differentially-expressed genes, functional annotation, and prospective molecular classification. These effects may be reduced in some circumstances, although not completely eliminated, by using nonparametric analytics. This analysis highlights two unreliable assumptions of translational cancer gene expression analysis: that "small" departures from normality in the expression data distributions are analytically-insignificant and that "robust" gene-calling algorithms can fully compensate for these effects.

  18. Comparison of the prevalence of malnutrition diagnosis in head and neck, gastrointestinal, and lung cancer patients by 3 classification methods.

    Science.gov (United States)

    Platek, Mary E; Popp, Johann V; Possinger, Candi S; Denysschen, Carol A; Horvath, Peter; Brown, Jean K

    2011-01-01

    Malnutrition is prevalent among patients within certain cancer types. There is lack of universal standard of care for nutrition screening and a lack of agreement on an operational definition and on validity of malnutrition indicators. In a secondary data analysis, we investigated prevalence of malnutrition diagnosis with 3 classification methods using data from medical records of a National Cancer Institute-designated comprehensive cancer center. Records of 227 patients hospitalized during 1998 with head and neck, gastrointestinal, or lung cancer were reviewed for malnutrition based on 3 methods: (1) physician-diagnosed malnutrition-related International Classification of Diseases, Ninth Revision codes; (2) in-hospital nutritional assessment summaries conducted by registered dietitians; and (3) body mass indexes (BMIs). For patients with multiple admissions, only data from the first hospitalization were included. Prevalence of malnutrition diagnosis ranged from 8.8% based on BMI to approximately 26% of all cases based on dietitian assessment. κ coefficients between any methods indicated a weak (κ = 0.23, BMI and dietitians; and κ = 0.28, dietitians and physicians)-to-fair strength of agreement (κ = 0.38, BMI and physicians). Available methods to identify patients with malnutrition in a National Cancer Institute-designated comprehensive cancer center resulted in varied prevalence of malnutrition diagnosis. A universal standard of care for nutrition screening that uses validated tools is needed. The Joint Commission on the Accreditation of Healthcare Organizations requires nutritional screening of patients within 24 hours of admission. For this purpose, implementation of a validated tool that can be used by various healthcare practitioners, including nurses, needs to be considered.

  19. Toward automated classification of consumers' cancer-related questions with a new taxonomy of expected answer types.

    Science.gov (United States)

    McRoy, Susan; Jones, Sean; Kurmally, Adam

    2016-09-01

    This article examines methods for automated question classification applied to cancer-related questions that people have asked on the web. This work is part of a broader effort to provide automated question answering for health education. We created a new corpus of consumer-health questions related to cancer and a new taxonomy for those questions. We then compared the effectiveness of different statistical methods for developing classifiers, including weighted classification and resampling. Basic methods for building classifiers were limited by the high variability in the natural distribution of questions and typical refinement approaches of feature selection and merging categories achieved only small improvements to classifier accuracy. Best performance was achieved using weighted classification and resampling methods, the latter yielding an accuracy of F1 = 0.963. Thus, it would appear that statistical classifiers can be trained on natural data, but only if natural distributions of classes are smoothed. Such classifiers would be useful for automated question answering, for enriching web-based content, or assisting clinical professionals to answer questions. © The Author(s) 2015.

  20. Body mass index: different nutritional status according to WHO, OPAS and Lipschitz classifications in gastrointestinal cancer patients

    Directory of Open Access Journals (Sweden)

    Katia Barao

    2012-06-01

    Full Text Available CONTEXT: The body mass index (BMI is the most common marker used on diagnoses of the nutritional status. The great advantage of this index is the easy way to measure, the low cost, the good correlation with the fat mass and the association to morbidity and mortality. OBJECTIVE: To compare the BMI differences according to the WHO, OPAS and Lipschitz classification. METHODS: A prospective study on 352 patients with esophageal, gastric or colorectal cancer was done. The BMI was calculated and analyzed by the classification of WHO, Lipschitz and OPAS. RESULTS: The mean age was 62.1 ± 12.4 years and 59% of them had more than 59 years. The BMI had not difference between the genders in patients <59 years (P = 0.75, but over 59 years the BMI was higher in women (P<0.01. The percentage of undernourished was 7%, 18% and 21% (P<0.01 by WHO, Lipschitz and OPAS, respectively. The overweight/obesity was also different among the various classifications (P<0.01. CONCLUSIONS: Most of the patients with gastrointestinal cancer had more than 65 years. A different cut off must be used for this patients, because undernourished patients may be wrongly considered well nourished.

  1. [Urine-based tumour diagnostics for bladder cancer: effects of the new histopathological classification--food for thought].

    Science.gov (United States)

    Knüchel, R; Lindemann-Docter, K

    2009-06-01

    The new WHO classification of bladder cancer was published in 2004 and consequently cannot be regarded as very recent. However, it is still timely since it picks up considerations affecting other schemes of tumour classification as well. Genetic results are included in the context of morphology, and at the same time a high inter- and intra-observer agreement is striven for as a matter of high quality patient care. The WHO classification of 2004 does not include cytological diagnosis. Thinking about and considering tumour tissue diagnosis, the style of cytological diagnoses is also affected. For tissue diagnoses, low- and high-grade tumours are differentiated from benign lesions including reactive changes. The element of this classification which has to be transferred to cytology is especially the unequivocal diagnosis of high-grade lesions. The low-grade lesion, correlating with tissue of well-differentiated papillary tumours and dysplasias, mostly cannot be distinguished cytologically with certainty from a broad spectrum of non-malignant lesions (papillomas, reactive urothelial detachment in urolithiasis patients, cytology specimen from vigorously irrigated bladders). For the latter group our aim should be to establish an additional diagnostic tool of high quality driven by clinical questions (e.g. potential of tumour progression).

  2. Argumentation Quality of Socio-scientific Issue between High School Students and Postgraduate Students about Cancer

    Science.gov (United States)

    Anisa, A.; Widodo, A.; Riandi, R.

    2017-09-01

    Argumentation is one factor that can help improve critical thinking skills. Arguing means to defend statements with the various data, denials, evidence, and reinforcement that support the statement. The research aimed to capture the quality of argument skills by students in grade 12 high school students and in postgraduate student on social-scientific issues of cancer. Both group subjects are not in the same school or institution, chosen purposively with the subject of 39 high school students of grade 12 in one district of West Java and 13 students of Biology education postgraduate in one of University in West Java - Indonesia. The results of the quality structure of arguments in both subject groups show the same pattern, which is claim - warrant - and ground, with the quality of counterclaim aspects on the postgraduate students look better than grade 12 students. This provides an illustration that the ability in argumentation between students and teachers in the socio-scientific issue of cancer should be evaluate so that the learning process would be more refined in schools.

  3. Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification

    Directory of Open Access Journals (Sweden)

    D. Ramyachitra

    2015-09-01

    Full Text Available Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM, K-nearest neighbor (KNN, Interval Valued Classification (IVC and the improvised Interval Value based Particle Swarm Optimization (IVPSO algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions.

  4. Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification.

    Science.gov (United States)

    Ramyachitra, D; Sofia, M; Manikandan, P

    2015-09-01

    Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM), K-nearest neighbor (KNN), Interval Valued Classification (IVC) and the improvised Interval Value based Particle Swarm Optimization (IVPSO) algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions.

  5. Practical Issues with the Use of Stem Cells for Cancer Gene Therapy.

    Science.gov (United States)

    Nouri, Faranak Salman; Banerjee, Debabrata; Hatefi, Arash

    2015-10-01

    Stem cell-based drug delivery for cancer therapy has steadily gained momentum in the past decade as several studies have reported stem cells' inherent tropism towards tumors. Since this science is still in its early stages and there are many factors that could significantly impact tumor tropism of stem cells, some contradictory results have been observed. This review starts by examining a number of proof-of-concept studies that demonstrate the potential application of stem cells in cancer therapy. Studies that illustrate stem cells' tumor tropism and discuss the technical difficulties that could impact the therapeutic outcome are also highlighted. The discussion also emphasizes stem cell imaging/tracking, as it plays a crucial role in performing reliable dose-response studies and evaluating the therapeutic outcome of treatment protocols. In each section, the pros and cons associated with each method are highlighted, limitations are underlined, and potential solutions are discussed. The overall intention is to familiarize the reader with important practical issues related to stem cell cancer tropism and in vivo tracking, underline the shortcomings, and emphasize critical factors that need to be considered for effective translation of this science into the clinic.

  6. Role of Graphene Nano-Composites in Cancer Therapy: Theranostic Applications, Metabolic Fate and Toxicity Issues.

    Science.gov (United States)

    Rahman, Mahfoozur; Ahmad, Mohammad Zaki; Ahmad, Javed; Firdous, Jamia; Ahmad, Farhan Jalees; Mushtaq, Gohar; Kamal, Mohammad A; Akhter, Sohail

    2015-01-01

    Graphene and its modified nano-composites have gained much attention in recent times in cancer therapy as nanotheranostics due to low production cost, ease in synthesis and physicochemical properties (ultra-large surface area with planar structure and π-π conjugation with the unsaturated and aromatic drugs/biomolecules) being favorable for multiple payloads and drug targeting. Yet, graphene nano-composites are a relatively new and rapid development. The adoption of graphene nano-composites in cancer nanobiomedicine research raises questions about in vivo metabolism and disposition as well as biological interaction and safety profile of these nano-particles. Limited in-vitro and in-vivo findings are available in literature, indicating the inconsistencies about the factors affecting in-vivo bio-interaction and toxicity. Presently, there is a lack of anticipated biodistribution and toxicity pattern of graphene. It appears that surface functionalization, biocompatible coating, and size are the key factors in determining the metabolic fate of graphene nano-composites. In-vitro and in-vivo toxicity data suggests that graphene nano-composites exhibit dose and size dependent toxicity. This review summarizes up-to-date research outcome of this promising inorganic nanomaterial for cancer therapy. Moreover, the metabolic fate and toxicity issues of graphene and its nano-composites shall also be discussed in detail.

  7. Appraisal of selected epidemiologic issues from studies of lung cancer among uranium and hard rock miners

    Energy Technology Data Exchange (ETDEWEB)

    Petersen, G R; Sever, L E

    1982-04-01

    An extensive body of published information about lung cancer among uranium miners was reviewed and diverse information, useful in identifying important issues but not in resolving them was found. Measuring exposure and response; thresholds of exposure; latency or the period from first mining experience to death; effort to predict excess risk of death, using a model; effects of smoking and radon daughter exposure on the histology of lung tumors; and the interplay of factors on the overall risk of death were all examined. The general concept of thresholds; that is, an exposure level below which risk does not increase was considered. The conclusion is that it should be possible to detect and estimate an epidemiologic threshold when the cohorts have been followed to the death of all members. Issues concerning latency in the studies of uranium miners published to date were examined. It is believed that the induction-latent period for lung cancer among uranium miners may be: as little as 10 to more than 40 years; dependent on age at which exposure begins; exposure rate; and ethnicity or smoking habits. Although suggested as factual, their existence is uncertain. An effect due to the exposure rate may exist although it has not been factual, their existence is uncertain. An effect due to the exposure rate may exist although it has not been confirmed. The median induction-latent period appears to be in excess of the 15 years frequently cited for US uranium miner. A distinct pattern of shorter induction-latent periods with increasing age at first mining exposure is reported. The evidence for and against an unusual histologic pattern of lung cancers among uranium miners was examined. The ratio of epidermoid to small cell types was close to 1:2; the ratio in the general population is nearer 2:1. The histologic pattern warrants closer attention of pathologists and epidemiologists. (ERB) (ERB)

  8. Restaging and Survival Analysis of 4036 Ovarian Cancer Patients According to the 2013 FIGO Classification for Ovarian, Fallopian Tube, and Primary Peritoneal Cancer

    DEFF Research Database (Denmark)

    Rosendahl, Mikkel; Høgdall, Claus Kim; Mosgaard, Berit Jul

    2016-01-01

    OBJECTIVE: With the 2013 International Federation of Gynecology and Obstetrics (FIGO) staging for ovarian, fallopian tube, and primary peritoneal cancer, the number of substages changed from 10 to 14. Any classification of a malignancy should easily assign patients to prognostic groups, refer...... patients to individualized treatments, and allow benchmarking and comparison of patients and results between centers. The stage should reflect survival in particular. The objective of the study was to validate these requirements of the revised FIGO staging on a high number of ovarian cancer patients....... MATERIALS AND METHODS: Demographic, surgical, histological, and survival data from 4036 ovarian cancer patients were used in the analysis. Five-year survival rates (5YSR) and hazard ratios for the old and revised FIGO staging were calculated using Kaplan-Meier curves and Cox regression. RESULTS: A total...

  9. 'Rapid discharge': issues for hospital-based nurses in discharging cancer patients home to die.

    Science.gov (United States)

    Tan, Yung Ying; Blackford, Jeanine

    2015-09-01

    To explore issues for hospital-based nurses in arranging rapid home discharge for imminently dying cancer patients in a Singapore acute hospital. Dying at home is an important measure of a 'good death'. For hospitalised terminally ill patients, achieving home death can be of paramount importance to them and their family. Nurses experience many challenges in discharging imminently dying cancer patients home, due to time limitations and complex needs of patients and their families. Qualitative interpretive description. Using purposive sampling, 14 registered nurses from an oncology ward in a Singapore hospital were recruited to participate in individual, semi-structured interviews. Nursing issues in facilitating rapid discharge fell into three categories: time, discharge processes and family preparation. Decisions to die at home appeared solely family/patient driven, and were made when death appeared imminent. Discharge then became time-critical, as nurses needed to complete multiple tasks within short timeframes. Stress was further exacerbated by nurses' inexperience and the infrequent occurrence of rapid discharge, as well as absence of standardised discharge framework for guidance. Together, the lack of time and discharge processes to enable smooth hospital-to-home transition potentially affected nurses' capacity to adequately prepare families, and may contribute to caregiver anxiety. Rapid discharge processes are needed as sudden patient/family decisions to die at home will continue. Earlier involvement of palliative care and implementation of a discharge pathway can potentially help nurses address their multiple responsibilities to ensure a successful transition from hospital to home. Recognition of nursing issues and challenges during rapid discharge has implications for clinical improvements in supporting nurses during this challenging situation. Results of this study can be used to inform the conceptualisation of clinical interventions to facilitate urgent

  10. Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set

    Science.gov (United States)

    Li, Hui; Zhu, Yitan; Burnside, Elizabeth S; Huang, Erich; Drukker, Karen; Hoadley, Katherine A; Fan, Cheng; Conzen, Suzanne D; Zuley, Margarita; Net, Jose M; Sutton, Elizabeth; Whitman, Gary J; Morris, Elizabeth; Perou, Charles M; Ji, Yuan; Giger, Maryellen L

    2016-01-01

    Using quantitative radiomics, we demonstrate that computer-extracted magnetic resonance (MR) image-based tumor phenotypes can be predictive of the molecular classification of invasive breast cancers. Radiomics analysis was performed on 91 MRIs of biopsy-proven invasive breast cancers from National Cancer Institute’s multi-institutional TCGA/TCIA. Immunohistochemistry molecular classification was performed including estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and for 84 cases, the molecular subtype (normal-like, luminal A, luminal B, HER2-enriched, and basal-like). Computerized quantitative image analysis included: three-dimensional lesion segmentation, phenotype extraction, and leave-one-case-out cross validation involving stepwise feature selection and linear discriminant analysis. The performance of the classifier model for molecular subtyping was evaluated using receiver operating characteristic analysis. The computer-extracted tumor phenotypes were able to distinguish between molecular prognostic indicators; area under the ROC curve values of 0.89, 0.69, 0.65, and 0.67 in the tasks of distinguishing between ER+ versus ER−, PR+ versus PR−, HER2+ versus HER2−, and triple-negative versus others, respectively. Statistically significant associations between tumor phenotypes and receptor status were observed. More aggressive cancers are likely to be larger in size with more heterogeneity in their contrast enhancement. Even after controlling for tumor size, a statistically significant trend was observed within each size group (P=0.04 for lesions ⩽2 cm; P=0.02 for lesions >2 to ⩽5 cm) as with the entire data set (P-value=0.006) for the relationship between enhancement texture (entropy) and molecular subtypes (normal-like, luminal A, luminal B, HER2-enriched, basal-like). In conclusion, computer-extracted image phenotypes show promise for high-throughput discrimination of breast cancer subtypes and may yield a

  11. Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set.

    Science.gov (United States)

    Li, Hui; Zhu, Yitan; Burnside, Elizabeth S; Huang, Erich; Drukker, Karen; Hoadley, Katherine A; Fan, Cheng; Conzen, Suzanne D; Zuley, Margarita; Net, Jose M; Sutton, Elizabeth; Whitman, Gary J; Morris, Elizabeth; Perou, Charles M; Ji, Yuan; Giger, Maryellen L

    2016-01-01

    Using quantitative radiomics, we demonstrate that computer-extracted magnetic resonance (MR) image-based tumor phenotypes can be predictive of the molecular classification of invasive breast cancers. Radiomics analysis was performed on 91 MRIs of biopsy-proven invasive breast cancers from National Cancer Institute's multi-institutional TCGA/TCIA. Immunohistochemistry molecular classification was performed including estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and for 84 cases, the molecular subtype (normal-like, luminal A, luminal B, HER2-enriched, and basal-like). Computerized quantitative image analysis included: three-dimensional lesion segmentation, phenotype extraction, and leave-one-case-out cross validation involving stepwise feature selection and linear discriminant analysis. The performance of the classifier model for molecular subtyping was evaluated using receiver operating characteristic analysis. The computer-extracted tumor phenotypes were able to distinguish between molecular prognostic indicators; area under the ROC curve values of 0.89, 0.69, 0.65, and 0.67 in the tasks of distinguishing between ER+ versus ER-, PR+ versus PR-, HER2+ versus HER2-, and triple-negative versus others, respectively. Statistically significant associations between tumor phenotypes and receptor status were observed. More aggressive cancers are likely to be larger in size with more heterogeneity in their contrast enhancement. Even after controlling for tumor size, a statistically significant trend was observed within each size group (P = 0.04 for lesions ≤ 2 cm; P = 0.02 for lesions >2 to ≤5 cm) as with the entire data set (P-value = 0.006) for the relationship between enhancement texture (entropy) and molecular subtypes (normal-like, luminal A, luminal B, HER2-enriched, basal-like). In conclusion, computer-extracted image phenotypes show promise for high-throughput discrimination of breast cancer subtypes and may yield a

  12. Oral epithelial dysplasia classification systems

    DEFF Research Database (Denmark)

    Warnakulasuriya, S; Reibel, J; Bouquot, J

    2008-01-01

    At a workshop coordinated by the WHO Collaborating Centre for Oral Cancer and Precancer in the United Kingdom issues related to potentially malignant disorders of the oral cavity were discussed by an expert group. The consensus views of the Working Group are presented in a series of papers....... In this report, we review the oral epithelial dysplasia classification systems. The three classification schemes [oral epithelial dysplasia scoring system, squamous intraepithelial neoplasia and Ljubljana classification] were presented and the Working Group recommended epithelial dysplasia grading for routine...... use. Although most oral pathologists possibly recognize and accept the criteria for grading epithelial dysplasia, firstly based on architectural features and then of cytology, there is great variability in their interpretation of the presence, degree and significance of the individual criteria...

  13. Breast cancer screening among women younger than age 50: a current assessment of the issues.

    Science.gov (United States)

    Smith, R A

    2000-01-01

    In the hope of resolving underlying policy questions related to the value of breast cancer screening with mammography for women younger than 50 years of age, the National Institutes of Health and the National Cancer Institute in 1997 jointly sponsored a consensus conference on the subject. While the panel concluded that the data were insufficient to endorse mammography for this age group apart from individual choice, the conclusion was not the "consensus" sought by many of those with strong opinions on both sides of this issue, and the debate raged on. Prior to the 1997 conference, and since, meta-analyses of trial data and assessments of service screening programs have indicated that breast cancer screening with mammography for women between 40 and 49 meets recommended levels of performance compared with performance in women 50 years and older, especially if programs achieve high quality and screen at 12-to-18 month intervals. Because the detectable preclinical phase is shorter in younger women who develop breast cancer compared with that in women 50 years of age or older, a key component of any screening program for those younger than 50 is an appropriate screening interval. Many of the screening programs that had historically been developed for women in their forties--and whose disappointing results contributed to the confusion and controversy about the efficacy of mammography in younger women--had a 24-month screening interval, which was not found to be of significant benefit for early detection of breast cancer in this age group. While a new emphasis of this controversy has focused on the balance of benefits and harms in women ages 40 to 49, women of all ages need to be fully informed about the benefits and limitations of breast cancer screening--more specifically, what to expect at the time of screening, and what to expect from screening. There are differences in the performance and effectiveness of mammography in different age groups of women aged 40 and

  14. A neglected issue on sexual well-being following breast cancer diagnosis and treatment among Chinese women.

    Directory of Open Access Journals (Sweden)

    Fengliang Wang

    Full Text Available BACKGROUND: Changes to sexual well-being can be one of the most problematic quality of life issues following the diagnosis and treatment of breast cancer. The objectives of the present study were to evaluate changes to sexual well-being following breast cancer, to expand upon the existing body of knowledge pertaining to breast cancer and sexuality, and to provide the necessary information for implementing future interventions that may help improve the quality of life in breast cancer patients. METHODS: This study was mixed with qualitative and quantitative designs. Twenty patients with breast cancer were recruited for in-depth interviews. The central questions covered a patient's cancer experience and perceptions of sexual activities following breast cancer. According to the findings of the qualitative study, we performed a quantitative study using a structured questionnaire to collect data on patient's experience and attitude to sexual well-being following breast cancer diagnosis and treatment. RESULTS: Based on the qualitative analysis, seven main themes emerged: (1 Decrease in sexual frequency; (2 Lack of sexual interest; (3 Menopausal symptoms; (4 Body image changes; (5 Effects on marital relationship; (6 Misconceptions about sex; (7 The need for professional consultation. Results from the quantitative study further supported the findings from the qualitative analysis, where changes to sexual well-being were common following cancer diagnosis and treatment and it was a neglected issue among Chinese women. CONCLUSIONS: The present study highlights the significant changes to sexual well-being following breast cancer, in addition to the lack of knowledge and misconceptions of sexual activity among patients. Addressing these problems will help improve a patient's quality of life. The findings of this study could help healthcare professionals recognize the sexual issues faced by women with breast cancer and ultimately promote a healthy life.

  15. Dealing with symptoms and issues of hospitalized patients with cancer in indonesia: the role of families, nurses, and physicians.

    Science.gov (United States)

    Effendy, Christantie; Vissers, Kris; Tejawinata, Sunaryadi; Vernooij-Dassen, Myrra; Engels, Yvonne

    2015-06-01

    Patients with cancer often face physical, psychological, social, spiritual, and emotional symptoms. Our aim was to study symptoms and issues of hospitalized patients with cancer in Indonesia, a country with strong family ties, and how family members, nurses, and physicians deal with them. In 2011, 150 hospitalized cancer patients in 3 general hospitals in Indonesia were invited to fill in a questionnaire, which was based on the validated Problems and Needs of Palliative Care (short version) questionnaire. Descriptive statistics were performed. Of 119 patients (79%) who completed the questionnaire, 85% stated that their symptoms and issues were addressed. According to these patients, financial (56%), autonomy (36%), and psychosocial (34%) issues were most often addressed by the family alone. Physical symptoms (52%) and spiritual issues (33%) were addressed mainly by a combination of family, nurses, and physicians. Hospitalized patients with cancer in Indonesia felt that most of their symptoms and issues had been addressed, and the family was highly involved. The strong family ties in Indonesian culture may have contributed to this family role. More research is needed to clarify how this influences patient outcome, quality of care, and quality of life of both the patients and their families, along with the degree of partnership between families and professionals. This information might help answer the question what advantages and disadvantages the family role in caring for a hospitalized patient with cancer generates for the patient, the family, and professional caregivers. © 2014 World Institute of Pain.

  16. Femur fracture classification in women with a history of breast cancer

    OpenAIRE

    Chau, Stephanie; Chandra, Malini; Grimsrud, Christopher D.; Gonzalez, Joel R.; Hui, Rita L; Lo, Joan C.

    2014-01-01

    Purpose: Women with breast cancer are at increased risk for femur fracture. Contributing factors include estrogen deficiency, cancer-related therapies, or direct bone involvement. This study examines fracture subtypes in women with prior breast cancer experiencing a femur fracture. Methods: Women age ≥50 years old with a history of invasive breast cancer who experienced a femur fracture were identified during 2005–2012. Fracture site was classified by hospital diagnosis (for hip) and/or ra...

  17. Psychosocial issues of the adolescent cancer patient and the development of the Teenage Outreach Program (TOP).

    Science.gov (United States)

    Shama, Wendy; Lucchetta, Sonia

    2007-01-01

    For young people with cancer their process through adolescence is marked with disruption. The demands of treatment and resulting social isolation combined with issues of body image/self-esteem complicate this turbulent life cycle transition. The effects of'these disruptions require psychosocial staff to utilize creative approaches to treatment. The framework of the Teen Outreach Program (TOP) is to connect teens with leukemia/lymphoma to one another, and to reconnect them back with their peers by engaging them in "normal" events. The overwhelming response highlights the positive effect on teenagers' psychosocial health, thereby solidifying the importance of providing innovative therapeutic interventions for this under-serviced population. Further studies of the long-term impact of the program's success are warranted.

  18. Thermographic image analysis for classification of ACL rupture disease, bone cancer, and feline hyperthyroid, with Gabor filters

    Science.gov (United States)

    Alvandipour, Mehrdad; Umbaugh, Scott E.; Mishra, Deependra K.; Dahal, Rohini; Lama, Norsang; Marino, Dominic J.; Sackman, Joseph

    2017-05-01

    Thermography and pattern classification techniques are used to classify three different pathologies in veterinary images. Thermographic images of both normal and diseased animals were provided by the Long Island Veterinary Specialists (LIVS). The three pathologies are ACL rupture disease, bone cancer, and feline hyperthyroid. The diagnosis of these diseases usually involves radiology and laboratory tests while the method that we propose uses thermographic images and image analysis techniques and is intended for use as a prescreening tool. Images in each category of pathologies are first filtered by Gabor filters and then various features are extracted and used for classification into normal and abnormal classes. Gabor filters are linear filters that can be characterized by the two parameters wavelength λ and orientation θ. With two different wavelength and five different orientations, a total of ten different filters were studied. Different combinations of camera views, filters, feature vectors, normalization methods, and classification methods, produce different tests that were examined and the sensitivity, specificity and success rate for each test were produced. Using the Gabor features alone, sensitivity, specificity, and overall success rates of 85% for each of the pathologies was achieved.

  19. Interactive Naive Bayesian network: A new approach of constructing gene-gene interaction network for cancer classification.

    Science.gov (United States)

    Tian, Xue W; Lim, Joon S

    2015-01-01

    Naive Bayesian (NB) network classifier is a simple and well-known type of classifier, which can be easily induced from a DNA microarray data set. However, a strong conditional independence assumption of NB network sometimes can lead to weak classification performance. In this paper, we propose a new approach of interactive naive Bayesian (INB) network to weaken the conditional independence of NB network and classify cancers using DNA microarray data set. We selected the differently expressed genes (DEGs) to reduce the dimension of the microarray data set. Then, an interactive parent which has the biggest influence among all DEGs is searched for each DEG. And then we calculate a weight to represent the interactive relationship between a DEG and its parent. Finally, the gene-gene interaction network is constructed. We experimentally test the INB network in terms of classification accuracy using leukemia and colon DNA microarray data sets, then we compare it with the NB network. The INB network can get higher classification accuracies than NB network. And INB network can show the gene-gene interactions visually.

  20. Barriers to breast cancer control for African-American women: the interdependence of culture and psychosocial issues.

    Science.gov (United States)

    Guidry, Jeffrey J; Matthews-Juarez, Patricia; Copeland, Valerie A

    2003-01-01

    This study evaluates the cultural context of the behaviors and beliefs of African-American women to determine the success or failure of breast cancer prevention and control interventions. Cultural and psychologic reactions, such as fear, distrust, fatalism, and other "historic rooted" factors, are major determinants to participation in these interventions by African-American women. Psychosocial and cultural issues were delineated through a literature review in the areas of cancer prevention, breast cancer control, and African-American women. Assessments were conducted to document key successful models and activities that increased the participation of African-American women in breast cancer prevention and control interventions. Current community-based intervention strategies and activities were assessed. Effective breast cancer prevention and control programs must address and develop cultural competent models that promote behavioral change in this population of women. Studying the relationship between culture and psychosocial issues is integral to our understanding of how African-American women participate and respond to cancer prevention and control interventions. Cultural competent models that reduce and eliminate cancer disparities in this population must be developed. Copyright 2003 American Cancer Society.DOI 10.1002/cncr.11016

  1. Classification of Colon Cancer Patients Based on the Methylation Patterns of Promoters

    Directory of Open Access Journals (Sweden)

    Wonyoung Choi

    2016-06-01

    Full Text Available Diverse somatic mutations have been reported to serve as cancer drivers. Recently, it has also been reported that epigenetic regulation is closely related to cancer development. However, the effect of epigenetic changes on cancer is still elusive. In this study, we analyzed DNA methylation data on colon cancer taken from The Caner Genome Atlas. We found that several promoters were significantly hypermethylated in colon cancer patients. Through clustering analysis of differentially methylated DNA regions, we were able to define subgroups of patients and observed clinical features associated with each subgroup. In addition, we analyzed the functional ontology of aberrantly methylated genes and identified the G-protein-coupled receptor signaling pathway as one of the major pathways affected epigenetically. In conclusion, our analysis shows the possibility of characterizing the clinical features of colon cancer subgroups based on DNA methylation patterns and provides lists of important genes and pathways possibly involved in colon cancer development.

  2. IDM-PhyChm-Ens: intelligent decision-making ensemble methodology for classification of human breast cancer using physicochemical properties of amino acids.

    Science.gov (United States)

    Ali, Safdar; Majid, Abdul; Khan, Asifullah

    2014-04-01

    Development of an accurate and reliable intelligent decision-making method for the construction of cancer diagnosis system is one of the fast growing research areas of health sciences. Such decision-making system can provide adequate information for cancer diagnosis and drug discovery. Descriptors derived from physicochemical properties of protein sequences are very useful for classifying cancerous proteins. Recently, several interesting research studies have been reported on breast cancer classification. To this end, we propose the exploitation of the physicochemical properties of amino acids in protein primary sequences such as hydrophobicity (Hd) and hydrophilicity (Hb) for breast cancer classification. Hd and Hb properties of amino acids, in recent literature, are reported to be quite effective in characterizing the constituent amino acids and are used to study protein foldings, interactions, structures, and sequence-order effects. Especially, using these physicochemical properties, we observed that proline, serine, tyrosine, cysteine, arginine, and asparagine amino acids offer high discrimination between cancerous and healthy proteins. In addition, unlike traditional ensemble classification approaches, the proposed 'IDM-PhyChm-Ens' method was developed by combining the decision spaces of a specific classifier trained on different feature spaces. The different feature spaces used were amino acid composition, split amino acid composition, and pseudo amino acid composition. Consequently, we have exploited different feature spaces using Hd and Hb properties of amino acids to develop an accurate method for classification of cancerous protein sequences. We developed ensemble classifiers using diverse learning algorithms such as random forest (RF), support vector machines (SVM), and K-nearest neighbor (KNN) trained on different feature spaces. We observed that ensemble-RF, in case of cancer classification, performed better than ensemble-SVM and ensemble-KNN. Our

  3. Computerized three-class classification of MRI-based prognostic markers for breast cancer

    Science.gov (United States)

    Bhooshan, Neha; Giger, Maryellen; Edwards, Darrin; Yuan, Yading; Jansen, Sanaz; Li, Hui; Lan, Li; Sattar, Husain; Newstead, Gillian

    2011-09-01

    The purpose of this study is to investigate whether computerized analysis using three-class Bayesian artificial neural network (BANN) feature selection and classification can characterize tumor grades (grade 1, grade 2 and grade 3) of breast lesions for prognostic classification on DCE-MRI. A database of 26 IDC grade 1 lesions, 86 IDC grade 2 lesions and 58 IDC grade 3 lesions was collected. The computer automatically segmented the lesions, and kinetic and morphological lesion features were automatically extracted. The discrimination tasks—grade 1 versus grade 3, grade 2 versus grade 3, and grade 1 versus grade 2 lesions—were investigated. Step-wise feature selection was conducted by three-class BANNs. Classification was performed with three-class BANNs using leave-one-lesion-out cross-validation to yield computer-estimated probabilities of being grade 3 lesion, grade 2 lesion and grade 1 lesion. Two-class ROC analysis was used to evaluate the performances. We achieved AUC values of 0.80 ± 0.05, 0.78 ± 0.05 and 0.62 ± 0.05 for grade 1 versus grade 3, grade 1 versus grade 2, and grade 2 versus grade 3, respectively. This study shows the potential for (1) applying three-class BANN feature selection and classification to CADx and (2) expanding the role of DCE-MRI CADx from diagnostic to prognostic classification in distinguishing tumor grades.

  4. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Directory of Open Access Journals (Sweden)

    Enrico Glaab

    Full Text Available Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  5. [Magnetic resonance semiotics of prostate cancer according to the PI-RADS classification. The clinical diagnostic algorithm of a study].

    Science.gov (United States)

    Korobkin, A S; Shariya, M A; Chaban, A S; Voskanvan, G A; Vinarov, A Z

    2015-01-01

    to elaborate the magnetic resonance imaging (MRI) signs of prostate cancer (PC) in accordance with the PI-RADS classification during multiparametric MRI (mpMRI). A total of 89 men aged 20 to 82 years were examined. A control group consisted of 8 (9%) healthy volunteers younger than 30 years of age with no urological history to obtain control images and MRI plots and 20 (22.5%) men aged 26-76 years, whose morphological changes were inflammatory and hyperplastic. The second age-matched group included 61 (68.5%) patients diagnosed with prostate cancer at morphological examination. A set of studies included digital rectal examination, serum prostate-specific antigen, and transrectal ultrasound-guided prostate biopsy. All the patients underwent prostate mpMRI applying a 3.0 T Achieva MRI scanner (Philips, the Netherlands). The patients have been found to have mpMRI signs that were typical of PC; its MRI semiotics according to the PI-RADS classification is presented. Each mpMRI procedure has been determined to be of importance and informative value in detecting PC. The comprehensive mpMRI approach to diagnosing PC improves the quality and diagnostic value of prostate MRI.

  6. Prophylactic human papillomavirus vaccination and primary prevention of cervical cancer: issues and challenges.

    Science.gov (United States)

    Poljak, M

    2012-10-01

    Two prophylactic human papillomavirus (HPV) vaccines have been recently approved: one quadrivalent and the other a bivalent vaccine. When administered in a three-dose course to HPV-naive individuals, both vaccines exhibited excellent safety profiles and were highly efficacious against targeted clinical endpoints in large-scale international phase III clinical trials. Where coverage has been high for the appropriate target population, a reduction of HPV-related diseases with the shortest incubation periods has already been seen. By March 2012, universal HPV vaccination had been introduced into national vaccination programmes in more than 40 countries, but only in a few low-income and middle-income countries. With the growing market for HPV vaccines and competition between manufacturers, negotiated prices are already beginning to decline although they still remain out of reach of many countries. The great majority of countries are struggling to reach a level of coverage that will have the most impact on cervical cancer rates. Increasing coverage and improving completion of the HPV vaccine schedule, particularly of sexually naive females, is now the most important public-health issue in HPV vaccine efforts. A clear strategy for integrating primary (HPV vaccination) and secondary (screening) cervical cancer prevention must be agreed as soon as possible. Several second-generation prophylactic vaccines are being developed with the aim of resolving some of the limitations of the two current HPV prophylactic vaccines. © 2012 The Author. Clinical Microbiology and Infection © 2012 European Society of Clinical Microbiology and Infectious Diseases.

  7. Issues Faced by Family Caregivers of Hospice Patients with Head and Neck Cancers.

    Science.gov (United States)

    McMillan, Susan C; Rodriguez, Carmen; Wang, Hsiao-Lan; Elliott, Amanda

    2015-01-01

    The purpose of this study was to explore issues reported by caregivers of Head and Neck cancer (HNC) patients newly admitted to hospice homecare. 26 caregivers providing hospice homecare to patients with HNC were induded. Caregiver depressive symptoms, social support and perceived health data were analyzed. The caregivers reported few depressive symptoms, good perceived social support, and good perceived health; however, there was large variation in the group with some individuals having significant problems. Caregivers appeared to be doing well physically, emotionally and socially, but baseline data were used, so follow-up data are needed. Further research is warranted. Family caregivers also are affected by the experience of cancer and may have depressive symptoms needing assessment and management. Hospice patients with HNC have a variety of symptoms specific to their disease and treatment that need assessment and management by their family caregivers. Caregivers of HNC patients in hospice and palliative care need and deserve attention from hospice providers as they care for patients.

  8. Issues in using epidemiologic data to estimate cancer risks from environmental chemical exposures

    Energy Technology Data Exchange (ETDEWEB)

    Picciotto, I.-H.; Neutra, R.; Alexeeff, G.; Lipsett, M.; Holtzman, D. (California Department of Health Services, Berkeley, CA (USA))

    Quantitative assessment of cancer is an important health policy application of environmental epidemiology. This paper addresses how epidemiology can reduce uncertainty in estimates of cancer risk from environmental exposures. To extrapolate to low levels, epidemiologic studies need well-qualified exposure data, adequate control of confounding, and a positive dose-response trend. In cases such as cadmium and arsenic, a critical issue is the shape of the dose-response curve. The data on arsenic suggest that assumption of linearity may under-estimate risk. Other uncertainties arise in extrapolating from adult males in occupational settings to a heterogeneous population exposed environmentally. Epidemiologic studies with less exposure data or negative findings may be used for a risk assessment based on animal data (e.g., ethylene dibromide, ethylene oxide, and methylene chloride). Then the hypothesized effect level for humans depends on the animal-based potency and estimated human exposures. Therefore, statistical power hinges on study size and on exposure levels (ethylene oxide, methylene chloride, and saccharin). Comparisons of human epidemiologic data and animal bioassays may permit the rejection of models and a narrowing of the range of plausible risks (e.g., ethylene dibromide, cadmium), or suggest that the animal-based assessment is not contradicted by the epidemiologic data (e.g., ethylene oxide, acrylonitrile, methylene chloride).

  9. Validation and Modification of the Japanese Classification System for Liver Metastases from Colorectal Cancer: A Multi-institutional Study.

    Science.gov (United States)

    Shinto, Eiji; Takahashi, Keiichi; Yamaguchi, Tatsuro; Hashiguchi, Yojiro; Kotake, Kenjiro; Itabashi, Michio; Yasuno, Masamichi; Kanemitsu, Yukihide; Nishimura, Genichi; Akagi, Yoshito; Sato, Toshihiko; Kato, Tomoyuki; Matsumoto, Hiroshi; Hase, Kazuo; Sugihara, Kenichi

    2015-11-01

    A Japanese multicenter study disclosed four prognostic indicators of colorectal cancer liver metastases: ≥5 hepatic tumors (HT), HT size > 5 cm, nodal status (N2) of primary cancer, and the presence of extrahepatic metastases (EM). The Japanese classification was then defined as Stage A, HT1 (≤4 lesions and ≤5 cm) and N0/1; Stage B, HT2 (≥5 lesions or >5 cm) and N0/1, or HT1 and N2; and Stage C, HT2 and N2, HT3 (≥5 lesions and >5 cm) with any N, or EM1 (presence of EM) with any HT/N. This study aimed to validate the prognostic reliability in a recent population and to develop a modified staging system that divided Stage C patients. A total of 1185 patients diagnosed with liver metastases between 2007 and 2008 were enrolled in the study. According to the classification, 358, 257, and 570 patients were categorized as Stages A, B, and C, respectively. Stage C was further divided into two groups: Stage C-I, HT3 and N0/1, HT2 and N2, or HT1 and EM1; and Stage C-II, HT3 and N2, or HT2/3 and EM1. Cumulative overall survival curves for Stages A, B, and C were significantly different between each two stages (p < 0.0001, p < 0.0001). The modified system discriminated patients with a relatively better outcome (Stage C-I) from desperate patients (Stage C-II) (p < 0.0001). The Japanese classification system was adequately validated in a recent population, and the modified system is useful in risk stratification of Stage C cases.

  10. Mechanism-based classification and physical therapy management of persons with cancer pain: A prospective case series

    Directory of Open Access Journals (Sweden)

    Senthil P Kumar

    2013-01-01

    Full Text Available Context: Mechanism-based classification (MBC was established with current evidence and physical therapy (PT management methods for both cancer and for noncancer pain. Aims: This study aims to describe the efficacy of MBC-based PT in persons with primary complaints of cancer pain. Settings and Design: A prospective case series of patients who attended the physiotherapy department of a multispecialty university-affiliated teaching hospital. Material and Methods: A total of 24 adults (18 female, 6 male aged 47.5 ± 10.6 years, with primary diagnosis of heterogeneous group of cancer, chief complaints of chronic disabling pain were included in the study on their consent for participation The patients were evaluated and classified on the basis of five predominant mechanisms for pain. Physical therapy interventions were recommended based on mechanisms identified and home program was prescribed with a patient log to ensure compliance. Treatments were given in five consecutive weekly sessions for five weeks each of 30 min duration. Statistical Analysis Used: Pre-post comparisons for pain severity (PS and pain interference (PI subscales of Brief pain inventory-Cancer pain (BPI-CP and, European organization for research and treatment in cancer-quality of life questionnaire (EORTC-QLQ-C30 were done using Wilcoxon signed-rank test at 95% confidence interval using SPSS for Windows version 16.0 (SPSS Inc, Chicago, IL. Results: There were statistically significant ( P < 0.05 reduction in pain severity, pain interference and total BPI-CP scores, and the EORTC-QLQ-C30. Conclusion: MBC-PT was effective for improving BPI-CP and EORTC-QLQ-C30 scores in people with cancer pain.

  11. Breast Cancer Survival Defined by the ER/PR/HER2 Subtypes and a Surrogate Classification according to Tumor Grade and Immunohistochemical Biomarkers

    Directory of Open Access Journals (Sweden)

    Carol A. Parise

    2014-01-01

    Full Text Available Introduction. ER, PR, and HER2 are routinely available in breast cancer specimens. The purpose of this study is to contrast breast cancer-specific survival for the eight ER/PR/HER2 subtypes with survival of an immunohistochemical surrogate for the molecular subtype based on the ER/PR/HER2 subtypes and tumor grade. Methods. We identified 123,780 cases of stages 1–3 primary female invasive breast cancer from California Cancer Registry. The surrogate classification was derived using ER/PR/HER2 and tumor grade. Kaplan-Meier survival analysis and Cox proportional hazards modeling were used to assess differences in survival and risk of mortality for the ER/PR/HER2 subtypes and surrogate classification within each stage. Results. The luminal B/HER2− surrogate classification had a higher risk of mortality than the luminal B/HER2+ for all stages of disease. There was no difference in risk of mortality between the ER+/PR+/HER2− and ER+/PR+/HER2+ in stage 3. With one exception in stage 3, the ER-negative subtypes all had an increased risk of mortality when compared with the ER-positive subtypes. Conclusions. Assessment of survival using ER/PR/HER2 illustrates the heterogeneity of HER2+ subtypes. The surrogate classification provides clear separation in survival and adjusted mortality but underestimates the wide variability within the subtypes that make up the classification.

  12. Systematic review of the health-related quality of life issues facing adolescents and young adults with cancer.

    Science.gov (United States)

    Sodergren, Samantha C; Husson, Olga; Robinson, Jessica; Rohde, Gudrun E; Tomaszewska, Iwona M; Vivat, Bella; Dyar, Rebecca; Darlington, Anne-Sophie

    2017-07-01

    For adolescents and young adults (AYAs), the impact of a cancer diagnosis and subsequent treatment is likely to be distinct from other age groups given the unique and complex psychosocial challenges of this developmental phase. In this review of the literature, we report the health-related quality of life (HRQoL) issues experienced by AYAs diagnosed with cancer and undergoing treatment. MEDLINE, EMBASE, CINAHL, PsychINFO and the Cochrane Library Databases were searched for publications reporting HRQoL of AYAs. Issues generated from interviews with AYAs or from responses to patient reported outcome measures (PROMs) were extracted. 166 papers were reviewed in full and comprised 72 papers covering 69 primary studies, 49 measurement development or evaluation papers and 45 reviews. Of the 69 studies reviewed, 11 (16%) used interviews to elicit AYAs' descriptions of HRQoL issues. The majority of the PROMs used in the studies represent adaptations of paediatric or adult measures. HRQoL issues were organised into the following categories: physical, cognitive, restricted activities, relationships with others, fertility, emotions, body image and spirituality/outlook on life. The HRQoL issues presented within this review are likely to be informative to health care professionals and AYAs. The extensive list of issues suggests that the impact of a cancer diagnosis and treatment during adolescence and young adulthood is widespread and reflects the complexities of this developmental phase.

  13. 4-IHC classification of breast cancer subtypes in a large cohort of a clinical cancer registry: use in clinical routine for therapeutic decisions and its effect on survival.

    Science.gov (United States)

    Inwald, Elisabeth Christine; Koller, M; Klinkhammer-Schalke, M; Zeman, F; Hofstädter, F; Gerstenhauer, M; Brockhoff, G; Ortmann, O

    2015-10-01

    The aim of the present study was to evaluate to what extent the combination of standard histopathological parameters determines the biology of breast cancer and the effect on therapy and prognosis. The Clinical Cancer Registry Regensburg (Bavaria, Germany) included n = 4,480 female patients with primary, non-metastatic (M0) invasive breast cancer diagnosed between 2000 and 2012. Immuno-histochemical analyses, i.e., estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki-67 (4-IHC), defined the tumor biological subtypes Luminal A, Luminal B, HER2-like, and Basal-like. Subtype-related differences in therapies and overall survival (OS) were analyzed using multivariable statistical methods. 4344 patients (97.0 %) could be classified into the four common tumor biological subtypes. The two most frequent entities were Luminal A (48.4 %), Luminal B (24.8 %), HER2-like (17.8 %), and Basal-like subtype (9.0 %). A multivariable Cox regression model showed that the best 7-year OS was seen in Luminal A patients and that OS of Luminal B and HER2-like patients was comparable (HR = 1.59, P < 0.001 versus HR = 1.51, P = 0.03). Lowest OS was seen in patients with Basal-like tumors (HR = 2.18, P < 0.001). In conclusion, the classification of tumor biological subtypes by the ER, PR, HER2, and Ki-67 biomarkers is practical in routine clinical work. Providing that quality assurance of these markers is ensured, this classification is useful for making therapy decisions in the routine clinical management of breast cancer patients.

  14. North American Magazine Coverage of Skin Cancer and Recreational Tanning Before and After the WHO/IARC 2009 Classification of Indoor Tanning Devices as Carcinogenic.

    Science.gov (United States)

    McWhirter, Jennifer E; Hoffman-Goetz, Laurie

    2015-09-01

    The mass media is an influential source of skin cancer information for the public. In 2009, the World Health Organization's International Agency for Research on Cancer classified UV radiation from tanning devices as carcinogenic. Our objective was to determine if media coverage of skin cancer and recreational tanning increased in volume or changed in nature after this classification. We conducted a directed content analysis on 29 North American popular magazines (2007-2012) to investigate the overall volume of articles on skin cancer and recreational tanning and, more specifically, the presence of skin cancer risk factors, UV behaviors, and early detection information in article text (n = 410) and images (n = 714). The volume of coverage on skin cancer and recreational tanning did not increase significantly after the 2009 classification of tanning beds as carcinogenic. Key-related messages, including that UV exposure is a risk factor for skin cancer and that indoor tanning should be avoided, were not reported more frequently after the classification, but the promotion of the tanned look as attractive was conveyed more often in images afterwards (p magazines.

  15. Cancer adjuvant chemotherapy strategic classification by artificial neural network with gene expression data: An example for non-small cell lung cancer.

    Science.gov (United States)

    Chen, Yen-Chen; Chang, Yo-Cheng; Ke, Wan-Chi; Chiu, Hung-Wen

    2015-08-01

    Adjuvant chemotherapy (ACT) is used after surgery to prevent recurrence or metastases. However, ACT for non-small cell lung cancer (NSCLC) is still controversial. This study aimed to develop prediction models to distinguish who is suitable for ACT (ACT-benefit) and who should avoid ACT (ACT-futile) in NSCLC. We identified the ACT correlated gene signatures and performed several types of ANN algorithms to construct the optimal ANN architecture for ACT benefit classification. Reliability was assessed by cross-data set validation. We obtained 2 probes (2 genes) with T-stage clinical data combination can get good prediction result. These genes included 208893_s_at (DUSP6) and 204891_s_at (LCK). The 10-fold cross validation classification accuracy was 65.71%. The best result of ANN models is MLP14-8-2 with logistic activation function. Using gene signature profiles to predict ACT benefit in NSCLC is feasible. The key to this analysis was identifying the pertinent genes and classification. This study maybe helps reduce the ineffective medical practices to avoid the waste of medical resources. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. The 2016 revision of the World Health Organization classification of lymphoid neoplasms | Center for Cancer Research

    Science.gov (United States)

    A revision of the nearly 8-year-old World Health Organization classification of the lymphoid neoplasms and the accompanying monograph is being published. It reflects a consensus among hematopathologists, geneticists, and clinicians regarding both updates to current entities as well as the addition of a limited number of new provisional entities.

  17. Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data

    DEFF Research Database (Denmark)

    List, Markus; Hauschild, Anne-Christin; Tan, Qihua

    2014-01-01

    expression data for hundreds of patients, the challenge is to extract a minimal optimal set of genes with good prognostic properties from a large bulk of genes making a moderate contribution to classification. Several studies have successfully applied machine learning algorithms to solve this so-called gene...

  18. Femur fracture classification in women with a history of breast cancer

    Directory of Open Access Journals (Sweden)

    Stephanie Chau

    2014-05-01

    Conclusion: Most femur fractures in women with prior breast cancer occurred in the hip. Among younger women and those experiencing diaphyseal fractures, a larger proportion were pathologic and some were found to be atypical. Further studies should examine risk factors for femur fracture in women with breast cancer with specific attention to fracture subtype and pharmacologic exposures.

  19. Comparison of the prevalence of malnutrition diagnosis in head and neck, gastrointestinal and lung cancer patients by three classification methods

    Science.gov (United States)

    Platek, Mary E.; Popp KPf, Johann V.; Possinger, Candi S.; DeNysschen, Carol A.; Horvath, Peter; Brown, Jean K.

    2011-01-01

    Background Malnutrition is prevalent among patients within certain cancer types. There is lack of universal standard of care for nutrition screening, lack of agreement on an operational definition and on validity of malnutrition indicators. Objective In a secondary data analysis, we investigated prevalence of malnutrition diagnosis by three classification methods using data from medical records of a National Cancer Institute (NCI)-designated comprehensive cancer center. Interventions/Methods Records of 227 patients hospitalized during 1998 with head and neck, gastrointestinal or lung cancer were reviewed for malnutrition based on three methods: 1) physician diagnosed malnutrition related ICD-9 codes; 2) in-hospital nutritional assessment summary conducted by Registered Dietitians; and 3) body mass index (BMI). For patients with multiple admissions, only data from the first hospitalization was included. Results Prevalence of malnutrition diagnosis ranged from 8.8% based on BMI to approximately 26% of all cases based on dietitian assessment. Kappa coefficients between any methods indicated a weak (kappa=0.23, BMI and Dietitians and kappa=0.28, Dietitians and Physicians) to fair strength of agreement (kappa=0.38, BMI and Physicians). Conclusions Available methods to identify patients with malnutrition in an NCI designated comprehensive cancer center resulted in varied prevalence of malnutrition diagnosis. Universal standard of care for nutrition screening that utilizes validated tools is needed. Implications for Practice The Joint Commission on the Accreditation of Healthcare Organizations requires nutritional screening of patients within 24 hours of admission. For this purpose, implementation of a validated tool that can be used by various healthcare practitioners, including nurses, needs to be considered. PMID:21242767

  20. The mammographic correlations of a new immunohistochemical classification of invasive breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Taneja, S. [Nottingham Breast Institute, City Hospital, Hucknall Road, Nottingham NG5 1PB (United Kingdom)], E-mail: sheeba_taneja@yahoo.co.uk; Evans, A.J. [Nottingham Breast Institute, City Hospital, Hucknall Road, Nottingham NG5 1PB (United Kingdom); Rakha, E.A.; Green, A.R. [Division of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham (United Kingdom); Ball, G. [Nottingham Trent University, School of Biomedical and Natural Sciences, Nottingham (United Kingdom); Ellis, I.O. [Division of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham (United Kingdom)

    2008-11-15

    Aim: Recent protein expression profiling of breast cancer has identified specific subtypes with clinical, biological, and therapeutic implications. The aim of this study was to identify the mammographic correlates of these novel molecular classes of invasive breast cancer. Materials and methods: The mammographic findings of 415 patients with operable breast cancer were correlated with the previously described protein expression classes identified by our group using immunohistochemical (IHC) assessment of a large series of breast cancer cases prepared as tissue microarrays (TMAs). Twenty-five proteins of known relevance in breast cancer were assessed, including hormone receptors, HER-2 status, basal and luminal markers, p53 expression, and E-cadherin. Results: The mammographic background pattern and proportion of lesions that were mammographically occult were similar in all groups. Groups characterized by luminal and hormone receptor positivity had significantly more spiculate lesions at mammography. Groups characterized by HER-2 overexpression, basal characteristics, and E-cadherin positivity had a significantly higher proportion of ill-defined masses. These findings were independent of histological grade. Conclusion: The mammographic features of breast cancer show significant correlation with molecular classes of invasive breast cancer identified by protein expression IHC analysis. The biological reasons for the findings and implications of these regarding imaging protocols require further study and may provide mechanisms for improvement of detection of these lesions.

  1. Classification of a palliative care population in a comprehensive cancer centre

    DEFF Research Database (Denmark)

    Benthien, Kirstine Skov; Nordly, Mie; Videbæk, Katja

    2016-01-01

    PURPOSE: The purposes of the present study were to classify the palliative care population (PCP) in a comprehensive cancer centre by using information on antineoplastic treatment options and to analyse associations between socio-demographic factors, cancer diagnoses, treatment characteristics...... and receiving specialist palliative care (SPC). METHODS: This is a cross-sectional screening study of patients with cancer in the Department of Oncology, Rigshospitalet, Copenhagen University Hospital for 6 months. Patients were assessed to be included in the DOMUS study: a randomised controlled trial...... of accelerated transition to SPC at home (NCT01885637). The PCP was classified as patients with incurable cancer and limited or no antineoplastic treatment options. Patients with performance status 2-4 were further classified as the essential palliative care population (EPCP). RESULTS: During the study period...

  2. Classification of a palliative care population in a comprehensive cancer centre

    DEFF Research Database (Denmark)

    Benthien, Kirstine Skov; Nordly, Mie; Videbæk, Katja

    2016-01-01

    of accelerated transition to SPC at home (NCT01885637). The PCP was classified as patients with incurable cancer and limited or no antineoplastic treatment options. Patients with performance status 2-4 were further classified as the essential palliative care population (EPCP). RESULTS: During the study period......PURPOSE: The purposes of the present study were to classify the palliative care population (PCP) in a comprehensive cancer centre by using information on antineoplastic treatment options and to analyse associations between socio-demographic factors, cancer diagnoses, treatment characteristics...... and receiving specialist palliative care (SPC). METHODS: This is a cross-sectional screening study of patients with cancer in the Department of Oncology, Rigshospitalet, Copenhagen University Hospital for 6 months. Patients were assessed to be included in the DOMUS study: a randomised controlled trial...

  3. Decision Tree of Occupational Lung Cancer Using Classification and Regression Analysis

    Directory of Open Access Journals (Sweden)

    Tae-Woo Kim

    2010-12-01

    Conclusion: We found that exposure to lung carcinogens, latency and smoking history were predictive factors of approval for occupational lung cancer. Further studies for work-relatedness of occupational disease are needed.

  4. The applicability of the international classification of functioning, disability, and health to study lifestyle and quality of life of colorectal cancer survivors

    NARCIS (Netherlands)

    Roekel, E.H. van; Bours, M.J.; Brouwer, C.P. de; Napel, H.M.T.D. ten; Sanduleanu, S.; Beets, G.L.; Kant, I.J.; Weijenberg, M.P.

    2014-01-01

    BACKGROUND: Well-designed studies on lifestyle and health-related quality of life (HRQoL) in colorectal cancer survivors based on a biopsychosocial instead of a traditional biomedical approach are warranted. We report on the applicability of the International Classification of Functioning,

  5. 6 Common Cancers - Colorectal Cancer

    Science.gov (United States)

    ... Home Current Issue Past Issues 6 Common Cancers - Colorectal Cancer Past Issues / Spring 2007 Table of Contents For ... of colon cancer. Photo: AP Photo/Ron Edmonds Colorectal Cancer Cancer of the colon (large intestine) or rectum ( ...

  6. 6 Common Cancers - Breast Cancer

    Science.gov (United States)

    ... Home Current Issue Past Issues 6 Common Cancers - Breast Cancer Past Issues / Spring 2007 Table of Contents For ... slow her down. Photo: AP Photo/Brett Flashnick Breast Cancer Breast cancer is a malignant (cancerous) growth that ...

  7. An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

    Science.gov (United States)

    Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

    2014-01-01

    The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

  8. Clinical Usefulness of the VS Classification System Using Magnifying Endoscopy with Blue Laser Imaging for Early Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Yoshikazu Yoshifuku

    2017-01-01

    Full Text Available Background. Blue laser imaging (BLI enables the acquisition of more information from tumors’ surfaces compared with white light imaging. Few reports confirm the validity of magnifying endoscopy (ME with BLI (ME-BLI for early gastric cancer (EGC. We aimed to assess the detailed endoscopic findings from EGCs using ME-BLI. Methods. We enrolled 386 consecutive patients with 417 EGCs that were diagnosed using ME-BLI and resected by endoscopic submucosal dissection. Using the VS classification system, three highly experienced endoscopists (HEEs and three less experienced endoscopists (LEEs evaluated the demarcation line (DL, microsurface pattern (MSP, and microvascular pattern (MVP within the endoscopic images of EGCs obtained using ME-BLI, assigning high-confidence (HC or low-confidence (LC levels. We investigated the clinicopathological features associated with each confidence level. Results. The HEEs’ evaluations determined the presence of DL in 99%, irregular MSP in 96%, and irregular MVP in 96%, and the LEEs’ evaluations determined the presence of DL in 98%, irregular MSP in 95%, and irregular MVP in 95% of the EGCs. When DL was present, HC levels in the Helicobacter pylori- (H. pylori- eradicated group and noneradicated group were evident in 65% and 89%, a difference that was significant (p<0.001. Conclusions. In the diagnosis of EGC with ME-BLI, the VS classification system with ME-NBI can be applied, but identifying the DL after H. pylori was difficult.

  9. Feature selection and classification of MAQC-II breast cancer and multiple myeloma microarray gene expression data.

    Directory of Open Access Journals (Sweden)

    Qingzhong Liu

    Full Text Available Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA, which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE, Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS, Gradient based Leave-one-out Gene Selection (GLGS. To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and

  10. Identification of immune cell infiltration in hematoxylin-eosin stained breast cancer samples: texture-based classification of tissue morphologies

    Science.gov (United States)

    Turkki, Riku; Linder, Nina; Kovanen, Panu E.; Pellinen, Teijo; Lundin, Johan

    2016-03-01

    The characteristics of immune cells in the tumor microenvironment of breast cancer capture clinically important information. Despite the heterogeneity of tumor-infiltrating immune cells, it has been shown that the degree of infiltration assessed by visual evaluation of hematoxylin-eosin (H and E) stained samples has prognostic and possibly predictive value. However, quantification of the infiltration in H and E-stained tissue samples is currently dependent on visual scoring by an expert. Computer vision enables automated characterization of the components of the tumor microenvironment, and texture-based methods have successfully been used to discriminate between different tissue morphologies and cell phenotypes. In this study, we evaluate whether local binary pattern texture features with superpixel segmentation and classification with support vector machine can be utilized to identify immune cell infiltration in H and E-stained breast cancer samples. Guided with the pan-leukocyte CD45 marker, we annotated training and test sets from 20 primary breast cancer samples. In the training set of arbitrary sized image regions (n=1,116) a 3-fold cross-validation resulted in 98% accuracy and an area under the receiver-operating characteristic curve (AUC) of 0.98 to discriminate between immune cell -rich and - poor areas. In the test set (n=204), we achieved an accuracy of 96% and AUC of 0.99 to label cropped tissue regions correctly into immune cell -rich and -poor categories. The obtained results demonstrate strong discrimination between immune cell -rich and -poor tissue morphologies. The proposed method can provide a quantitative measurement of the degree of immune cell infiltration and applied to digitally scanned H and E-stained breast cancer samples for diagnostic purposes.

  11. The Mouse Model of Pancreatic Cancer Atlas (MMPCA) for classification of pancreatic cancer lesions: A large histological investigation of the Ptf1aCre/+;LSL-KrasG12D/+ transgenic mouse model of pancreatic cancer.

    Science.gov (United States)

    Veite-Schmahl, Michelle J; Rivers, Adam C; Regan, Daniel P; Kennedy, Michael A

    2017-01-01

    Pancreatic ductal adenocarcinoma (PDAC) is one of the leading forms of cancer related deaths in the United States. With limited treatment options and unreliable diagnostic methods, long-term survival rates following a diagnosis of pancreatic cancer remain poor. Pancreatic intraepithelial neoplasia (PanIN) are precancerous lesions that precede progression towards PDAC. PanIN occur in increasing complexity as the disease progresses and the description of PanIN plays a critical role in describing, staging and diagnosing PDAC. Inconsistencies in PanIN classifications exist even amongst leading pathologists. This has led to debate and confusion among researchers and pathologists involved in pancreatic cancer research, diagnosis and treatment. We have sought to initiate a discussion with leading pathologists with a goal of increasing consensus in the interpretation of PanIN and associated structures within the precancerous pancreas. Toward achieving this goal, we are in the process of conducting an extensive study of over 1000 male and female pancreata in varying stages of PanIN progression isolated from the Ptf1aCre/+;LSL-KrasG12D/+ transgenic mouse model of pancreatic cancer. Using this extensive database, we have established the Mouse Model of Pancreatic Cancer Atlas (MMPCA) to serve as a platform for meaningful and interactive discussion among researchers and pathologists who study pancreatic disease. We hope that the MMPCA will be an effective tool for promoting a more consistent and accurate consensus of PanIN classifications in the future.

  12. A personalized committee classification approach to improving prediction of breast cancer metastasis.

    Science.gov (United States)

    Jahid, Md Jamiul; Huang, Tim H; Ruan, Jianhua

    2014-07-01

    Metastasis prediction is a well-known problem in breast cancer research. As breast cancer is a complex and heterogeneous disease with many molecular subtypes, predictive models trained for one cohort often perform poorly on other cohorts, and a combined model may be suboptimal for individual patients. Furthermore, attempting to develop subtype-specific models is hindered by the ambiguity and stereotypical definitions of subtypes. Here, we propose a personalized approach by relaxing the definition of breast cancer subtypes. We assume that each patient belongs to a distinct subtype, defined implicitly by a set of patients with similar molecular characteristics, and construct a different predictive model for each patient, using as training data, only the patients defining the subtype. To increase robustness, we also develop a committee-based prediction method by pooling together multiple personalized models. Using both intra- and inter-dataset validations, we show that our approach can significantly improve the prediction accuracy of breast cancer metastasis compared with several popular approaches, especially on those hard-to-learn cases. Furthermore, we find that breast cancer patients belonging to different canonical subtypes tend to have different predictive models and gene signatures, suggesting that metastasis in different canonical subtypes are likely governed by different molecular mechanisms. Source code implemented in MATLAB and Java available at www.cs.utsa.edu/∼jruan/PCC/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  13. Abridged republication of FIGO's staging classification for cancer of the ovary, fallopian tube, and peritoneum.

    Science.gov (United States)

    Prat, Jaime

    2015-10-01

    Ovarian, fallopian tube, and peritoneal cancers have a similar clinical presentation and are treated similarly, and current evidence supports staging all 3 cancers in a single system. The primary site (i.e. ovary, fallopian tube, or peritoneum) should be designated where possible. The histologic type should be recorded. Intraoperative rupture ("surgical spill") is IC1; capsule ruptured before surgery or tumor on ovarian or fallopian tube surface is IC2; and positive peritoneal cytology with or without rupture is IC3. The new staging includes a revision of stage III patients; assignment to stage IIIA1 is based on spread to the retroperitoneal lymph nodes without intraperitoneal dissemination. Extension of tumor from omentum to spleen or liver (stage IIIC) should be differentiated from isolated parenchymal metastases (stage IVB). © 2015 American Cancer Society.

  14. Taxonomies in L1 and L2 Reading Strategies: A Critical Review of Issues Surrounding Strategy-Use Definitions and Classifications in Previous Think-Aloud Research

    Science.gov (United States)

    Alkhaleefah, Tarek A.

    2016-01-01

    Considering the various classifications of L1 and L2 reading strategies in previous think-aloud studies, the present review aims to provide a comprehensive look into those various taxonomies reported in major L1 and L2 reading studies. The rationale for this review is not only to offer a comprehensive overview of the different classifications in…

  15. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  16. Raman spectroscopy complements optical coherent tomography in tissue classification and cancer detection

    Science.gov (United States)

    Qi, Ji; Sudheendran, Narendran; Liu, Chih-Hao; Santos, Greggy M.; Young, Eric D.; Lazar, Alexander J.; Lev, Dina C.; Pollock, Raphael E.; Larin, Kirill V.; Shih, Wei-Chuan

    2015-03-01

    Optical coherence tomography (OCT) provides significant advantages of high-resolution (approaching the histopathology level) real-time imaging of tissues without use of contrast agents. Based on these advantages, the microstructural features of tumors can be visualized and detected intra-operatively. However, it is still not clinically accepted for tumor margin delineation due to poor specificity and accuracy. In contrast, Raman spectroscopy (RS) can obtain tissue information at the molecular level, but does not provide real-time imaging capability. Therefore, combining OCT and RS could provide synergy. To this end, we present a tissue analysis and classification method using both the slope of OCT intensity signal versus depth and the principle components from the RS spectrum as the indicators for tissue characterization. Our pilot experiments were performed on mouse kidneys, livers, and small intestines. The prediction accuracy with five-fold cross validation of the method has been evaluated by support vector machine method. The results demonstrate that RS can effectively improve tissue classification compared to OCT alone. Next, we demonstrate that the boundary between myxoid liposarcoma and normal fat which is easily identifiable both Raman and OCT. In cases where structural images are indistinguishable, for example, in normal fat and well differentiated liposarcoma (WDLS) or gastrointestinal sarcoma tumor (GIST) and Myxoma, distinct molecular spectra have been obtained. The results suggest RS can effectively complement OCT to tumor boundary demarcation with high specificity.

  17. A computational study on convolutional feature combination strategies for grade classification in colon cancer using fluorescence microscopy data

    Science.gov (United States)

    Chowdhury, Aritra; Sevinsky, Christopher J.; Santamaria-Pang, Alberto; Yener, Bülent

    2017-03-01

    The cancer diagnostic workflow is typically performed by highly specialized and trained pathologists, for which analysis is expensive both in terms of time and money. This work focuses on grade classification in colon cancer. The analysis is performed over 3 protein markers; namely E-cadherin, beta actin and colagenIV. In addition, we also use a virtual Hematoxylin and Eosin (HE) stain. This study involves a comparison of various ways in which we can manipulate the information over the 4 different images of the tissue samples and come up with a coherent and unified response based on the data at our disposal. Pre- trained convolutional neural networks (CNNs) is the method of choice for feature extraction. The AlexNet architecture trained on the ImageNet database is used for this purpose. We extract a 4096 dimensional feature vector corresponding to the 6th layer in the network. Linear SVM is used to classify the data. The information from the 4 different images pertaining to a particular tissue sample; are combined using the following techniques: soft voting, hard voting, multiplication, addition, linear combination, concatenation and multi-channel feature extraction. We observe that we obtain better results in general than when we use a linear combination of the feature representations. We use 5-fold cross validation to perform the experiments. The best results are obtained when the various features are linearly combined together resulting in a mean accuracy of 91.27%.

  18. Radiomic signature as a diagnostic factor for histologic subtype classification of non-small cell lung cancer.

    Science.gov (United States)

    Zhu, Xinzhong; Dong, Di; Chen, Zhendong; Fang, Mengjie; Zhang, Liwen; Song, Jiangdian; Yu, Dongdong; Zang, Yali; Liu, Zhenyu; Shi, Jingyun; Tian, Jie

    2018-02-15

    To distinguish squamous cell carcinoma (SCC) from lung adenocarcinoma (ADC) based on a radiomic signature METHODS: This study involved 129 patients with non-small cell lung cancer (NSCLC) (81 in the training cohort and 48 in the independent validation cohort). Approximately 485 features were extracted from a manually outlined tumor region. The LASSO logistic regression model selected the key features of a radiomic signature. Receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the performance of the radiomic signature in the training and validation cohorts. Five features were selected to construct the radiomic signature for histologic subtype classification. The performance of the radiomic signature to distinguish between lung ADC and SCC in both training and validation cohorts was good, with an AUC of 0.905 (95% confidence interval [CI]: 0.838 to 0.971), sensitivity of 0.830, and specificity of 0.929. In the validation cohort, the radiomic signature showed an AUC of 0.893 (95% CI: 0.789 to 0.996), sensitivity of 0.828, and specificity of 0.900. A unique radiomic signature was constructed for use as a diagnostic factor for discriminating lung ADC from SCC. Patients with NSCLC will benefit from the proposed radiomic signature. • Machine learning can be used for auxiliary distinguish in lung cancer. • Radiomic signature can discriminate lung ADC from SCC. • Radiomics can help to achieve precision medical treatment.

  19. Classification and Diagnostic Output Prediction of Cancer Using Gene Expression Profiling and Supervised Machine Learning Algorithms

    DEFF Research Database (Denmark)

    Yoo, C.; Gernaey, Krist

    2008-01-01

    importance in the projection (VIP) information of the DPLS method. The power of the gene selection method and the proposed supervised hierarchical clustering method is illustrated on a three microarray data sets of leukemia, breast, and colon cancer. Supervised machine learning algorithms thus enable...

  20. Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team

    DEFF Research Database (Denmark)

    Bjørn, Signe Frahm; Schnack, Tine Henrichsen; Lajer, Henrik

    2017-01-01

    multidisciplinary team (MDT) decisions. Materials and Methods Four hundred eighteen women diagnosed with ovarian cancers (n = 351) or borderline tumors (n = 66) were selected for primary debulking surgery from January 2008 to July 2013. At an MDT meeting, women were allocated into 3 groups named "pre-COVA" 1 to 3...

  1. Differential gene expression profiles according to the Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society histopathological classification in lung adenocarcinoma subtypes.

    Science.gov (United States)

    Molina-Romero, Camilo; Rangel-Escareño, Claudia; Ortega-Gómez, Alette; Alanis-Funes, Gerardo J; Avilés-Salas, Alejandro; Avila-Moreno, Federico; Mercado, Gabriela E; Cardona, Andrés F; Hidalgo-Miranda, Alfredo; Arrieta, Oscar

    2017-08-01

    The current lung cancer classification from the Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society has considerably changed the pathologic diagnosis of lung invasive adenocarcinoma, identifying disease subtypes with substantial implications for medical practice, such as clinical, radiological, molecular, and prognostic differences. We analyzed the differences in the genetic expression of adenocarcinoma subtypes according to the new classification. Microarray gene expression analysis was performed on a cohort of 29 adenocarcinoma patients treated at the Instituto Nacional de Cancerología of Mexico from 2008 to 2011. All patients had an available biopsy sample and were classified into 4 different subtypes of adenocarcinoma (2015 World Health Organization classification). Lepidic-predominant adenocarcinoma was the only pattern that exhibited a marked gene expression difference compared with other predominant histologic patterns, revealing genes with significant expression (P adenocarcinoma that could be used as a gene signature. The lepidic-predominant histologic pattern has a differential gene expression profile compared with all predominant histologic patterns. Additionally, we identified a gene expression signature of 13 genes that have a unique behavior in the lepidic histologic pattern; these 13 genes are candidates for follow-up studies for their potential use as biomarkers or therapeutic targets. Results from this study highlight the importance of the new Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification and exemplify the potential clinical implications of correlating histopathology with exclusive molecular beacons. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. HPV infection, anal intra-epithelial neoplasia (AIN and anal cancer: current issues

    Directory of Open Access Journals (Sweden)

    Stanley Margaret A

    2012-09-01

    Full Text Available Abstract Background Human papillomavirus (HPV is well known as the major etiological agent for ano-genital cancer. In contrast to cervical cancer, anal cancer is uncommon, but is increasing steadily in the community over the last few decades. However, it has undergone an exponential rise in the men who have sex with men (MSM and HIV + groups. HIV + MSM in particular, have anal cancer incidences about three times that of the highest worldwide reported cervical cancer incidences. Discussion There has therefore traditionally been a lack of data from studies focused on heterosexual men and non-HIV + women. There is also less evidence reporting on the putative precursor lesion to anal cancer (AIN – anal intraepithelial neoplasia, when compared to cervical cancer and CIN (cervical intraepithelial neoplasia. This review summarises the available biological and epidemiological evidence for HPV in the anal site and the pathogenesis of AIN and anal cancer amongst traditionally non-high risk groups. Summary There is strong evidence to conclude that high-grade AIN is a precursor to anal cancer, and some data on the progression of AIN to invasive cancer.

  3. Next-Generation Sequencing in Oncology: Genetic Diagnosis, Risk Prediction and Cancer Classification.

    Science.gov (United States)

    Kamps, Rick; Brandão, Rita D; Bosch, Bianca J van den; Paulussen, Aimee D C; Xanthoulea, Sofia; Blok, Marinus J; Romano, Andrea

    2017-01-31

    Next-generation sequencing (NGS) technology has expanded in the last decades with significant improvements in the reliability, sequencing chemistry, pipeline analyses, data interpretation and costs. Such advances make the use of NGS feasible in clinical practice today. This review describes the recent technological developments in NGS applied to the field of oncology. A number of clinical applications are reviewed, i.e., mutation detection in inherited cancer syndromes based on DNA-sequencing, detection of spliceogenic variants based on RNA-sequencing, DNA-sequencing to identify risk modifiers and application for pre-implantation genetic diagnosis, cancer somatic mutation analysis, pharmacogenetics and liquid biopsy. Conclusive remarks, clinical limitations, implications and ethical considerations that relate to the different applications are provided.

  4. Next-Generation Sequencing in Oncology: Genetic Diagnosis, Risk Prediction and Cancer Classification

    Directory of Open Access Journals (Sweden)

    Rick Kamps

    2017-01-01

    Full Text Available Next-generation sequencing (NGS technology has expanded in the last decades with significant improvements in the reliability, sequencing chemistry, pipeline analyses, data interpretation and costs. Such advances make the use of NGS feasible in clinical practice today. This review describes the recent technological developments in NGS applied to the field of oncology. A number of clinical applications are reviewed, i.e., mutation detection in inherited cancer syndromes based on DNA-sequencing, detection of spliceogenic variants based on RNA-sequencing, DNA-sequencing to identify risk modifiers and application for pre-implantation genetic diagnosis, cancer somatic mutation analysis, pharmacogenetics and liquid biopsy. Conclusive remarks, clinical limitations, implications and ethical considerations that relate to the different applications are provided.

  5. Next-Generation Sequencing in Oncology: Genetic Diagnosis, Risk Prediction and Cancer Classification

    Science.gov (United States)

    Kamps, Rick; Brandão, Rita D.; van den Bosch, Bianca J.; Paulussen, Aimee D. C.; Xanthoulea, Sofia; Blok, Marinus J.; Romano, Andrea

    2017-01-01

    Next-generation sequencing (NGS) technology has expanded in the last decades with significant improvements in the reliability, sequencing chemistry, pipeline analyses, data interpretation and costs. Such advances make the use of NGS feasible in clinical practice today. This review describes the recent technological developments in NGS applied to the field of oncology. A number of clinical applications are reviewed, i.e., mutation detection in inherited cancer syndromes based on DNA-sequencing, detection of spliceogenic variants based on RNA-sequencing, DNA-sequencing to identify risk modifiers and application for pre-implantation genetic diagnosis, cancer somatic mutation analysis, pharmacogenetics and liquid biopsy. Conclusive remarks, clinical limitations, implications and ethical considerations that relate to the different applications are provided. PMID:28146134

  6. Immune Contexture, Immunoscore, and Malignant Cell Molecular Subgroups for Prognostic and Theranostic Classifications of Cancers.

    Science.gov (United States)

    Becht, Etienne; Giraldo, Nicolas A; Germain, Claire; de Reyniès, Aurélien; Laurent-Puig, Pierre; Zucman-Rossi, Jessica; Dieu-Nosjean, Marie-Caroline; Sautès-Fridman, Catherine; Fridman, Wolf H

    2016-01-01

    The outcome of tumors results from genetic and epigenetic modifications of the transformed cells and also from the interactions of the malignant cells with their tumor microenvironment (TME), which includes immune and inflammatory cells. For a given cancer type, the composition of the immunological TME is not homogeneous. Heterogeneity is found between different cancer types and also between tumors from patients with the same type of cancer. Some tumors exhibit a poor infiltration by immune cells, and others are highly infiltrated by lymphocytes. Among the latter, the architecture of the TME, with the localization of immune cells in the invasive front and the center of the tumor, the presence of tumor-adjacent organized lymphoid aggregates, and the type of inflammatory context, determines the prognostic impact of the infiltrating cells. The description and the understanding of the immune and inflammatory landscape in human tumors are of paramount importance at different levels of patient's care. It completes the mutational, transcriptional, and epigenetic patterns of the malignant cells and open paths to understand how tumor cells shape their immune microenvironment and are shaped by the immune reaction. It provides prognostic and theranostic markers, as well as novel targets for immunotherapies. © 2016 Elsevier Inc. All rights reserved.

  7. Carcinoma de mama: novos conceitos na classificação Breast cancer: new concepts in classification

    Directory of Open Access Journals (Sweden)

    Daniella Serafin Couto Vieira

    2008-01-01

    and the basis for and improved breast cancer molecular taxonomy. Another important implication is that genetic profiling may lead to the identification of new target for therapy and better predictive markers are needed to guide difficult treatment decisions. Additionally, the current pathology classification system is suboptimal, since patients with identical tumor types and stage of disease present different responses to therapy and different overall outcomes. Basal breast tumor represents one of the most intriguing subtypes and is frequently associated with poor prognosis and absence of putative therapeutic targets. Then, the purpose of this review was to resume the most recent knowledge about the breast carcinoma classification and characterization.

  8. An associated classification of triple negative breast cancer: the risk of relapse and the response to chemotherapy.

    Science.gov (United States)

    Zhang, Jing; Wang, Yahong; Yin, Quangui; Zhang, Wei; Zhang, Tongxian; Niu, Yun

    2013-01-01

    Triple negative breast cancer (TNBC) is heterogeneous and considered as an aggressive tumor. This study was to evaluate the associated classification and its correlations with prognosis and the response to chemotherapy in Chinese women. Four hundred and twenty-eight cases of invasive TNBC were involved in this study. The expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), epidermal growth factor receptor (EGFR), and cytokeratin 5/6 (CK5/6), Ki67 and p53 were analyzed by immunohistochemistry and compared with patient outcome, and its implications and chemotherapy response were evaluated in four subgroups: typical medullary carcinoma (TMC), atypical medullary carcinoma (AMC), non-specific invasive ductal carcinoma (IDC) and other types. The factors of tumor grade, tumor stage, lymph node status, EGFR/CK5/6 status and p53 labeling index were different among the groups. TMC tumors had the lowest rate of relapse (5.8%), while AMC, IDC and other types were associated with an increased risk of relapse (19.1%, 26.7% and 38.2% respectively). Many factors were risk predictors of relapse for TNBC and IDC, while only positive lymph node was for AMC. For MC tumors, adjunctive chemotherapy decreased the risk of relapse in lymph node positive subgroup (36.8% and 66.7%), while not significant in lymph node negative one (8.1% and 10.0%). The classification based on histologic and IHC findings may be a significant improvement in predicting outcome in TNBC. The different chemotherapy response in subgroups may contribute to guiding the treatment of TNBC.

  9. Red meat, processed meat and cancer in South Africa : issues in medicine

    National Research Council Canada - National Science Library

    Stefan, D.C

    2016-01-01

    Epidemiological studies around the world were analysed recently by the International Agency for Research on Cancer, demonstrating a positive correlation between consumption of red meat and processed...

  10. Building a model for disease classification integration in oncology, an approach based on the national cancer institute thesaurus.

    Science.gov (United States)

    Jouhet, Vianney; Mougin, Fleur; Bréchat, Bérénice; Thiessard, Frantz

    2017-02-07

    Identifying incident cancer cases within a population remains essential for scientific research in oncology. Data produced within electronic health records can be useful for this purpose. Due to the multiplicity of providers, heterogeneous terminologies such as ICD-10 and ICD-O-3 are used for oncology diagnosis recording purpose. To enable disease identification based on these diagnoses, there is a need for integrating disease classifications in oncology. Our aim was to build a model integrating concepts involved in two disease classifications, namely ICD-10 (diagnosis) and ICD-O-3 (topography and morphology), despite their structural heterogeneity. Based on the NCIt, a "derivative" model for linking diagnosis and topography-morphology combinations was defined and built. ICD-O-3 and ICD-10 codes were then used to instantiate classes of the "derivative" model. Links between terminologies obtained through the model were then compared to mappings provided by the Surveillance, Epidemiology, and End Results (SEER) program. The model integrated 42% of neoplasm ICD-10 codes (excluding metastasis), 98% of ICD-O-3 morphology codes (excluding metastasis) and 68% of ICD-O-3 topography codes. For every codes instantiating at least a class in the "derivative" model, comparison with SEER mappings reveals that all mappings were actually available in the model as a link between the corresponding codes. We have proposed a method to automatically build a model for integrating ICD-10 and ICD-O-3 based on the NCIt. The resulting "derivative" model is a machine understandable resource that enables an integrated view of these heterogeneous terminologies. The NCIt structure and the available relationships can help to bridge disease classifications taking into account their structural and granular heterogeneities. However, (i) inconsistencies exist within the NCIt leading to misclassifications in the "derivative" model, (ii) the "derivative" model only integrates a part of ICD-10 and ICD

  11. Cancer patient perceptions on the ethical and legal issues related to biobanking.

    Science.gov (United States)

    Master, Zubin; Claudio, Jaime O; Rachul, Christen; Wang, Jean C Y; Minden, Mark D; Caulfield, Timothy

    2013-03-08

    Understanding the perception of patients on research ethics issues related to biobanking is important to enrich ethical discourse and help inform policy. We examined the views of leukemia patients undergoing treatment in clinics located in the Princess Margaret Hospital in Toronto, Ontario, Canada. An initial written survey was provided to 100 patients (64.1% response rate) followed by a follow-up survey (62.5% response rate) covering the topics of informed consent, withdrawal, anonymity, incidental findings and the return of results, ownership, and trust. The majority (59.6%) preferred one-time consent, 30.3% desired a tiered consent approach that provides multiple options, and 10.1% preferred re-consent for future research. When asked different questions on re-consent, most (58%) reported that re-consent was a waste of time and money, but 51.7% indicated they would feel respected and involved if asked to re-consent. The majority of patients (62.2%) stated they had a right to withdraw their consent, but many changed their mind in the follow-up survey explaining that they should not have the right to withdraw consent. Nearly all of the patients (98%) desired being informed of incidental health findings and explained that the information was useful. Of these, 67.3% of patients preferred that researchers inform them and their doctors of the results. The majority of patients (62.2%) stated that the research institution owns the samples whereas 19.4% stated that the participants owned their samples. Patients had a great deal of trust in doctors, hospitals and government-funded university researchers, moderate levels of trust for provincial governments and industry-funded university researchers, and low levels of trust towards industry and insurance companies. Many cancer patients surveyed preferred a one-time consent although others desired some form of control. The majority of participants wanted a continuing right to withdraw consent and nearly all wanted to be

  12. Beyond treatment : Psychosocial and behavioural issues in cancer survivorship research and practice

    NARCIS (Netherlands)

    Aaronson, N.K.; Mattioli, V.; Minton, O.; Weis, J.; Johansen, C.; Dalton, S.O.; Verdonck-de Leeuw, I.M.; Stein, K.D.; Alfano, C.M.; Mehnert, A.; de Boer, A.; van de Poll-Franse, L.

    2014-01-01

    The population of cancer survivors has grown steadily over the past several decades. Surviving cancer, however, is not synonymous with a life free of problems related to the disease and its treatment. In this paper we provide a brief overview of selected physical and psychosocial health problems

  13. Beyond treatment - Psychosocial and behavioral issues in cancer survivorship research and practice

    NARCIS (Netherlands)

    Aaronson, N.K.; Mattioli, V.; Minton, O.; Weis, J.; Johansen, C.; Dalton, S.O.; Verdonck-de Leeuw, I.M.; Stein, K.D.; Alfano, C.M.; Mehnert, A.; de Boer, A.; van de Poll-Franse, L.V.

    2014-01-01

    The population of cancer survivors has grown steadily over the past several decades. Surviving cancer, however, is not synonymous with a life free of problems related to the disease and its treatment. In this paper we provide a brief overview of selected physical and psychosocial health problems

  14. Beyond treatment – Psychosocial and behavioural issues in cancer survivorship research and practice

    NARCIS (Netherlands)

    Aaronson, N.K.; Mattioli, V.; Minton, O.; Weis, J.; Johansen, C.; Dalton, S.O.; Verdonck-de Leeuw, I.M.; Stein, K.D.; Alfano, C.M.; Mehnert, A.; de Boer, A.; van de Poll-Franse, L.

    2014-01-01

    The population of cancer survivors has grown steadily over the past several decades. Surviving cancer, however, is not synonymous with a life free of problems related to the disease and its treatment. In this paper we provide a brief overview of selected physical and psychosocial health problems

  15. Beyond treatment - Psychosocial and behavioural issues in cancer survivorship research and practice

    NARCIS (Netherlands)

    Aaronson, Neil K.; Mattioli, Vittorio; Minton, Ollie; Weis, Joachim; Johansen, Christoffer; Dalton, Susanne O.; Verdonck-de Leeuw, Irma M.; Stein, Kevin D.; Alfano, Catherine M.; Mehnert, Anja; de Boer, Angela; van de Poll-Franse, Lonneke V.

    2014-01-01

    The population of cancer survivors has grown steadily over the past several decades. Surviving cancer, however, is not synonymous with a life free of problems related to the disease and its treatment. In this paper we provide a brief overview of selected physical and psychosocial health problems

  16. CPTC and KIST Join Efforts to Solve Complex Proteomic Issues | Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    The National Cancer Institute's (NCI) Clinical Proteomic Technologies for Cancer (CPTC) initiative at the National Institutes of Health has entered into a memorandum of understanding (MOU) with the Korea Institute of Science and Technology (KIST). This MOU promotes proteomic technology optimization and standards implementation in large-scale international programs.

  17. Clinical study of quantitative diagnosis of early cervical cancer based on the classification of acetowhitening kinetics

    Science.gov (United States)

    Wu, Tao; Cheung, Tak-Hong; Yim, So-Fan; Qu, Jianan Y.

    2010-03-01

    A quantitative colposcopic imaging system for the diagnosis of early cervical cancer is evaluated in a clinical study. This imaging technology based on 3-D active stereo vision and motion tracking extracts diagnostic information from the kinetics of acetowhitening process measured from the cervix of human subjects in vivo. Acetowhitening kinetics measured from 137 cervical sites of 57 subjects are analyzed and classified using multivariate statistical algorithms. Cross-validation methods are used to evaluate the performance of the diagnostic algorithms. The results show that an algorithm for screening precancer produced 95% sensitivity (SE) and 96% specificity (SP) for discriminating normal and human papillomavirus (HPV)-infected tissues from cervical intraepithelial neoplasia (CIN) lesions. For a diagnostic algorithm, 91% SE and 90% SP are achieved for discriminating normal tissue, HPV infected tissue, and low-grade CIN lesions from high-grade CIN lesions. The results demonstrate that the quantitative colposcopic imaging system could provide objective screening and diagnostic information for early detection of cervical cancer.

  18. The Understanding of Terminal Cancer and Its Relationship with Attitudes toward End-of-Life Care Issues.

    Science.gov (United States)

    Lee, June Koo; Yun, Young Ho; An, Ah Reum; Heo, Dae Seog; Park, Byeong-Woo; Cho, Chi-Heum; Kim, Sung; Lee, Dae Ho; Lee, Soon Nam; Lee, Eun Sook; Kang, Jung Hun; Kim, Si-Young; Lee, Jung Lim; Lee, Chang Geol; Lim, Yeun Keun; Kim, Samyong; Choi, Jong Soo; Jeong, Hyun Sik; Chun, Mison

    2014-08-01

    Although terminal cancer is a widely used term, its meaning varies, which may lead to different attitudes toward end-of-life issues. The study was conducted to investigate differences in the understanding of terminal cancer and determine the relationship between this understanding and attitudes toward end-of-life issues. A questionnaire survey was performed between 2008 and 2009. A total of 1242 cancer patients, 1289 family caregivers, 303 oncologists from 17 hospitals, and 1006 participants from the general population responded. A "6-month life expectancy" was the most common understanding of terminal cancer (45.6%), followed by "treatment refractoriness" (21.1%), "metastatic/recurrent disease" (19.4%), "survival of a few days/weeks" (11.4%), and "locally advanced disease" (2.5%). The combined proportion of "treatment refractoriness" and "6-month life expectancy" differed significantly between oncologists and the other groups combined (76.0% v. 65.9%, P = 0.0003). Multivariate analyses showed that patients and caregivers who understood terminal cancer as "survival of a few days/weeks" showed more negative attitudes toward disclosure of terminal status compared with participants who chose "treatment refractoriness" (adjusted odds ratio [aOR] 0.42, 95% confidence interval [CI] 0.22-0.79 for patients; aOR 0.34, 95% CI 0.18-0.63 for caregivers). Caregivers who understood terminal cancer as "locally advanced" or "metastatic/recurrent disease" showed a significantly lower percentage of agreement with withdrawal of futile life-sustaining treatment compared with those who chose "treatment refractoriness" (aOR 0.19, 95% CI 0.07-0.54 for locally advanced; aOR 0.39, 95% CI 0.21-0.72 for metastatic/recurrent). The understanding of terminal cancer varied among the 4 participant groups. It was associated with different preferences regarding end-of-life issues. Standardization of these terms is needed to better understand end-of-life care. © The Author(s) 2013.

  19. Prognostic Performance and Reproducibility of the 1973 and 2004/2016 World Health Organization Grading Classification Systems in Non-muscle-invasive Bladder Cancer: A European Association of Urology Non-muscle Invasive Bladder Cancer Guidelines Panel Systematic Review.

    Science.gov (United States)

    Soukup, Viktor; Čapoun, Otakar; Cohen, Daniel; Hernández, Virginia; Babjuk, Marek; Burger, Max; Compérat, Eva; Gontero, Paolo; Lam, Thomas; MacLennan, Steven; Mostafid, A Hugh; Palou, Joan; van Rhijn, Bas W G; Rouprêt, Morgan; Shariat, Shahrokh F; Sylvester, Richard; Yuan, Yuhong; Zigeuner, Richard

    2017-11-01

    Tumour grade is an important prognostic indicator in non-muscle-invasive bladder cancer (NMIBC). Histopathological classifications are limited by interobserver variability (reproducibility), which may have prognostic implications. European Association of Urology NMIBC guidelines suggest concurrent use of both 1973 and 2004/2016 World Health Organization (WHO) classifications. To compare the prognostic performance and reproducibility of the 1973 and 2004/2016 WHO grading systems for NMIBC. A systematic literature search was undertaken incorporating Medline, Embase, and the Cochrane Library. Studies were critically appraised for risk of bias (QUIPS). For prognosis, the primary outcome was progression to muscle-invasive or metastatic disease. Secondary outcomes were disease recurrence, and overall and cancer-specific survival. For reproducibility, the primary outcome was interobserver variability between pathologists. Secondary outcome was intraobserver variability (repeatability) by the same pathologist. Of 3593 articles identified, 20 were included in the prognostic review; three were eligible for the reproducibility review. Increasing tumour grade in both classifications was associated with higher disease progression and recurrence rates. Progression rates in grade 1 patients were similar to those in low-grade patients; progression rates in grade 3 patients were higher than those in high-grade patients. Survival data were limited. Reproducibility of the 2004/2016 system was marginally better than that of the 1973 system. Two studies on repeatability showed conflicting results. Most studies had a moderate to high risk of bias. Current grading classifications in NMIBC are suboptimal. The 1973 system identifies more aggressive tumours. Intra- and interobserver variability was slightly less in the 2004/2016 classification. We could not confirm that the 2004/2016 classification outperforms the 1973 classification in prediction of recurrence and progression. This article

  20. Communication difficulties and the experience of loneliness in patients with cancer dealing with fertility issues: a qualitative study.

    Science.gov (United States)

    Goossens, Joline; Delbaere, Ilse; Beeckman, Dimitri; Verhaeghe, Sofie; Van Hecke, Ann

    2015-01-01

    To explore communication difficulties and the experience of loneliness among patients with cancer dealing with fertility issues. Qualitative study based on grounded theory principles. One university hospital and two general hospitals in Flanders, Belgium. 21 female and 7 male patients with cancer with potential fertility problems as a result of treatment. Grounded theory approach using the constant comparison method; data collection (semistructured face-to-face interviews) and analysis occurred simultaneously. Loneliness was a central theme in the experience of potential fertility loss among patients with cancer. Feelings of loneliness resulted from communication difficulties between the patient and members of his or her social environment or healthcare professionals because of several underlying processes and influencing factors. Loneliness was a strong and common feeling among patients with cancer. Patients, members of their social environment, and healthcare professionals experienced difficulties in communicating about fertility in the context of cancer, leading to patients' feelings of loneliness. Healthcare professionals must be attentive to signs indicating loneliness regarding fertility concerns, and they should provide adequate information and appropriate guidance to support patients. Professionals need further training to improve knowledge and skills.

  1. 15 CFR 2008.9 - Classification guides.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Classification guides. 2008.9 Section... REPRESENTATIVE Derivative Classification § 2008.9 Classification guides. Classification guides shall be issued by... direct derivative classification, shall identify the information to be protected in specific and uniform...

  2. 32 CFR 2400.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2400.15 Section 2400.15... Derivative Classification § 2400.15 Classification guides. (a) OSTP shall issue and maintain classification guides to facilitate the proper and uniform derivative classification of information. These guides shall...

  3. Biomarker identification and cancer classification based on microarray data using Laplace naive Bayes model with mean shrinkage.

    Science.gov (United States)

    Wu, Meng-Yun; Dai, Dao-Qing; Shi, Yu; Yan, Hong; Zhang, Xiao-Fei

    2012-01-01

    Biomarker identification and cancer classification are two closely related problems. In gene expression data sets, the correlation between genes can be high when they share the same biological pathway. Moreover, the gene expression data sets may contain outliers due to either chemical or electrical reasons. A good gene selection method should take group effects into account and be robust to outliers. In this paper, we propose a Laplace naive Bayes model with mean shrinkage (LNB-MS). The Laplace distribution instead of the normal distribution is used as the conditional distribution of the samples for the reasons that it is less sensitive to outliers and has been applied in many fields. The key technique is the L1 penalty imposed on the mean of each class to achieve automatic feature selection. The objective function of the proposed model is a piecewise linear function with respect to the mean of each class, of which the optimal value can be evaluated at the breakpoints simply. An efficient algorithm is designed to estimate the parameters in the model. A new strategy that uses the number of selected features to control the regularization parameter is introduced. Experimental results on simulated data sets and 17 publicly available cancer data sets attest to the accuracy, sparsity, efficiency, and robustness of the proposed algorithm. Many biomarkers identified with our method have been verified in biochemical or biomedical research. The analysis of biological and functional correlation of the genes based on Gene Ontology (GO) terms shows that the proposed method guarantees the selection of highly correlated genes simultaneously

  4. A Novel Classification Method for Prediction of Rectal Bleeding in Prostate Cancer Radiotherapy Based on a Semi-Nonnegative ICA of 3D Planned Dose Distributions.

    Science.gov (United States)

    Coloigner, Julie; Fargeas, Auréline; Kachenoura, Amar; Wang, Lu; Dréan, Gaël; Lafond, Caroline; Senhadji, Lotfi; de Crevoisier, Renaud; Acosta, Oscar; Albera, Laurent

    2015-05-01

    The understanding of dose/side-effects relationships in prostate cancer radiotherapy is crucial to define appropriate individual's constraints for the therapy planning. Most of the existing methods to predict side-effects do not fully exploit the rich spatial information conveyed by the three-dimensional planned dose distributions. We propose a new classification method for three-dimensional individuals' doses, based on a new semi-nonnegative ICA algorithm to identify patients at risk of presenting rectal bleeding from a population treated for prostate cancer. The method first determines two bases of vectors from the population data: the two bases span vector subspaces, which characterize patients with and without rectal bleeding, respectively. The classification is then achieved by calculating the distance of a given patient to the two subspaces. The results, obtained on a cohort of 87 patients (at two year follow-up) treated with radiotherapy, showed high performance in terms of sensitivity and specificity.

  5. 6 Common Cancers - Lung Cancer

    Science.gov (United States)

    ... Bar Home Current Issue Past Issues 6 Common Cancers - Lung Cancer Past Issues / Spring 2007 Table of Contents ... Desperate Housewives. (Photo ©2005 Kathy Hutchins / Hutchins) Lung Cancer Lung cancer causes more deaths than the next three ...

  6. Ethical issues raised by thyroid cancer overdiagnosis: A matter for public health?

    Science.gov (United States)

    Rogers, Wendy A; Craig, Wendy L; Entwistle, Vikki A

    2017-10-01

    Current practices of identifying and treating small indolent thyroid cancers constitute an important but in some ways unusual form of overdiagnosis. Overdiagnosis refers to diagnoses that generally harm rather than benefit patients, primarily because the diagnosed condition is not a harmful form of disease. Patients who are overdiagnosed with thyroid cancer are harmed by the psycho-social impact of a cancer diagnosis, as well as treatment interventions such partial or total thyroidectomy, lifelong thyroid replacement hormone, monitoring, surgical complications and other side effects. These harms seem to outweigh any putative benefit of knowing about a cancer that would not have caused problems if left undiscovered. In addition to harms to patients, thyroid cancer overdiagnosis leads to significant opportunity costs at a societal level, due to costs of diagnosis and treatment. Unlike many other overdiagnosed cancers, accurate risk stratification is possible with thyroid cancer. At the individual patient level, use of this risk information might support informed choice and/or shared decision-making, as mandated by clinical ethics frameworks. And this approach might, to some extent, help to reduce rates of diagnosis and intervention. In practice, however, it is unlikely to stem the rising incidence and associated harms and costs of overdiagnosed thyroid cancer, especially in situations where health professionals have conflicts of interest. We argue in this article that thyroid cancer overdiagnosis may be usefully understood as a public health problem, and that some public health approaches will be readily justifiable and are more likely to be effective in minimising its harms. © 2017 John Wiley & Sons Ltd.

  7. Is cancer a disease that can be cured? An answer based on a new classification of diseases

    CERN Document Server

    Richmond, Peter

    2016-01-01

    Is cancer a disease that can be cured or a degenerative disease which comes predominantly with old age? We give an answer based on a two-dimensional representation of diseases. These two dimensions are defined as follows. In mortality curves there is an age, namely a_c = 10 years, which plays a crucial role in the sense that the mortality rate decreases in the interval I1=(aa_c). The respective trends in I1 and I2 are the two parameters used in our classification of diseases. Within the framework of reliability analysis, I1 and I2 would be referred to as the "burn-in" and "wear-out" phases. This leads to define three broad groups of diseases. (AS1) Asymmetry with prevalence of I1. (AS2) Asymmetry with prevalence of I2. (S) Symmetry, with I1 and I2 both playing roles of comparable importance. Not surprisingly, among AS1-cases one finds all diseases due to congenital malformations. In the AS2-class one finds degenerative diseases, e.g. Alzheimer's disease. Among S-cases one finds most diseases due to external p...

  8. Is conversion therapy possible in stage IV gastric cancer: the proposal of new biological categories of classification.

    Science.gov (United States)

    Yoshida, Kazuhiro; Yamaguchi, Kazuya; Okumura, Naoki; Tanahashi, Toshiyuki; Kodera, Yasuhiro

    2016-04-01

    Conversion therapy for gastric cancer (GC) has been the subject of much recent attention. It is defined as a surgical treatment aiming at an R0 resection after chemotherapy for tumors that were originally unresectable or marginally resectable for technical and/or oncological reasons. However, the indications for resection remain to be clarified. In the present review, we focus on the biology and heterogeneous characteristics of stage IV GC and propose new categories of classification. Stage IV GC patients can be divided based on the absence (categories 1 and 2) or presence (categories 3 and 4) of macroscopically detectable peritoneal dissemination, which has a different biological outcome compared to hematological metastasis. Category 1 is defined oncologically as stage IV but the metastasis is technically resectable. Category 2 includes a marginally resectable metastasis or patients for whom the operation would not necessarily be the best choice. Category 3 includes a potentially unresectable metastasis of peritoneal dissemination that is only macroscopically detectable. Category 4 includes noncurable metastasis with peritoneal and other organ metastasis. The indications for conversion therapy might include the patients from category 2, some patients from category 3 and a very small number of patients from category 4. The longer survival can be expected for patients corresponding to categories 1, 2 and, to a lesser extent, 3, while the treatment of other patients focuses on "care." The provision of conversion therapy for stage IV GC patients might be one of the main roles of surgical oncologists in the near future.

  9. Clinical application of a microfluidic chip for immunocapture and quantification of circulating exosomes to assist breast cancer diagnosis and molecular classification.

    Science.gov (United States)

    Fang, Shimeng; Tian, Hongzhu; Li, Xiancheng; Jin, Dong; Li, Xiaojie; Kong, Jing; Yang, Chun; Yang, Xuesong; Lu, Yao; Luo, Yong; Lin, Bingcheng; Niu, Weidong; Liu, Tingjiao

    2017-01-01

    Increasing attention has been attracted by exosomes in blood-based diagnosis because cancer cells release more exosomes in serum than normal cells and these exosomes overexpress a certain number of cancer-related biomarkers. However, capture and biomarker analysis of exosomes for clinical application are technically challenging. In this study, we developed a microfluidic chip for immunocapture and quantification of circulating exosomes from small sample volume and applied this device in clinical study. Circulating EpCAM-positive exosomes were measured in 6 cases breast cancer patients and 3 healthy controls to assist diagnosis. A significant increase in the EpCAM-positive exosome level in these patients was detected, compared to healthy controls. Furthermore, we quantified circulating HER2-positive exosomes in 19 cases of breast cancer patients for molecular classification. We demonstrated that the exosomal HER2 expression levels were almost consistent with that in tumor tissues assessed by immunohistochemical staining. The microfluidic chip might provide a new platform to assist breast cancer diagnosis and molecular classification.

  10. Clinical audit on "Evaluation of special issues in adolescents with cancer treated in an adult cancer setting": An Indian experience

    Directory of Open Access Journals (Sweden)

    Naveen S Salins

    2012-01-01

    Results: Pain was the most common physical symptom seen in all 10 patients. 3 out of 10 patients were involved in decision making, 3 out of 10 patients had identity issues and 4 out of 10 patients had peer group isolation issues. Only 3 were aware of diagnosis and none were aware of treatment outcomes and mortality. 4 out of 10 had anxiety and depression and 3 out of 10 had body image issues. Sexuality, spiritual and existential issues were not explored in any of the patients studied. Conclusion: The outcomes of the study were in an adult oncology setting there was a poor recognition of key adolescent issues such as sexuality, body image, identity and peer group isolation. The psychosocial supports to these adolescents were minimal and spiritual and existential issues were not explored. The inferences drawn from this study suggested a need for multidisciplinary team approach oriented in handling adolescent care needs and preferably to have a dedicated space that will help the peer group to interact, bond and cope better with the illness.

  11. Cardiotoxicity of cancer therapeutics: current issues in screening, prevention and therapy

    Directory of Open Access Journals (Sweden)

    Richard Joseph Sheppard

    2013-03-01

    Full Text Available In the context of modern cancer chemotherapeutics, cancer survivors are living longer and being exposed to potential comorbidities related to non-cancer side effects of such treatments. With close monitoring of cancer patients receiving potentially cardiotoxic medical therapies, oncologists and cardiologists alike are identifying patients in both clinical and subclinical phases of cardiovascular disease related to such chemotherapies. Specifically, cardiotoxicity at the level of the myocardium and potential for the development of heart failure are becoming a growing concern with increasing survival of cancer patients.Traditional chemotherapeutic agents used commonly in the treatment of breast cancer and hematologic malignancies, such as anthracyclines and HER-2 antagonists, are well known to be associated with cardiovascular sequelae. Patients often present without symptoms and an abnormal cardiac imaging study performed as part of routine evaluation of patients receiving cardiotoxic therapies. Additionally, patients can present with signs and symptoms of cardiovascular disease months to years after receiving the chemotherapies. As the understanding of the physiology underlying the various cancers has grown, therapies have been developed that target specific molecules that represent key aspects of physiologic pathways responsible for cancer growth. Inhibition of these pathways, such as those involving tyrosine kinases, has lead to the potential for cardiotoxicity as well. In view of the potential cardiotoxicity of specific chemotherapies, there is a growing interest in identifying patients who are at risk of cardiotoxicity prior to becoming symptomatic or developing cardiotoxicity that may limit the use of potentially life-saving chemotherapy agents. Serological markers and novel cardiac imaging techniques have become the source of many investigations with the goal of screening patients for pre-clinical cardiotoxicity. Additionally, studies have

  12. Cancer as robust intrinsic state shaped by evolution: a key issues review

    Science.gov (United States)

    Yuan, Ruoshi; Zhu, Xiaomei; Wang, Gaowei; Li, Site; Ao, Ping

    2017-04-01

    Cancer is a complex disease: its pathology cannot be properly understood in terms of independent players—genes, proteins, molecular pathways, or their simple combinations. This is similar to many-body physics of a condensed phase that many important properties are not determined by a single atom or molecule. The rapidly accumulating large ‘omics’ data also require a new mechanistic and global underpinning to organize for rationalizing cancer complexity. A unifying and quantitative theory was proposed by some of the present authors that cancer is a robust state formed by the endogenous molecular-cellular network, which is evolutionarily built for the developmental processes and physiological functions. Cancer state is not optimized for the whole organism. The discovery of crucial players in cancer, together with their developmental and physiological roles, in turn, suggests the existence of a hierarchical structure within molecular biology systems. Such a structure enables a decision network to be constructed from experimental knowledge. By examining the nonlinear stochastic dynamics of the network, robust states corresponding to normal physiological and abnormal pathological phenotypes, including cancer, emerge naturally. The nonlinear dynamical model of the network leads to a more encompassing understanding than the prevailing linear-additive thinking in cancer research. So far, this theory has been applied to prostate, hepatocellular, gastric cancers and acute promyelocytic leukemia with initial success. It may offer an example of carrying physics inquiring spirit beyond its traditional domain: while quantitative approaches can address individual cases, however there must be general rules/laws to be discovered in biology and medicine.

  13. Skin Cancer Epidemics in the Elderly as An Emerging Issue in Geriatric Oncology.

    Science.gov (United States)

    Garcovich, Simone; Colloca, Giuseppe; Sollena, Pietro; Andrea, Bellieni; Balducci, Lodovico; Cho, William C; Bernabei, Roberto; Peris, Ketty

    2017-10-01

    Skin cancer is a worldwide, emerging clinical need in the elderly white population, with a steady increase in incidence rates, morbidity and related medical costs. Skin cancer is a heterogeneous group of cancers comprising cutaneous melanoma and non-melanoma skin cancers (NMSC), which predominantly affect elderly patients, aged older than 65 years. Melanoma has distinct clinical presentations in the elderly patient and represents a challenging question in terms of clinical management. NMSC includes the basal cell carcinoma and cutaneous squamous cell carcinoma and presents a wide disease spectrum in the elderly population, ranging from low-risk to high-risk tumours, advanced and inoperable disease. Treatment decisions for NMSC are preferentially based on tumour characteristics, patient's chronological age and physician's preferences and operational settings. Several treatment options are available for NMSC, from surgery to non-invasive/medical therapies, but patient-based factors, such as geriatric comorbidities and patient's life expectancy, do not frequently modulate treatment goals. In melanoma, age-related variations in clinical management are significant and may frequently lead to under-treatment, limiting access to advanced surgical and medical treatments. Clinical decision-making in the care of elderly skin cancer patient should ideally implement a geriatric assessment, prioritizing patient-based factors and efficiently differentiating fit from frail cancer patients. Current clinical practice guidelines for NMSC and melanoma only partially address geriatric aspects of cancer care, such as frailty, limited life-expectancy, geriatric comorbidities and treatment compliance. We review the recent evidence on the scope and problem of skin cancer in the elderly population as well as age-related variations in its clinical management, highlighting the potential role of a geriatric approach in optimizing dermato-oncological care.

  14. PULMONARY EMBOLISM: SOME ISSUES OF EPIDEMIOLOGY AND TREATMENT IN CANCER PATIENTS

    Directory of Open Access Journals (Sweden)

    I. D. Rozanov

    2015-01-01

    Full Text Available The risk of pulmonary embolism (PE in cancer patients  is 4–7-fold, compared to other  patient  categories. PE is the  second  most frequent  cause of death  in the first year after cancer diagnosis. PE is diagnosed in 7.5% of patients with malignant brain tumors, in 1 to 25% of those  with gastrointestinal tumors, in 4.5 to 17.5% of those with breast cancer and in 4 to 10% of lung cancer patients. The risk of PE is higher with surgical interventions and chemotherapy, as well as in metastatic tumors. In 13% of cases, PE may be the first symptom of cancer manifestation. For prevention and treatment of PE low molecular weight heparin (LMWH and warfarin are   used. The risk of recurrent  PE is 2-fold lower with LMWH. The frequency of bleeding with LMWH and warfarin treatment is from 14 to 19%. Placement of a cava filter is indicated  only if anticoagulation is inefficient.  New oral anticoagulants,  which act as selective thrombin  or Factor Xa inhibitors, are not used in cancer patients. Thus, diagnostics and treatment of PE is a very urgent  problem in oncology that requires new approaches to be looked for.

  15. Bilateral image subtraction features for multivariate automated classification of breast cancer risk

    Science.gov (United States)

    Celaya-Padilla, Jose M.; Rodriguez-Rojas, Juan; Galván-Tejada, Jorge I.; Martínez-Torteya, Antonio; Treviño, Victor; Tamez-Peña, José G.

    2014-03-01

    Early tumor detection is key in reducing breast cancer deaths and screening mammography is the most widely available method for early detection. However, mammogram interpretation is based on human radiologist, whose radiological skills, experience and workload makes radiological interpretation inconsistent. In an attempt to make mammographic interpretation more consistent, computer aided diagnosis (CADx) systems has been introduced. This paper presents an CADx system aimed to automatically triage normal mammograms form suspicious mammograms. The CADx system co-reregister the left and breast images, then extracts image features from the co-registered mammographic bilateral sets. Finally, an optimal logistic multivariate model is generated by means of an evolutionary search engine. In this study, 440 subjects form the DDSM public data sets were used: 44 normal mammograms, 201 malignant mass mammograms, and 195 mammograms with malignant calci cations. The results showed a cross validation accuracy of 0.88 and an area under receiver operating characteristic (AUC) of 0.89 for the calci cations vs. normal mammograms. The optimal mass vs. normal mammograms model obtained an accuracy of 0.85 and an AUC of 0.88.

  16. [Prevention of cervical cancer (II): prophylactic HPV vaccination, current knowledge, practical procedures and new issues].

    Science.gov (United States)

    Monsonego, Joseph

    2007-04-01

    Despite the considerable success of early screening for prevention of cervical cancer, Pap smears have not fulfilled the hopes that it would lead to a large-scale reduction of this cancer's incidence. Screening appears to be useful for a tiny portion of the world population, although a relatively large portion must put up with its limitations and disadvantages. Human papilloma viruses (HPV) 16 and 18 are responsible for two thirds of all cervical cancers worldwide. The condylomata (condyloma acuminatum), or genital warts, induced by HPV 6 and 11 are frequent among the young and difficult to manage. The extent and burden of HPV infection are considerable, as is the psychological and emotional impact of the diseases associated with it. Because cancer of the cervix is the final consequence of chronic HPV infection, it can be prevented by vaccination. A prophylactic vaccine to protect against the precancerous and cancerous lesions associated with HPV should save lives, reduce expensive diagnostic and therapeutic interventions, and have substantial individual and collective benefits. Clinical trials of anti-HPV vaccines for the prevention of cervical cancer and condyloma have shown remarkable results and an efficacy unequaled in the history of vaccination against infectious diseases. Vaccine efficacy has been shown only in young girls never exposed to the virus and only for the lesions associated with the specific viral types in the vaccine. Preliminary data indicate that the vaccination is effective in women who have previously eliminated naturally the virus. It has no therapeutic effects on existing lesions or in healthy virus carriers. Practical questions remain to be resolved. If the vaccination is left to individual initiative and vaccination coverage is insufficient, there will be no perceptible reduction in the frequency of cervical cancer. Vaccination policies will not be identical in poor countries, where the disease represents one of the leading causes of

  17. Ethics of palliative care in late-stage cancer management and end-of-life issues in a depressed economy.

    Science.gov (United States)

    Chukwuneke, F N

    2015-12-01

    The Hippocratic Oath has often been referred to as the ethical foundation of medical practice with the key restriction "cause no harm" which is also the principle of benevolence in bioethics. In medical profession, the Oath still exemplifies the key virtues of a doctor in its emphasis on the obligations toward the well-being of the individual patient. In management of end-stage cancer in a depressed economy such as Nigeria, we frequently encounter a wide range of ethical issues that arise in the provision of palliative care mostly due to the prevailing economic situation and cultural setting. Since most of these patients came from a lower economic class of the society, with little or no formal education and lived at a subsistence level, they often find it difficult to provide the medications needed. In a poor setting where health inequity is rife, and ignorance and poverty are commonplace, a good understanding of medical ethics with a good model of health care system will contribute to the health professional's decision-making that will be in the best interest of the patients. Physicians must protect the lives of their patients and should never hasten their death. In end-stage cancer management, we have to relieve suffering and pains, promote palliative care, and give psychological support but never abandoning the patient or initiate terminating their life. This presentation is a clinical analysis of the ethical issues regarding the management of end-stage cancer patients in a poor economy with a critical overview of end-of-life issues in African perspective.

  18. Colorectal Cancer in the Family: Psychosocial Distress and Social Issues in the Years Following Genetic Counselling

    Directory of Open Access Journals (Sweden)

    Bleiker Eveline MA

    2007-06-01

    Full Text Available Abstract Background This study examined: (1 levels of cancer-specific distress more than one year after genetic counselling for hereditary nonpolyposis colorectal cancer (HNPCC; (2 associations between sociodemographic, clinical and psychosocial factors and levels of distress; (3 the impact of genetic counselling on family relationships, and (4 social consequences of genetic counselling. Methods In this cross-sectional study, individuals who had received genetic counselling for HNPCC during 1986–1998 completed a self-report questionnaire by mail. Results 116 individuals (81% response rate completed the questionnaire, on average 4 years after the last counselling session. Of all respondents, 6% had clinically significant levels of cancer-specific distress (Impact of Event Scale, IES. Having had contact with a professional psychosocial worker for cancer risk in the past 10 years was significantly associated with higher levels of current cancer specific distress. Only a minority of the counselees reported any adverse effects of genetic counselling on: communication about genetic counselling with their children (9%, family relationships (5%, obtaining life insurance (8%, choice or change of jobs (2%, and obtaining a mortgage (2%. Conclusion On average, four years after genetic counselling for HNPCC, only a small minority of counselled individuals reports clinically significant levels of distress, or significant family or social problems.

  19. The future of general classification

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2013-01-01

    Discusses problems related to accessing multiple collections using a single retrieval language. Surveys the concepts of interoperability and switching language. Finds that mapping between more indexing languages always will be an approximation. Surveys the issues related to general classification...... and contrasts that to special classifications. Argues for the use of general classifications to provide access to collections nationally and internationally....

  20. [A systematic review of worldwide natural history models of colorectal cancer: classification, transition rate and a recommendation for developing Chinese population-specific model].

    Science.gov (United States)

    Li, Z F; Huang, H Y; Shi, J F; Guo, C G; Zou, S M; Liu, C C; Wang, Y; Wang, L; Zhu, S L; Wu, S L; Dai, M

    2017-02-10

    Objective: To review the worldwide studies on natural history models among colorectal cancer (CRC), and to inform building a Chinese population-specific CRC model and developing a platform for further evaluation of CRC screening and other interventions in population in China. Methods: A structured literature search process was conducted in PubMed and the target publication dates were from January 1995 to December 2014. Information about classification systems on both colorectal cancer and precancer on corresponding transition rate, were extracted and summarized. Indicators were mainly expressed by the medians and ranges of annual progression or regression rate. Results: A total of 24 studies were extracted from 1 022 studies, most were from America (n=9), but 2 from China including 1 from the mainland area, mainly based on Markov model (n=22). Classification systems for adenomas included progression risk (n=9) and the sizes of adenoma (n=13, divided into two ways) as follows: 1) Based on studies where adenoma was risk-dependent, the median annual transition rates, from ' normal status' to ' non-advanced adenoma', 'non-advanced' to ' advanced' and ' advanced adenoma' to CRC were 0.016 0 (range: 0.002 2-0.020 0), 0.020 (range: 0.002-0.177) and 0.044 (range: 0.005-0.063), respectively. 2) Median annual transition rates, based on studies where adenoma were classified by sizes, into system of CRC mainly included LRD (localized/regional/distant, n=10), Dukes' (n=7) and TNM (n=3). When using the LRD classification, the median annual transition rates from ' localized' to ' regional' and ' regional' to 'distant' were 0.28 (range: 0.20-0.33) and 0.40 (range: 0.24-0.63), respectively. Under the Dukes' classification, the median annual transition rates appeared as 0.583 (range: 0.050-0.910), 0.656 (range: 0.280-0.720) and 0.830 (range: 0.630-0.865) from Dukes' A to B, B to C and C to Dukes' D, respectively. Again, when using the TNM classification, very limited transition rate

  1. IARC use of oxidative stress as key mode of action characteristic for facilitating cancer classification: Glyphosate case example illustrating a lack of robustness in interpretative implementation.

    Science.gov (United States)

    Bus, James S

    2017-06-01

    The International Agency for Research on Cancer (IARC) has formulated 10 key characteristics of human carcinogens to incorporate mechanistic data into cancer hazard classifications. The analysis used glyphosate as a case example to examine the robustness of IARC's determination of oxidative stress as "strong" evidence supporting a plausible cancer mechanism in humans. The IARC analysis primarily relied on 14 human/mammalian studies; 19 non-mammalian studies were uninformative of human cancer given the broad spectrum of test species and extensive use of formulations and aquatic testing. The mammalian studies had substantial experimental limitations for informing cancer mechanism including use of: single doses and time points; cytotoxic/toxic test doses; tissues not identified as potential cancer targets; glyphosate formulations or mixtures; technically limited oxidative stress biomarkers. The doses were many orders of magnitude higher than human exposures determined in human biomonitoring studies. The glyphosate case example reveals that the IARC evaluation fell substantially short of "strong" supporting evidence of oxidative stress as a plausible human cancer mechanism, and suggests that other IARC monographs relying on the 10 key characteristics approach should be similarly examined for a lack of robust data integration fundamental to reasonable mode of action evaluations. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Standards for the Psychosocial Care of Children With Cancer and Their Families: An Introduction to the Special Issue.

    Science.gov (United States)

    Wiener, Lori; Kazak, Anne E; Noll, Robert B; Patenaude, Andrea Farkas; Kupst, Mary Jo

    2015-12-01

    Pediatric oncology psychosocial professionals collaborated with an interdisciplinary group of experts and stakeholders and developed evidence-based standards for pediatric psychosocial care. Given the breadth of research evidence and traditions of clinical care, 15 standards were derived. Each standard is based on a systematic review of relevant literature and used the AGREE II process to evaluate the quality of the evidence. This article describes the methods used to develop the standards and introduces the 15 articles included in this special issue. Established standards help ensure that all children with cancer and their families receive essential psychosocial care. © 2015 Wiley Periodicals, Inc.

  3. Breast cancer metastasis: issues for the personalization of its prevention and treatment.

    Science.gov (United States)

    Marino, Natascia; Woditschka, Stephan; Reed, L Tiffany; Nakayama, Joji; Mayer, Musa; Wetzel, Maria; Steeg, Patricia S

    2013-10-01

    Despite important progress in adjuvant and neoadjuvant therapies, metastatic disease often develops in breast cancer patients and remains the leading cause of their deaths. For patients with established metastatic disease, therapy is palliative, with few breaks and with mounting adverse effects. Many have hypothesized that a personalized or precision approach (the terms are used interchangeably) to cancer therapy, in which treatment is based on the individual characteristics of each patient, will provide better outcomes. Here, we discuss the molecular basis of breast cancer metastasis and the challenges in personalization of treatment. The instability of metastatic tumors remains a leading obstacle to personalization, because information from a patient's primary tumor may not accurately reflect the metastasis, and one metastasis may vary from another. Furthermore, the variable presence of tumor subpopulations, such as stem cells and dormant cells, may increase the complexity of the targeted treatments needed. Although molecular signatures and circulating biomarkers have been identified in breast cancer, there is lack of validated predictive molecular markers to optimize treatment choices for either prevention or treatment of metastatic disease. Finally, to maximize the information that can be obtained, increased attention to clinical trial design in the metastasis preventive setting is needed. Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

  4. Psychosocial issues in the diagnosis and management of cancer cachexia and anorexia.

    Science.gov (United States)

    Lesko, L M

    1989-01-01

    Anorexia with its associated decreased food intake and weight loss is a common and profoundly important symptom in cancer, and one which has at times a psychological as well as physical component. When it is physical in origin it may be caused directly or indirectly by the disease process or treatment. Most poorly understood is the anorexia-cachexia syndrome of advanced disease. Psychological causes often reflect anxiety about cancer, its possible progression, depression, anticipatory phenomena, and learned food adversions. Pre-existing psychiatric disorders, especially anorexia nervosa or paranoid states, can substantially complicate cancer treatment. Learned food aversions, which can further restrict limited intake, have been demonstrated in children receiving chemotherapy and may also contribute to aversions of specific foods seen among adult patients after chemotherapy or radiation. Regardless of etiology, psychological management of the anorexia is often helpful. Optimal management often involves use of a combination of modalities: psychotherapeutic, behavioral and/or pharmacologic supplemented by education, counseling and support. Behavioral techniques such as relaxation exercises are useful tools to alter this response as well as to relieve the anxiety precipitated by the patient's concerns about anorexia and weight loss. Environmental interventions and nutritional advice can also be of considerable value in reversing the negative effects of this distressing symptom in cancer.

  5. Interrogating open issues in cancer precision medicine with patient-derived xenografts

    NARCIS (Netherlands)

    Byrne, Annette T.; Alferez, Denis G.; Amant, Frederic; Annibali, Daniela; Arribas, Joaquin; Biankin, Andrew V.; Bruna, Alejandra; Budinska, Eva; Caldas, Carlos; Chang, David K.; Clarke, Robert B.; Clevers, Hans; Coukos, George; Dangles-Marie, Virginie; Eckhardt, S. Gail; Gonzalez-Suarez, Eva; Hermans, Els; Hidalgo, Manuel; Jarzabek, Monika A.; de Jong, Steven; Jonkers, Jos; Kemper, Kristel; Lanfrancone, Luisa; Maelandsmo, Gunhild Mari; Marangoni, Elisabetta; Marine, Jean-Christophe; Medico, Enzo; Norum, Jens Henrik; Palmer, Hector G.; Peeper, Daniel S.; Pelicci, Pier Giuseppe; Piris-Gimenez, Alejandro; Roman-Roman, Sergio; Rueda, Oscar M.; Seoane, Joan; Serra, Violeta; Soucek, Laura; Vanhecke, Dominique; Villanueva, Alberto; Vinolo, Emilie; Bertotti, Andrea; Trusolino, Livio

    Patient-derived xenografts (PDXs) have emerged as an important platform to elucidate new treatments and biomarkers in oncology. PDX models are used to address clinically relevant questions, including the contribution of tumour heterogeneity to therapeutic responsiveness, the patterns of cancer

  6. Interrogating open issues in cancer precision medicine with patient-derived xenografts

    NARCIS (Netherlands)

    Byrne, Annette T.; Alférez, Denis G.; Amant, Frédéric; Annibali, Daniela; Arribas, Joaquín; Biankin, Andrew V.; Bruna, Alejandra; Budinská, Eva; Caldas, Carlos; Chang, David K.; Clarke, Robert B.; Clevers, Hans; Coukos, George; Dangles-Marie, Virginie; Gail Eckhardt, S.; Gonzalez-Suarez, Eva; Hermans, Els; Hidalgo, Manuel; Jarzabek, Monika A.; De Jong, Steven; Jonkers, Jos; Kemper, Kristel; Lanfrancone, Luisa; Mælandsmo, Gunhild Mari; Marangoni, Elisabetta; Marine, Jean Christophe; Medico, Enzo; Norum, Jens Henrik; Palmer, Héctor G.; Peeper, Daniel S.; Pelicci, Pier Giuseppe; Piris-Gimenez, Alejandro; Roman-Roman, Sergio; Rueda, Oscar M.; Seoane, Joan; Serra, Violeta; Soucek, Laura; Vanhecke, Dominique; Villanueva, Alberto; Vinolo, Emilie; Bertotti, Andrea; Trusolino, Livio

    2017-01-01

    Patient-derived xenografts (PDXs) have emerged as an important platform to elucidate new treatments and biomarkers in oncology. PDX models are used to address clinically relevant questions, including the contribution of tumour heterogeneity to therapeutic responsiveness, the patterns of cancer

  7. Topical Issues of Adequate Antibiotic Therapy of Bacterial Complications of Pediatric Cancer Diseases

    Directory of Open Access Journals (Sweden)

    O.Ye. Chernyshova

    2015-09-01

    Full Text Available One of the main causes of morbidity in children with cancer blood diseases is development bacterial complications against the specific chemotherapy that are caused by antibiotic-resistant flora. The paper deals with a rational choice of antibiotic treatment of these patients.

  8. Regional radiotherapy in high-risk breast cancer: is the issue solved?

    DEFF Research Database (Denmark)

    Krause, M; Petersen, C; Offersen, B V

    2015-01-01

    Adjuvant radiotherapy is the treatment standard for breast cancer with lymph node metastases after breast-conserving surgery or mastectomy. The inclusion of regional lymph nodes into the treatment volumes has been a question in recent clinical trials. Their impact on treatment standards and open ...

  9. A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection.

    Science.gov (United States)

    Iliyasu, Abdullah M; Fatichah, Chastine

    2017-12-19

    A quantum hybrid (QH) intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO) method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN) algorithm (known simply as the Q-Fuzzy approach) is proposed for efficient feature selection and classification of cells in cervical smeared (CS) images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles) that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection) and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach). In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

  10. Prognostic value of the new International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification in stage IB lung adenocarcinoma.

    Science.gov (United States)

    Xu, C-h; Wang, W; Wei, Y; Hu, H-d; Zou, J; Yan, J; Yu, L-k; Yang, R-s; Wang, Y

    2015-10-01

    Patients with pathological stage IB lung adenocarcinoma have a variable prognosis, even if received the same treatment. This study investigated the prognostic value of the new International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society (IASLC/ATS/ERS) lung adenocarcinoma classification in resected stage IB lung adenocarcinoma. We identified 276 patients with pathological stage IB adenocarcinoma who had undergone surgical resection at the Nanjing Chest Hospital between 2005 and 2010. The histological subtypes of all patients were classified according to the 2011 IASLC/ATS/ERS international multidisciplinary lung adenocarcinoma classification. Kaplan-Meier and Cox regression analyses were used to analyze the correlation between the IASLC/ATS/ERS classification and patients' prognosis. Two hundred and seventy-six patients with pathological stage IB adenocarcinoma had an 86.2% 5-year overall survival (OS) and 80.4% 5-year disease-free survival (DFS). Patients with micropapillary and solid predominant tumors had a significantly worse OS and DFS as compared to those with other subtypes predominant tumors (p = 0.003 and 0.001). Multivariate analysis revealed that the new classification was an independent prognostic factor for both OS and DFS of pathological stage IB adenocarcinoma (p = 0.009 and 0.003). Our study revealed that the new IASLC/ATS/ERS classification was an independent prognostic factor of pathological stage IB adenocarcinoma. This new classification is valuable of screening out high risk patients to receive postoperative adjuvant therapy. Copyright © 2015. Published by Elsevier Ltd.

  11. Industrial pollution and cancer in Spain: An important public health issue.

    Science.gov (United States)

    Fernández-Navarro, Pablo; García-Pérez, Javier; Ramis, Rebeca; Boldo, Elena; López-Abente, Gonzalo

    2017-11-01

    Cancer can be caused by exposure to air pollution released by industrial facilities. The European Pollutant Release and Transfer Register (E-PRTR) has made it possible to study exposure to industrial pollution. This study seeks to describe the industrial emissions in the vicinity of Spanish towns and their temporal changes, and review our experience studying industrial pollution and cancer. Data on industrial pollutant sources (2007-2010) were obtained from the E-PRTR registries. Population exposure was estimated by the distance from towns to industrial facilities. We calculated the amount of carcinogens emitted into the air in the proximity (cancer mortality and industrial pollution in Spain and the limitations and result interpretations of these types of studies. There are high amounts of carcinogen emissions in the proximity of towns in the southwest, east and north of the country and the total amount of emitted carcinogens is considerable (e.g. 20Mt of arsenic, 63Mt of chromium and 9Mt of cadmium). Although the emissions of some carcinogens in the proximity of certain towns were reduced during the study period, emissions of benzene, dioxins+furans and polychlorinated biphenyls rose. Moreover, the average population of towns lying within a 5km radius from emission sources of carcinogens included in the International Agency for Research on Cancer list of carcinogens was 9 million persons. On the other hand, the results of the reviewed studies suggest that those Spanish regions exposed to the pollution released by certain types of industrial facilities have around 17% cancer excess mortality when compared with those unexposed. Moreover, excess mortality is focused on digestive and respiratory tract cancers, leukemias, prostate, breast and ovarian cancers. Despite their limitations, ecological studies are a useful tool in environmental epidemiology, not only for proposing etiological hypotheses about the risk of living close to industrial pollutant sources, but

  12. Peace of mind and sense of purpose as core existential issues among parents of children with cancer.

    Science.gov (United States)

    Mack, Jennifer W; Wolfe, Joanne; Cook, E Francis; Grier, Holcombe E; Cleary, Paul D; Weeks, Jane C

    2009-06-01

    To evaluate issues experienced by parents of children with cancer and factors related to parents' ability to find peace of mind. Cross-sectional survey. Dana-Farber Cancer Institute and Children's Hospital, Boston, Massachusetts. One hundred ninety-four parents of children with cancer (response rate, 70%) in the first year of cancer treatment. The Functional Assessment of Chronic Illness Therapy-Spiritual Well-being sense of meaning subscale. Principal components analysis of Functional Assessment of Chronic Illness Therapy-Spiritual Well-being sense of meaning subscale responses identified 2 distinct constructs, peace of mind (Cronbach alpha = .83) and sense of purpose (Cronbach alpha = .71). Scores ranged from 1 to 5, with 5 representing the strongest sense of peace or purpose. One hundred forty-seven of 181 parents (81%) scored 4 or higher for questions related to sense of purpose (mean [SD] score, 4.4 [0.6]). Only 44 of 185 parents (24%) had scores in the same range for peace of mind (mean [SD] score, 3.2 [0.9]) (P peace of mind scores when they also reported that they trusted the oncologist's judgment (odds ratio [OR] = 6.65; 95% confidence interval [CI], 1.47-30.02), that the oncologist had disclosed detailed prognostic information (OR = 2.05; 95% CI, 1.14-3.70), and that the oncologist had provided high-quality information about the cancer (OR = 2.54; 95% CI, 1.11-5.79). Peace of mind was not associated with prognosis (OR = 0.74; 95% CI, 0.41-1.32) or time since diagnosis (OR = 1.00; 95% CI, 0.995-1.003). Physicians may be able to facilitate formulation of peace of mind by giving parents high-quality medical information, including prognostic information, and facilitating parents' trust.

  13. Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

    Science.gov (United States)

    Lestari, A. W.; Rustam, Z.

    2017-07-01

    In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

  14. Identifying the concepts contained in outcome measures of clinical trials on breast cancer using the International Classification of Functioning, Disability and Health as a reference.

    Science.gov (United States)

    Brockow, Thomas; Duddeck, Katharina; Geyh, Szilvia; Schwarzkopf, Susanne; Weigl, Martin; Franke, Thomas; Brach, Mirjam

    2004-07-01

    To systematically identify and quantify the concepts contained in outcome measures of clinical breast cancer trials using the International Classification of Functioning, Disability and Health (ICF) as a reference. Randomized controlled trials between 1991 and 2000 were located in MEDLINE and selected according predefined criteria. The outcome measures were extracted and the concepts contained in the outcome measures were linked to the ICF. A total of 640 trials were included. Ninety-four different health status questionnaires were extracted. Three questionnaires were breast cancer-specific and 12 cancer-specific. Of 19,692 extracted concepts, 88% could be linked to the ICF. The most used ICF categories within the components body structures, body functions, and activities and participation were structure of the reproductive system (s630), sensations associated with the digestive system (b535), and looking after one's health (d570) with frequencies of 64%, 46% and 14%, respectively. No category of the environmental factors component reached a frequency of 10%. The ICF provides a useful reference to identify and quantify the concepts contained in outcome assessment used in clinical breast cancer trials. There seems to be a lack of health concepts evaluating specific aspects of disability and participation in breast cancer. Similarly, environmental factors with an impact on individual life of breast cancer survivors seem to be poorly represented.

  15. Symptom control issues and supportive care of patients with head and neck cancers.

    Science.gov (United States)

    Murphy, Barbara A; Gilbert, Jill; Cmelak, Anthony; Ridner, Sheila H

    2007-10-01

    Combined-modality treatment of head and neck cancers, though linked to improved outcomes over earlier treatment methods, can be associated with acute and late adverse effects. These toxicities may lead to significant morbidity, increased mortality, and decreased quality of life. It is necessary to provide patients with adequate supportive-care measures in order to lessen suffering while maintaining the ability to deliver necessary doses of anticancer agents. The current review describes the pathology, assessment, and treatment options for cases of mucositis, impaired swallowing, nutritional and metabolic changes, xerostomia, radiation dermatitis, lymphedema, taste alterations, and pain, all of which may be associated with treatment of patients with head and neck cancers. Additionally, the pretreatment and during-treatment evaluation of dental health, as well as posttreatment dental care, are described.

  16. Clinical issues: music therapy in an adult cancer inpatient treatment setting.

    Science.gov (United States)

    O'Callaghan, Clare

    2006-01-01

    The adult oncology inpatient music therapy program at Peter MacCallum Cancer Center, which is Australia's only hospital solely dedicated to cancer treatment, research and care, is described. Patients' treatment requirements and often changing conditions compel music therapist to be flexible in their approach, offering both pre-planned treatment sessions and spontaneous sessions in open ward contexts. Patients and families who wish to engage im music therapy choose from various music therapy methods, including live song choice, music imagery and relaxation, therapeutic music lessons, and improvisation. Complex variables inevitable in such human relationship therapies necessitate that, alongside randomized controlled trials, research methods are grounded in the social sciences to meaningfully substantiate, and further advance, oncologic music therapy.

  17. Preoperative Axillary Lymph Node Evaluation in Breast Cancer: Current Issues and Literature Review.

    Science.gov (United States)

    Choi, Hee Young; Park, Minho; Seo, Mirinae; Song, Eunjee; Shin, So Youn; Sohn, Yu-Mee

    2017-03-01

    Axillary lymph node (ALN) status is an important prognostic factor for overall breast cancer survival. In current clinical practice, ALN status is evaluated before surgery via multimodal imaging and physical examination. Mammography is typically suboptimal for complete ALN evaluation. Currently, ultrasonography is widely used to evaluate ALN status; nonetheless, results may vary according to operator. Ultrasonography is the primary imaging modality for evaluating ALN status. Other imaging modalities including contrast-enhanced magnetic resonance imaging, computed tomography, and positron emission tomography/computed tomography can play additional roles in axillary nodal staging.The purpose of this article is (1) to review the strengths and weaknesses of current imaging modalities for nodal staging in breast cancer patients and (2) to discuss updated guidelines for ALN management with regard to preoperative ALN imaging.

  18. Training the powerful: issues that emerged during the evaluation of a communication skills training programme for senior cancer care professionals.

    Science.gov (United States)

    Bibila, S; Rabiee, F

    2014-07-01

    'Connected' is the name of the national advanced communication skills training programme developed in 2008 for cancer care professionals in the NHS. A 3-day training course combining didactic and experiential learning elements is run by two facilitators with course participants expected to engage fully in simulated consultations with trained actors. In 2011, and as a result of participant feedback on the length of the course and increasing pressures on budgets and clinical time, the Connected team developed and piloted an alternative 2-day training course. Before its roll-out in 2012, Birmingham City University was commissioned to evaluate the effectiveness and quality of the 2-day course vis-à-vis the 'traditional' 3-day one. This article is written by the two evaluators and it discusses some of the issues that emerged during the evaluation. We broadly grouped these issues into two overlapping categories: the mandatory nature of the course and the different professional background and seniority of participants. In our discussion we consider the implications these issues have for communication skills training policy and practice and put forward suggestions for further research. © 2013 John Wiley & Sons Ltd.

  19. Methodological issues in estimating survival in patients with multiple primary cancers: an application to women with breast cancer as a first tumour

    Directory of Open Access Journals (Sweden)

    Ricceri Fulvio

    2009-02-01

    Full Text Available Abstract Background Comparing survival of patients with a single tumour and patients with multiple primaries poses different methodological problems. In population based studies, where we cannot rely on detailed clinical information, the issue is disentangling the share of survival probability from the first and second cancer, and their compounded effect. We examined three hypotheses: A the survival probability since the first tumour does not change with the occurrence of a second tumour; B the probability of surviving a tumour does not change with the presence of a previous primary; C the probabilities of surviving two subsequent primary tumours are independent (additivity hypothesis on mortality rates. Methods We studied the survival probabilities modelling mortality rates according to hypotheses A, B and C. Mortality rates were calculated using Aalen-Johansen estimators which allowed to discount for the lag-time survival before developing a second tumour. We applied this approach to a cohort of 436 women with breast cancer (BC and a subsequent tumour in the resident population of Turin, Italy, between 1985 and 2002. Results We presented our results in term of a Standardised Mortality Ratio calculated (SMRAJ after 10 years of follow-up. For hypothesis A we observed a significant excess mortality of 2.21 (95% C.I. 1.94 – 2.45. Concerning hypothesis B we found a not significant SMRAJ of 0.98 (95% C.I. 0.87 – 1.10. The additivity hypothesis (C was not confirmed as it overestimated the risk of death, in fact SMRsAJ were all below 1: 0.75 (95% C.I. 0.66 – 0.84 for BC and all subsequent cancers, 0.72 (95% C.I. 0.55 – 0.94 for BC and colon-rectum cancer, 0.76 (95% C.I. 0.48 – 1.14 for BC and corpus uteri cancer (not significant. Conclusion This method proved to be useful in disentangling the effect of different subsequent cancers on mortality. In our application it shows a worse long-term mortality for women with two cancers than that with

  20. Principles of cancer screening: lessons from history and study design issues.

    Science.gov (United States)

    Croswell, Jennifer M; Ransohoff, David F; Kramer, Barnett S

    2010-06-01

    Early detection of cancer has held great promise and intuitive appeal in the medical community for well over a century. Its history developed in tandem with that of the periodic health examination, in which any deviations--subtle or glaring--from a clearly demarcated "normal" were to be rooted out, given the underlying hypothesis that diseases develop along progressive linear paths of increasing abnormalities. This model of disease development drove the logical deduction that early detection, by "breaking the chain" of cancer development, must be of benefit to affected individuals. In the latter half of the 20th century, researchers and guidelines organizations began to explicitly challenge the core assumptions underpinning many clinical practices. A move away from intuitive thinking began with the development of evidence-based medicine. One key method developed to explicitly quantify the overall risk-benefit profile of a given procedure was the analytic framework. The shift away from pure deductive reasoning and reliance on personal observation was driven, in part, by a rising awareness of critical biases in cancer screening that can mislead clinicians, including healthy volunteer bias, length-biased sampling, lead-time bias, and overdiagnosis. A new focus on the net balance of both benefits and harms when determining the overall worth of an intervention also arose: it was recognized that the potential downsides of early detection were frequently overlooked or discounted because screening is performed on basically healthy persons and initially involves relatively noninvasive methods. Although still inconsistently applied to early detection programs, policies, and belief systems in the United States, an evidence-based approach is essential to counteract the misleading--even potentially harmful--allure of intuition and individual observation. Published by Elsevier Inc.

  1. Cardio-oncology issues among pediatric cancer and stem cell transplant survivors.

    Science.gov (United States)

    Hochberg, Jessica C; Cairo, Mitchell S; Friedman, Deborah M

    2014-01-01

    Improvements in the survival of children and adolescents diagnosed with cancer have resulted in a growing population of childhood, adolescent and adult cancer and stem cell transplant survivors. Approximately two thirds of these survivors will experience at least 1 late effect of their treatment, and about one third will experience a late effect that is severe or life threatening. Childhood cancer survivors are at high risk for development of severe cardiac disease, particularly after anthracycline and/or radiation exposure. Cardiotoxicity can present as early cardiac dysfunction during or shortly after therapy or as chronic impairment of cardiac function several years after treatment. Attempts to minimize serious adverse effects have included reduction of high-dose chemotherapy, particularly anthracycline dosing to <350 mg/m, use of cardioprotective agents such as dexrazoxane and decreased radiation dosing and radiation fields. There have been no convincing data showing medical interventions that can reliably slow or reverse cardiotoxicity in treated patients, which therefore warrants further studies looking at the use of beta blockers, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, or newer agents either prior to or following the discovery of heart damage. Emphasis on the prevention of further damage is critical and can be accomplished through aggressive surveillance, including screening for lipid abnormalities, cardiac biomarkers such as troponins and B-type natriuretic peptides, hypertension, diabetes and obesity as well as the use of echocardiography and cardiac magnetic resonance imaging to identify abnormalities early in their course. Here, we provide an overview of the field of cardio-oncology to stimulate interest among cardiologists.

  2. Vitamin D3 in cancer prevention and therapy: the nutritional issue.

    Science.gov (United States)

    Chirumbolo, Salvatore

    2015-09-01

    The action of vitamin D3, in its biological form 1α,25(OH)2vitD3 or calcitriol, may be summarized as a steroid-like hormone able to modulate basic functions of cell encompassing energy balance, stress response, mitochondria biogenesis, intracellular calcium oscillations, and replication/apoptosis mechanisms leading to cell survival. Moreover, calcitriol exerts a potent role as an innate and adaptive immune cytokine as immunity is closely related to self-maintenance through its energetic/metabolic balance and homeostasis of cell turnover. Therefore, vitamin D might be the ancestral form of survival hormones developed with calcified vertebrate bearing skeleton in order to survive far from water. This characteristic may suggest that the role of dietary vitamin D in preventing cancer is simply ancillary to the many factors playing a major role in contrasting impairment in energy balance and cell survival. Most probably, the immune role of calcitriol might be included in the maintenance, mostly by adipose tissue, of an anti-inflammatory, tolerant immune status, depending on the immune tolerance and modulation from the gut. A balance closely modulated by the leptin axis, which when impairments in metabolism occur, such as in insulin resistance or obesity, calcitriol is unable to face at this imbalance, while leptin plays a major role and cancer progression may be promoted. Furthermore, this mechanism promotes epithelial/mesenchymal transition-mediated fibrosis, leading to cancer resistance to immune control and drug action. Interestingly, this pathologic picture is triggered by deficiency in vitamin D from the diet. Therefore, a dietary habit including vitamin D sources, besides flavonoids, may ameliorate lifestyle and health span in most individuals, depending on their genetic background.

  3. Reverse phase protein array based tumor profiling identifies a biomarker signature for risk classification of hormone receptor-positive breast cancer

    Directory of Open Access Journals (Sweden)

    Johanna Sonntag

    2014-03-01

    Full Text Available A robust subclassification of luminal breast cancer, the most common molecular subtype of human breast cancer, is crucial for therapy decisions. While a part of patients is at higher risk of recurrence and requires chemo-endocrine treatment, the other part is at lower risk and also poorly responds to chemotherapeutic regimens. To approximate the risk of cancer recurrence, clinical guidelines recommend determining histologic grading and abundance of a cell proliferation marker in tumor specimens. However, this approach assigns an intermediate risk to a substantial number of patients and in addition suffers from a high interobserver variability. Therefore, the aim of our study was to identify a quantitative protein biomarker signature to facilitate risk classification. Reverse phase protein arrays (RPPA were used to obtain quantitative expression data for 128 breast cancer relevant proteins in a set of hormone receptor-positive tumors (n = 109. Proteomic data for the subset of histologic G1 (n = 14 and G3 (n = 22 samples were used for biomarker discovery serving as surrogates of low and high recurrence risk, respectively. A novel biomarker selection workflow based on combining three different classification methods identified caveolin-1, NDKA, RPS6, and Ki-67 as top candidates. NDKA, RPS6, and Ki-67 were expressed at elevated levels in high risk tumors whereas caveolin-1 was observed as downregulated. The identified biomarker signature was subsequently analyzed using an independent test set (AUC = 0.78. Further evaluation of the identified biomarker panel by Western blot and mRNA profiling confirmed the proteomic signature obtained by RPPA. In conclusion, the biomarker signature introduced supports RPPA as a tool for cancer biomarker discovery.

  4. Molecular and clinical support for a four-tiered grading system for bladder cancer based on the WHO 1973 and 2004 classifications.

    Science.gov (United States)

    van Rhijn, Bas W G; Musquera, Mireia; Liu, Liyang; Vis, André N; Zuiverloon, Tahlita C M; van Leenders, Geert J L H; Kirkels, Wim J; Zwarthoff, Ellen C; Boevé, Egbert R; Jöbsis, Adriaan C; Bapat, Bharati; Jewett, Michael A S; Zlotta, Alexandre R; van der Kwast, Theo H

    2015-05-01

    Currently, the use of two classification systems for bladder cancer grade is advocated in clinical guidelines because the WHO2004 classification has not been sufficiently validated with biological markers and follow-up. The slides of 325 primary non-muscle invasive bladder cancers from three hospitals were reviewed by one uro-pathologist in two separate sessions for the WHO1973 (G1, G2 and G3) and 2004 (papillary urothelial neoplasm of low malignant potential (LMP), low-grade (LG) and high-grade (HG)) classifications. FGFR3 status was examined with PCR-SNaPshot analysis. Expression of Ki-67, P53 and P27 was analyzed by immuno-histochemistry. Clinical recurrence and progression were determined. We performed validation and cross-validation of the two systems for grade with molecular markers and clinical outcome. Multivariable analyses were done to predict prognosis and pT1 bladder cancer. Grade review resulted in 88 G1, 149 G2 and 88 G3 lesions (WHO1973) and 79 LMP, 101 LG and 145 HG lesions (WHO2004). Molecular validation of both grading systems showed that FGFR3 mutations were associated with lower grades whereas altered expression (Ki-67, P53 and P27) was found in higher grades. Clinical validation showed that the two classification systems were both significant predictors for progression but not for recurrence. Cross-validation of both WHO systems showed a significant stepwise increase in biological (molecular markers) and clinical (progression) potential along the line: G1-LG-G2-HG-G3. The LMP and G1 categories had a similar clinical and molecular profile. On the basis of molecular biology and multivariable clinical data, our results support a four-tiered grading system using the 1973 and 2004 WHO classifications with one low-grade (LMP/LG/G1) category that includes LMP, two intermediate grade (LG/G2 and HG/G2) categories and one high-grade (HG/G3) category.

  5. Revision, uptake and coding issues related to the open access Orchard Sports Injury Classification System (OSICS versions 8, 9 and 10.1

    Directory of Open Access Journals (Sweden)

    John Orchard

    2010-10-01

    Full Text Available John Orchard1, Katherine Rae1, John Brooks2, Martin Hägglund3, Lluis Til4, David Wales5, Tim Wood61Sports Medicine at Sydney University, Sydney NSW Australia; 2Rugby Football Union, Twickenham, England, UK; 3Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; 4FC Barcelona, Barcelona, Catalonia, Spain; 5Arsenal FC, Highbury, England, UK; 6Tennis Australia, Melbourne, Vic, AustraliaAbstract: The Orchard Sports Injury Classification System (OSICS is one of the world’s most commonly used systems for coding injury diagnoses in sports injury surveillance systems. Its major strengths are that it has wide usage, has codes specific to sports medicine and that it is free to use. Literature searches and stakeholder consultations were made to assess the uptake of OSICS and to develop new versions. OSICS was commonly used in the sports of football (soccer, Australian football, rugby union, cricket and tennis. It is referenced in international papers in three sports and used in four commercially available computerised injury management systems. Suggested injury categories for the major sports are presented. New versions OSICS 9 (three digit codes and OSICS 10.1 (four digit codes are presented. OSICS is a potentially helpful component of a comprehensive sports injury surveillance system, but many other components are required. Choices made in developing these components should ideally be agreed upon by groups of researchers in consensus statements.Keywords: sports injury classification, epidemiology, surveillance, coding

  6. Topical interferon alfa-2b for management of ocular surface squamous neoplasia in 23 cases: outcomes based on American Joint Committee on Cancer classification.

    Science.gov (United States)

    Shah, Sanket U; Kaliki, Swathi; Kim, H Jane; Lally, Sara E; Shields, Jerry A; Shields, Carol L

    2012-02-01

    To evaluate the efficacy of topical interferon alfa-2b in the management of ocular surface squamous neoplasia (OSSN). Clinically visible OSSN in 20 patients (23 tumors) was managed with topical interferon alfa-2b, 1 million IU/mL, 4 times daily. Tumor control and complications were evaluated according to American Joint Committee on Cancer classification. Complete tumor resolution was achieved in 19 tumors (83%) following topical interferon alfa-2b treatment for a median period of 6 months (mean, 7 months; range, 1-12 months) and maintained for up to 24 months of follow-up. Of the 4 tumors with partial resolution (17%), tumor surface area was reduced 44% (median) during 4 months (median) without further response and alternative therapy was used. Based on American Joint Committee on Cancer classification, complete control was achieved in 2 of 3 Tis (67%), 17 of 20 T3 (85%), 19 of 23 N0 (83%), and 19 of 23 M0 (83%) category tumors. Tumors involving the cornea responded earlier compared with those without corneal involvement (P = .01). Initial tumor size did not correlate with time to response (P = .27). Recurrence was noted in 1 case (Tis, 4%) at 3 months. Adverse effects included conjunctival hyperemia (2 [10%]), follicular hypertrophy (2 [10%]), giant papillary conjunctivitis (1 [5%]), irritation (1 [5%]), corneal epithelial defect (1 [5%]), and flulike symptoms (1 [5%]); all resolved within 1 month of medication discontinuation. According to American Joint Committee on Cancer classification, complete control with topical interferon alfa-2b can be achieved in 67% of Tis, 85% of T3, and 83% of all OSSN.

  7. Immune Monitoring in Cancer Vaccine Clinical Trials: Critical Issues of Functional Flow Cytometry-Based Assays

    Directory of Open Access Journals (Sweden)

    Iole Macchia

    2013-01-01

    Full Text Available The development of immune monitoring assays is essential to determine the immune responses against tumor-specific antigens (TSAs and tumor-associated antigens (TAAs and their possible correlation with clinical outcome in cancer patients receiving immunotherapies. Despite the wide range of techniques used, to date these assays have not shown consistent results among clinical trials and failed to define surrogate markers of clinical efficacy to antitumor vaccines. Multiparameter flow cytometry- (FCM- based assays combining different phenotypic and functional markers have been developed in the past decade for informative and longitudinal analysis of polyfunctional T-cells. These technologies were designed to address the complexity and functional heterogeneity of cancer biology and cellular immunity and to define biomarkers predicting clinical response to anticancer treatment. So far, there is still a lack of standardization of some of these immunological tests. The aim of this review is to overview the latest technologies for immune monitoring and to highlight critical steps involved in some of the FCM-based cellular immune assays. In particular, our laboratory is focused on melanoma vaccine research and thus our main goal was the validation of a functional multiparameter test (FMT combining different functional and lineage markers to be applied in clinical trials involving patients with melanoma.

  8. 6 Common Cancers - Prostate Cancer

    Science.gov (United States)

    ... Bar Home Current Issue Past Issues 6 Common Cancers - Prostate Cancer Past Issues / Spring 2007 Table of Contents ... early screening. Photo: AP Photo/Danny Moloshok Prostate Cancer The prostate gland is a walnut-sized structure that makes ...

  9. Addressing Quality of Life Issues in Long Term Survivors of Head & Neck Cancer treated with Radiation Therapy

    Directory of Open Access Journals (Sweden)

    Bishan Basu

    2015-04-01

    Full Text Available The rapid advancement of curative treatment modalities has resulted in improvement of cure rates of head neck cancer leaving us with a larger number of long term survivors from the disease. Unfortunately, long term complications of therapy continue to hurt patients even after cure, compromising their quality of life. This is particularly true for the patients treated with primary radiation/chemo-radiation therapy, where so called organ preservation does not necessarily translate into preservation of organ function. Long term sequelae of treatment, particularly xerostomia and swallowing difficulties compromise the survivors’ quality of life. More studies, particularly suited to our clinical scenario, are warranted to address the quality of life issues in these patients, so that better evidence-based guidelines may be developed for their benefit.

  10. Issues relating to classification of colluvial soils in young morainic areas (Chełmno and Brodnica Lake District, northern Poland

    Directory of Open Access Journals (Sweden)

    Świtoniak Marcin

    2015-06-01

    Full Text Available Colluvial soils (in Polish: gleby deluwialne are an important part of the soil cover in young morainic landscapes of northern Poland. They evolved as a result of the accumulation of eroded material at the foot of the slopes and bottoms of closed depressions. The aim of this study was to determine the systematic position of colluvial soils commonly found in the Chełmno and Brodnica Lake District, northern Poland. Ten soil pits located in different types of landscapes were selected for testing soil properties. The colluvial material is characterized by diversified properties: thickness, particle-size distribution, organic carbon content, color, pH, and base saturation. As a result, the investigated soils represent broad spectrum of typological units according to Polish Soil Classification (2011. Some of them contain epipedons mollic and meet the criteria of colluvial chernozemic soils. They were found mainly on buried black earths in areas with small slope inclinations. Many pedons contain pale colored acidic colluvial material with low base saturation and low organic carbon content and must be classified as other types: arenosols (in Polish: arenosole or rusty soils (in Polish: gleby rdzawe. These soils occur mostly in areas with intensive relief and overlay the different soil types, including rusty soil and organic soils. They are formed as a result of soils lessivés and rusty soils truncation. An introduction of the additional units of “proper colluvial soils” which have epipedon ochric, and “rusty-colluvial soils” with endopedon sideric to the next edition of Polish Soil Classification would enable a more precise expression of the genesis of these soils in the type rank. Moreover, the definition of chernozemic colluvial soils could be extended to colluvial soils with umbric horizon. Classifying soils derived from colluvial material as soils of other types leads to the disappearance of this units on maps and underestimation of the

  11. Determining issues of importance for the evaluation of quality of life and patient-reported outcomes in breast cancer: results of a survey of 1072 patients.

    Science.gov (United States)

    Hollen, Patricia J; Msaouel, Pavlos; Gralla, Richard J

    2015-06-01

    Identifying key issues for patients is central to assessing treatment for cancer, especially when evaluating health-related quality of life (QL) and patient-reported outcomes (PROs). This study was conducted to provide enhanced content validity support by incorporating the views of a large number of patients with breast cancer. This methodological study used an anonymous, cross-sectional, electronic web-based survey of 1072 patients with a diagnosis of breast cancer. Patients ranked the importance of 21 issues on a 5-point scale. Issues included general, physical, functional, psychosocial, and summative items. Analysis was also performed by four key factors (age group, time since diagnosis, adjuvant treatment or not, and tumor extent). All of the top five issues rated as either "very important" or "important" were global issues-rather than symptoms-such as maintaining quality of life (ranked in these two highest categories by 99 % of patients), maintaining independence (97 %), and ability to perform normal activities (97 %). The abilities to concentrate and to be able to sleep (97 and 96 %, respectively) were ranked above specific breast cancer symptoms. Specific symptoms included within the top ten highest ranked items were fatigue, depression, anxiety, shortness of breath, and pain. This is the largest analysis of evidence-based data determining support for content validity for QL and PROs provided by patients with breast cancer. While symptoms are important to patients, the survey also demonstrates that PRO measures that only evaluate symptoms are not fully responding to patient-expressed needs. These results provide confidence in the content of quality of life measures for large groups of patients with breast cancer, including the new Breast Cancer Symptom Scale (BCSS) questionnaire.

  12. Uncertainties in Biologically-Based Modeling of Formaldehyde-Induced Respiratory Cancer Risk: Identification of Key Issues

    Science.gov (United States)

    Subramaniam, Ravi P.; Chen, Chao; Crump, Kenny S.; DeVoney, Danielle; Fox, John F.; Portier, Christopher J.; Schlosser, Paul M.; Thompson, Chad M.; White, Paul

    2009-01-01

    In a series of articles and a health-risk assessment report, scientists at the CIIT Hamner Institutes developed a model (CIIT model) for estimating respiratory cancer risk due to inhaled formaldehyde within a conceptual framework incorporating extensive mechanistic information and advanced computational methods at the toxicokinetic and toxicodynamic levels. Several regulatory bodies have utilized predictions from this model; on the other hand, upon detailed evaluation the California EPA has decided against doing so. In this article, we study the CIIT model to identify key biological and statistical uncertainties that need careful evaluation if such two-stage clonal expansion models are to be used for extrapolation of cancer risk from animal bioassays to human exposure. Broadly, these issues pertain to the use and interpretation of experimental labeling index and tumor data, the evaluation and biological interpretation of estimated parameters, and uncertainties in model specification, in particular that of initiated cells. We also identify key uncertainties in the scale-up of the CIIT model to humans, focusing on assumptions underlying model parameters for cell replication rates and formaldehyde-induced mutation. We discuss uncertainties in identifying parameter values in the model used to estimate and extrapolate DNA protein cross-link levels. The authors of the CIIT modeling endeavor characterized their human risk estimates as “conservative in the face of modeling uncertainties.” The uncertainties discussed in this article indicate that such a claim is premature. PMID:18564991

  13. Clinical and organizational issues in the management of surviving breast and colorectal cancer patients: attitudes and feelings of medical oncologists.

    Directory of Open Access Journals (Sweden)

    Gianmauro Numico

    Full Text Available The fast growing demand and the shortage of resources are pushing toward more efficient models of survivorship care delivery. The Associazione Italiana di Oncologia Medica (AIOM established an interdisciplinary working group with the purpose of promoting organizational improvements at the national level. A survey aimed at assessing attitudes and feelings of oncologists was considered preliminary to further initiatives.A 25-item questionnaire, sent to the mailing list of the Society, explored the following issues on the practice of breast and colorectal cancer patients' follow up: 1 organization; 2 clinical features; 3 feelings about the different meanings of follow-up.Ninety-one oncologists of 160 institutions (57% answered to the questionnaire. Although follow up is considered a distinct oncological activity in 68%, a fully shared organization between specialists is not common and communications with Primary Care Physicians are not structured in the majority of the cases. Fifty-five and 30% of the oncologists follow breast and colorectal cancer patients indefinitely. In case of discharge a survivorship care plan is delivered in only 9%. The majority of respondents do not hold a role of follow up in mortality reduction.Although survivorship care represents a significant part of the oncologists' workload, an "oncology-centered" model is largely adopted and established care pathways are still incomplete. Survivorship care needs to be put at the center of an educational policy and of a widespread organizational effort, directed at improving appropriateness and quality.

  14. Surgical nurses' attitudes towards caring for patients dying of cancer - a pilot study of an educational intervention on existential issues.

    Science.gov (United States)

    Udo, C; Melin-Johansson, C; Henoch, I; Axelsson, B; Danielson, E

    2014-07-01

    This is a randomised controlled pilot study using a mixed methods design. The overall aim was to test an educational intervention on existential issues and to describe surgical nurses' perceived attitudes towards caring for patients dying of cancer. Specific aims were to examine whether the educational intervention consisting of lectures and reflective discussions, affects nurses' perceived confidence in communication and to explore nurses' experiences and reflections on existential issues after participating in the intervention. Forty-two nurses from three surgical wards at one hospital were randomly assigned to an intervention or control group. Nurses in both groups completed a questionnaire at equivalent time intervals: at baseline before the educational intervention, directly after the intervention, and 3 and 6 months later. Eleven face-to-face interviews were conducted with nurses directly after the intervention and 6 months later. Significant short-term and long-term changes were reported. Main results concerned the significant long-term effects regarding nurses' increased confidence and decreased powerlessness in communication, and their increased feelings of value when caring for a dying patient. In addition, nurses described enhanced awareness and increased reflection. Results indicate that an understanding of the patient's situation, derived from enhanced awareness and increased reflection, precedes changes in attitudes towards communication. © 2014 John Wiley & Sons Ltd.

  15. Fine-grained parallelization of fitness functions in bioinformatics optimization problems: gene selection for cancer classification and biclustering of gene expression data.

    Science.gov (United States)

    Gomez-Pulido, Juan A; Cerrada-Barrios, Jose L; Trinidad-Amado, Sebastian; Lanza-Gutierrez, Jose M; Fernandez-Diaz, Ramon A; Crawford, Broderick; Soto, Ricardo

    2016-08-31

    Metaheuristics are widely used to solve large combinatorial optimization problems in bioinformatics because of the huge set of possible solutions. Two representative problems are gene selection for cancer classification and biclustering of gene expression data. In most cases, these metaheuristics, as well as other non-linear techniques, apply a fitness function to each possible solution with a size-limited population, and that step involves higher latencies than other parts of the algorithms, which is the reason why the execution time of the applications will mainly depend on the execution time of the fitness function. In addition, it is usual to find floating-point arithmetic formulations for the fitness functions. This way, a careful parallelization of these functions using the reconfigurable hardware technology will accelerate the computation, specially if they are applied in parallel to several solutions of the population. A fine-grained parallelization of two floating-point fitness functions of different complexities and features involved in biclustering of gene expression data and gene selection for cancer classification allowed for obtaining higher speedups and power-reduced computation with regard to usual microprocessors. The results show better performances using reconfigurable hardware technology instead of usual microprocessors, in computing time and power consumption terms, not only because of the parallelization of the arithmetic operations, but also thanks to the concurrent fitness evaluation for several individuals of the population in the metaheuristic. This is a good basis for building accelerated and low-energy solutions for intensive computing scenarios.

  16. [Non-muscle invasive bladder cancer : Current aspects of diagnostics, local therapy options and the update of the 2016 WHO classification].

    Science.gov (United States)

    Karl, A; Grimm, T; Jokisch, F; Gaisa, N T; Stief, C G

    2016-09-01

    Urothelial carcinoma of the bladder is known as one of most common malignant tumors in the urogenital tract. Non-muscle invasive bladder cancer (NMIBC) in particular has a high recurrence rate and results in correspondingly high costs for the public health system. To improve the recurrence rate and the prognosis of NMIBC the diagnosis, resection technique, adjuvant instillation therapy and exact histopathological classification of tumor lesions are indispensable. This article gives an overview on the current developments in this field. The current European Association of Urology (EAU) guidelines and the preliminary version of the German S3 guidelines on bladder cancer list photodynamic diagnosis (PDD) and narrow band imaging (NBI) as diagnostic procedures for tumors of the bladder. The trend for resection of bladder tumors is towards the use of en bloc resection using various techniques. Furthermore, an update of the WHO classification aims at a better identification and prognosis of the different risk groups of NMIBC. The treatment of NMIBC can only be improved by the combination of optimized diagnosis, precise tumor resection, improved adjuvant intravesical therapy and correct histopathological evaluation of tumors.

  17. Shyness and openness--common ground for dialogue between health personnel and women about sexual and intimate issues after gynecological cancer.

    Science.gov (United States)

    Sekse, Ragnhild J T; Råheim, Målfrid; Gjengedal, Eva

    2015-01-01

    In this article we explore shyness and openness related to sexuality and intimacy in long-term female survivors of gynecological cancer, and how these women experienced dialogue with health personnel on these issues. Further analysis on two core themes, based on empirical data presented elsewhere, inspired continued theoretical and philosophical thinking drawing on Løgstrup's expressions of life and unified opposites. The findings show that gynecological cancer survivors and health personnel share common ground as human beings because shyness and openness are basic human phenomena. Health personnel's own movement between these phenomena may represent a resource because it can help women to handle sexual and intimacy challenges following gynecological cancer.

  18. Static micro-array isolation, dynamic time series classification, capture and enumeration of spiked breast cancer cells in blood: the nanotube-CTC chip

    Science.gov (United States)

    Khosravi, Farhad; Trainor, Patrick J.; Lambert, Christopher; Kloecker, Goetz; Wickstrom, Eric; Rai, Shesh N.; Panchapakesan, Balaji

    2016-11-01

    We demonstrate the rapid and label-free capture of breast cancer cells spiked in blood using nanotube-antibody micro-arrays. 76-element single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (anti-EpCAM), Anti-human epithelial growth factor receptor 2 (anti-Her2) and non-specific IgG antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester. Following device functionalization, blood spiked with SKBR3, MCF7 and MCF10A cells (100/1000 cells per 5 μl per device, 170 elements totaling 0.85 ml of whole blood) were adsorbed on to the nanotube device arrays. Electrical signatures were recorded from each device to screen the samples for differences in interaction (specific or non-specific) between samples and devices. A zone classification scheme enabled the classification of all 170 elements in a single map. A kernel-based statistical classifier for the ‘liquid biopsy’ was developed to create a predictive model based on dynamic time warping series to classify device electrical signals that corresponded to plain blood (control) or SKBR3 spiked blood (case) on anti-Her2 functionalized devices with ˜90% sensitivity, and 90% specificity in capture of 1000 SKBR3 breast cancer cells in blood using anti-Her2 functionalized devices. Screened devices that gave positive electrical signatures were confirmed using optical/confocal microscopy to hold spiked cancer cells. Confocal microscopic analysis of devices that were classified to hold spiked blood based on their electrical signatures confirmed the presence of cancer cells through staining for DAPI (nuclei), cytokeratin (cancer cells) and CD45 (hematologic cells) with single cell sensitivity. We report 55%-100% cancer cell capture yield depending on the active device area for blood adsorption with mean of 62% (˜12 500 captured off 20 000 spiked cells in 0.1 ml

  19. CLASSIFICATION OF SEVERAL SKIN CANCER TYPES BASED ON AUTOFLUORESCENCE INTENSITY OF VISIBLE LIGHT TO NEAR INFRARED RATIO

    Directory of Open Access Journals (Sweden)

    Aryo Tedjo

    2009-12-01

    Full Text Available Skin cancer is a malignant growth on the skin caused by many factors. The most common skin cancers are Basal Cell Cancer (BCC and Squamous Cell Cancer (SCC. This research uses a discriminant analysis to classify some tissues of skin cancer based on criterion number of independent variables. An independent variable is variation of excitation light sources (LED lamp, filters, and sensors to measure Autofluorescence Intensity (IAF of visible light to near infrared (VIS/NIR ratio of paraffin embedded tissue biopsy from BCC, SCC, and Lipoma. From the result of discriminant analysis, it is known that the discriminant function is determined by 4 (four independent variables i.e., Blue LED-Red Filter, Blue LED-Yellow Filter, UV LED-Blue Filter, and UV LED-Yellow Filter. The accuracy of discriminant in classifying the analysis of three skin cancer tissues is 100 %.

  20. Analysis of classifiers performance for classification of potential microcalcification

    Science.gov (United States)

    M. N., Arun K.; Sheshadri, H. S.

    2013-07-01

    Breast cancer is a significant public health problem in the world. According to the literature early detection improve breast cancer prognosis. Mammography is a screening tool used for early detection of breast cancer. About 10-30% cases are missed during the routine check as it is difficult for the radiologists to make accurate analysis due to large amount of data. The Microcalcifications (MCs) are considered to be important signs of breast cancer. It has been reported in literature that 30% - 50% of breast cancer detected radio graphically show MCs on mammograms. Histologic examinations report 62% to 79% of breast carcinomas reveals MCs. MC are tiny, vary in size, shape, and distribution, and MC may be closely connected to surrounding tissues. There is a major challenge using the traditional classifiers in the classification of individual potential MCs as the processing of mammograms in appropriate stage generates data sets with an unequal amount of information for both classes (i.e., MC, and Not-MC). Most of the existing state-of-the-art classification approaches are well developed by assuming the underlying training set is evenly distributed. However, they are faced with a severe bias problem when the training set is highly imbalanced in distribution. This paper addresses this issue by using classifiers which handle the imbalanced data sets. In this paper, we also compare the performance of classifiers which are used in the classification of potential MC.

  1. Introduction to Special Issue: A Review of the International Classification of Functioning, Disability and Health and Physical Therapy over the Years.

    Science.gov (United States)

    Escorpizo, Reuben; Bemis-Dougherty, Anita

    2015-12-01

    The International Classification of Functioning, Disability and Health (ICF) of the World Health Organization was developed as a common framework to understand health and to describe the impact of health condition on functioning. The purpose of this paper is to summarize the literature on the use of the ICF in physical therapy practice and research. We performed a scoping-narrative review and searched for relevant English language articles from 2001 to 2012 in multiple databases that included MEDLINE, PsycINFO, PubMed and Physiotherapy Evidence Database. Our keywords for the search consisted of ['physical therapy' OR 'physiotherapy'] AND ['ICF']. All types of articles were considered. We found 268 articles; out of which, 79 were reviewed. The years with most publications were 2011 (n = 16), 2008 (n = 15) and 2010 and 2012 (both with n = 13). Publications mostly came from the United States with 27% of the articles. The journal Physical Therapy leads with almost a third of ICF-related physical therapy publications. The ICF has been mostly used in studies of musculoskeletal and neuromuscular conditions. We found a wide array of application of the ICF in research, clinical practice and teaching (classroom and clinical education). Emerging topics included using the ICF in resource allocation and prevention and wellness. The use of the ICF in physical therapy practice and research is promising and continues to evolve. With recent developments in ICF-based measurement and integration in assessment tools for use in the clinics, research and teaching, the need to show the added value of using the ICF in practice and research remains. Copyright © 2013 John Wiley & Sons, Ltd.

  2. Body image issues after bilateral prophylactic mastectomy with breast reconstruction in healthy women at risk for hereditary breast cancer.

    Science.gov (United States)

    Gopie, Jessica P; Mureau, Marc A M; Seynaeve, Caroline; Ter Kuile, Moniek M; Menke-Pluymers, Marian B E; Timman, Reinier; Tibben, Aad

    2013-09-01

    The outcome of bilateral prophylactic mastectomy with breast reconstruction (BPM-IBR) in healthy BRCA1/2 mutation carriers can be potentially burdensome for body image and the intimate relationship. Therefore, in the current analysis the impact on body image, sexual and partner relationship satisfaction was prospectively investigated in women opting for BPM-IBR as well as cancer distress and general quality of life. Healthy women undergoing BPM-IBR completed questionnaires preoperatively (T0, n = 48), at 6 months (T1, n = 44) and after finishing breast reconstruction (median 21 months, range 12-35) (T2, n = 36). With multi-level regression analyses the course of outcome variables was investigated and a statistically significant change in body image and/or sexual and partner relationship satisfaction was predicted by baseline covariates. Body image significantly decreased at T1. At T2 sexual relationship satisfaction and body image tended to be lower compared to baseline. The overall partner relationship satisfaction did not significantly change. At T2, 37 % of the women reported that their breasts felt unpleasantly, 29 % was not satisfied with their breast appearance and 21 % felt embarrassed for their naked body. Most body image issues remained unchanged in 30 % of the women. A negative body image was predicted by high preoperative cancer distress. BPM-IBR was associated with adverse impact on body image in a substantial subgroup, but satisfaction with the overall sexual and partner relationship did not significantly change in time. The psychosocial impact of BPM-IBR in unaffected women should not be underestimated. Psychological support should ideally be integrated both before and after BPM-IBR.

  3. An Efficient Ensemble Learning Method for Gene Microarray Classification

    Directory of Open Access Journals (Sweden)

    Alireza Osareh

    2013-01-01

    Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

  4. An efficient ensemble learning method for gene microarray classification.

    Science.gov (United States)

    Osareh, Alireza; Shadgar, Bita

    2013-01-01

    The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

  5. Profiling of microRNAs in tumor interstitial fluid of breast tumors - a novel resource to identify biomarkers for prognostic classification and detection of cancer.

    Science.gov (United States)

    Halvorsen, Ann Rita; Helland, Åslaug; Gromov, Pavel; Wielenga, Vera Timmermans; Talman, Maj-Lis Møller; Brunner, Nils; Sandhu, Vandana; Børresen-Dale, Anne-Lise; Gromova, Irina; Haakensen, Vilde D

    2017-02-01

    It has been hypothesized based on accumulated data that a class of small noncoding RNAs, termed microRNAs, are key factors in intercellular communication. Here, microRNAs present in interstitial breast tumor fluids have been analyzed to identify relevant markers for a diagnosis of breast cancer and to elucidate the cross-talk that exists among cells in a tumor microenvironment. Matched tumor interstitial fluid samples (TIF, n = 60), normal interstitial fluid samples (NIF, n = 51), corresponding tumor tissue specimens (n = 54), and serum samples (n = 27) were collected from patients with breast cancer, and detectable microRNAs were analyzed and compared. In addition, serum data from 32 patients with breast cancer and 22 healthy controls were obtained for a validation study. To identify potential serum biomarkers of breast cancer, first the microRNA profiles of TIF and NIF samples were compared. A total of 266 microRNAs were present at higher level in the TIF samples as compared to normal counterparts. Sixty-one of these microRNAs were present in > 75% of the serum samples and were subsequently tested in a validation set. Seven of the 61 microRNAs were associated with poor survival, while 23 were associated with the presence of immune cells and adipocytes. To our knowledge, these data demonstrate for the first time that profiling of microRNAs in TIF can identify novel biomarkers for the prognostic classification and detection of breast cancer. In addition, the present findings demonstrate that microRNAs may represent the cross-talk that occurs between tumor cells and their surrounding stroma. © 2016 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

  6. A prospective study of duration of smoking cessation and colorectal cancer risk by epigenetics-related tumor classification.

    Science.gov (United States)

    Nishihara, Reiko; Morikawa, Teppei; Kuchiba, Aya; Lochhead, Paul; Yamauchi, Mai; Liao, Xiaoyun; Imamura, Yu; Nosho, Katsuhiko; Shima, Kaori; Kawachi, Ichiro; Qian, Zhi Rong; Fuchs, Charles S; Chan, Andrew T; Giovannucci, Edward; Ogino, Shuji

    2013-07-01

    The effect of duration of cigarette smoking cessation on colorectal cancer risk by molecular subtypes remains unclear. Using duplication-method Cox proportional-hazards regression analyses, we examined associations between duration of smoking cessation and colorectal cancer risk according to status of CpG island methylator phenotype (CIMP), microsatellite instability, v-raf murine sarcoma viral oncogene homolog B1 (BRAF) mutation, or DNA methyltransferase-3B (DNMT3B) expression. Follow-up of 134,204 individuals in 2 US nationwide prospective cohorts (Nurses' Health Study (1980-2008) and Health Professionals Follow-up Study (1986-2008)) resulted in 1,260 incident rectal and colon cancers with available molecular data. Compared with current smoking, 10-19, 20-39, and ≥40 years of smoking cessation were associated with a lower risk of CIMP-high colorectal cancer, with multivariate hazard ratios (95% confidence intervals) of 0.53 (0.29, 0.95), 0.52 (0.32, 0.85), and 0.50 (0.27, 0.94), respectively (Ptrend = 0.001), but not with the risk of CIMP-low/CIMP-negative cancer (Ptrend = 0.25) (Pheterogeneity = 0.02, between CIMP-high and CIMP-low/CIMP-negative cancer risks). Differential associations between smoking cessation and cancer risks by microsatellite instability (Pheterogeneity = 0.02), DNMT3B expression (Pheterogeneity = 0.03), and BRAF (Pheterogeneity = 0.10) status appeared to be driven by the associations of CIMP-high cancer with microsatellite instability-high, DNMT3B-positive, and BRAF-mutated cancers. These molecular pathological epidemiology data suggest a protective effect of smoking cessation on a DNA methylation-related carcinogenesis pathway leading to CIMP-high colorectal cancer.

  7. Applicability of the Nursing Outcomes Classification (NOC) to the evaluation of cancer patients with acute or chronic pain in palliative care.

    Science.gov (United States)

    Mello, Bruna S; Massutti, Tânia M; Longaray, Vanessa K; Trevisan, Daniela F; Lucena, Amália de Fátima

    2016-02-01

    The aim of this study was to verify the clinical applicability of the Nursing Outcomes Classification (NOC) to the evaluation of cancer patients with a nursing diagnosis of acute or chronic pain in a palliative care unit. A prospective longitudinal study performed on a sample of 13 adult cancer patients in a palliative care unit. Patients were followed for at least 4 days. Data were collected with an instrument containing eight nursing outcomes and nineteen NOC indicators. Statistical analysis was performed using generalized estimating equation models. The following outcome and indicator scores changed significantly over the course of the study: reported pain and length of pain episodes in the pain level outcome; social relationships in the personal well-being outcome; respirator rate in the vital signs outcome; and describes causal factors in the pain control outcome. The NOC outcomes and indicators included in this study were able to successfully evaluate the clinical evolution of cancer patients in palliative care. These scores proved to be applicable for use in palliative nursing care. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Actualización de la estadificación de cáncer de cuello uterino Classification and staging of cervical cancer: an update

    Directory of Open Access Journals (Sweden)

    Claudia Álvarez

    2012-06-01

    Full Text Available A pesar de los avances en la detección y prevención del cáncer de cuello uterino, éste continúa siendo una gran amenaza para la salud de las mujeres a nivel mundial. Una correcta evaluación de los factores pronósticos es crucial para la elección y planificación de un tratamiento adecuado. La estadificación del cáncer de cuello uterino ha sufrido modificaciones en la 7° edición del TNM, reflejando la nueva clasificación adoptada por la Federación Internacional de Ginecología y Obstetricia (FIGO. En este artículo presentamos el sistema actualizado y unificado de estadificación para cáncer de cuello uterino.Despite advances in screening and prevention, cervical cancer remains a major threat to women's health worldwide. A correct evaluation of prognostic factors is crucial for choosing and planning the most appropriate treatment. Cervical cancer staging has undergone modifications in the 7th edition of TNM, reflecting the new classification adopted by the International Federation of Gynecology and Obstetrics (FIGO. In this paper we present the updated and consolidated system of cervical cancer staging.

  9. Equivalent Diagnostic Classification Models

    Science.gov (United States)

    Maris, Gunter; Bechger, Timo

    2009-01-01

    Rupp and Templin (2008) do a good job at describing the ever expanding landscape of Diagnostic Classification Models (DCM). In many ways, their review article clearly points to some of the questions that need to be answered before DCMs can become part of the psychometric practitioners toolkit. Apart from the issues mentioned in this article that…

  10. Noninvasive diagnosis of hepatocellular carcinoma: Elaboration on Korean liver cancer study group-National Cancer Center Korea Practice Guidelines compared with other guidelines and remaining issues

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Jeong Hee; Lee, Jeong Min [Dept. of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Park, Joong Won [Center for Liver Cancer, National Cancer Center, Goyang (Korea, Republic of)

    2016-02-15

    Hepatocellular carcinoma (HCC) can be diagnosed based on characteristic findings of arterial-phase enhancement and portal/delayed 'washout' in cirrhotic patients. Several countries and major academic societies have proposed varying specific diagnostic criteria for HCC, largely reflecting the variable HCC prevalence in different regions and ethnic groups, as well as different practice patterns. In 2014, a new version of Korean practice guidelines for management of HCC was released by the Korean Liver Cancer Study Group (KLCSG) and the National Cancer Center (NCC). According to the KLCSG-NCC Korea practice guidelines, if the typical hallmark of HCC (i.e., hypervascularity in the arterial phase with washout in the portal or 3 min-delayed phases) is identified in a nodule ≥ 1 cm in diameter on either dynamic CT, dynamic MRI, or MRI using hepatocyte-specific contrast agent in high-risk groups, a diagnosis of HCC is established. In addition, the KLCSG-NCC Korea practice guidelines provide criteria to diagnose HCC for subcentimeter hepatic nodules according to imaging findings and tumor marker, which has not been addressed in other guidelines such as Association for the Study of Liver Diseases and European Association for the Study of the Liver. In this review, we briefly review the new HCC diagnostic criteria endorsed by the 2014 KLCSG-NCC Korea practice guidelines, in comparison with other recent guidelines; we furthermore address several remaining issues in noninvasive diagnosis of HCC, including prerequisite of sonographic demonstration of nodules, discrepancy between transitional phase and delayed phase, and implementation of ancillary features for HCC diagnosis.

  11. Noninvasive Diagnosis of Hepatocellular Carcinoma: Elaboration on Korean Liver Cancer Study Group-National Cancer Center Korea Practice Guidelines Compared with Other Guidelines and Remaining Issues

    Science.gov (United States)

    Yoon, Jeong Hee; Park, Joong-Won

    2016-01-01

    Hepatocellular carcinoma (HCC) can be diagnosed based on characteristic findings of arterial-phase enhancement and portal/delayed "washout" in cirrhotic patients. Several countries and major academic societies have proposed varying specific diagnostic criteria for HCC, largely reflecting the variable HCC prevalence in different regions and ethnic groups, as well as different practice patterns. In 2014, a new version of Korean practice guidelines for management of HCC was released by the Korean Liver Cancer Study Group (KLCSG) and the National Cancer Center (NCC). According to the KLCSG-NCC Korea practice guidelines, if the typical hallmark of HCC (i.e., hypervascularity in the arterial phase with washout in the portal or 3 min-delayed phases) is identified in a nodule ≥ 1 cm in diameter on either dynamic CT, dynamic MRI, or MRI using hepatocyte-specific contrast agent in high-risk groups, a diagnosis of HCC is established. In addition, the KLCSG-NCC Korea practice guidelines provide criteria to diagnose HCC for subcentimeter hepatic nodules according to imaging findings and tumor marker, which has not been addressed in other guidelines such as Association for the Study of Liver Diseases and European Association for the Study of the Liver. In this review, we briefly review the new HCC diagnostic criteria endorsed by the 2014 KLCSG-NCC Korea practice guidelines, in comparison with other recent guidelines; we furthermore address several remaining issues in noninvasive diagnosis of HCC, including prerequisite of sonographic demonstration of nodules, discrepancy between transitional phase and delayed phase, and implementation of ancillary features for HCC diagnosis. PMID:26798212

  12. Optimized color decomposition of localized whole slide images and convolutional neural network for intermediate prostate cancer classification

    Science.gov (United States)

    Zhou, Naiyun; Gao, Yi

    2017-03-01

    This paper presents a fully automatic approach to grade intermediate prostate malignancy with hematoxylin and eosin-stained whole slide images. Deep learning architectures such as convolutional neural networks have been utilized in the domain of histopathology for automated carcinoma detection and classification. However, few work show its power in discriminating intermediate Gleason patterns, due to sporadic distribution of prostate glands on stained surgical section samples. We propose optimized hematoxylin decomposition on localized images, followed by convolutional neural network to classify Gleason patterns 3+4 and 4+3 without handcrafted features or gland segmentation. Crucial glands morphology and structural relationship of nuclei are extracted twice in different color space by the multi-scale strategy to mimic pathologists' visual examination. Our novel classification scheme evaluated on 169 whole slide images yielded a 70.41% accuracy and corresponding area under the receiver operating characteristic curve of 0.7247.

  13. A neglected issue on sexual well-being following breast cancer diagnosis and treatment among Chinese women

    National Research Council Canada - National Science Library

    Wang, Fengliang; Chen, Fei; Huo, Xiqian; Xu, Ruobing; Wu, Liang; Wang, Jianming; Lu, Cheng

    2013-01-01

    .... The objectives of the present study were to evaluate changes to sexual well-being following breast cancer, to expand upon the existing body of knowledge pertaining to breast cancer and sexuality...

  14. Diagnosis of lung cancer in small biopsies and cytology: implications of the 2011 International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification.

    Science.gov (United States)

    Travis, William D; Brambilla, Elisabeth; Noguchi, Masayuki; Nicholson, Andrew G; Geisinger, Kim; Yatabe, Yasushi; Ishikawa, Yuichi; Wistuba, Ignacio; Flieder, Douglas B; Franklin, Wilbur; Gazdar, Adi; Hasleton, Philip S; Henderson, Douglas W; Kerr, Keith M; Petersen, Iver; Roggli, Victor; Thunnissen, Erik; Tsao, Ming

    2013-05-01

    The new International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society lung adenocarcinoma classification provides, for the first time, standardized terminology for lung cancer diagnosis in small biopsies and cytology; this was not primarily addressed by previous World Health Organization classifications. Until recently there have been no therapeutic implications to further classification of NSCLC, so little attention has been given to the distinction of adenocarcinoma and squamous cell carcinoma in small tissue samples. This situation has changed dramatically in recent years with the discovery of several therapeutic options that are available only to patients with adenocarcinoma or NSCLC, not otherwise specified, rather than squamous cell carcinoma. This includes recommendation for use of special stains as an aid to diagnosis, particularly in the setting of poorly differentiated tumors that do not show clear differentiation by routine light microscopy. A limited diagnostic workup is recommended to preserve as much tissue for molecular testing as possible. Most tumors can be classified using a single adenocarcinoma marker (eg, thyroid transcription factor 1 or mucin) and a single squamous marker (eg, p40 or p63). Carcinomas lacking clear differentiation by morphology and special stains are classified as NSCLC, not otherwise specified. Not otherwise specified carcinomas that stain with adenocarcinoma markers are classified as NSCLC, favor adenocarcinoma, and tumors that stain only with squamous markers are classified as NSCLC, favor squamous cell carcinoma. The need for every institution to develop a multidisciplinary tissue management strategy to obtain these small specimens and process them, not only for diagnosis but also for molecular testing and evaluation of markers of resistance to therapy, is emphasized.

  15. Innovative patient-centered skills training addressing challenging issues in cancer communications: Using patient's stories that teach.

    Science.gov (United States)

    Bishop, Thomas W; Gorniewicz, James; Floyd, Michael; Tudiver, Fred; Odom, Amy; Zoppi, Kathy

    2016-05-01

    This workshop demonstrated the utility of a patient-centered web-based/digital Breaking Bad News communication training module designed to educate learners of various levels and disciplines. This training module is designed for independent, self-directed learning as well as group instruction. These interactive educational interventions are based upon video-recorded patient stories. Curriculum development was the result of an interdisciplinary, collaborative effort involving faculty from the East Tennessee State University (ETSU) Graduate Storytelling Program and the departments of Family and Internal Medicine at the James H. Quillen College of Medicine. The specific goals of the BBN training module are to assist learners in: (1) understanding a five-step patient-centered model that is based upon needs, preferences, and expectations of patients with cancer and (2) individualizing communication that is consistent with patient preferences in discussing emotions, informational detail, prognosis and timeline, and whether or not to discuss end-of-life issues. The pedagogical approach to the training module is to cycle through Emotional Engagement, Data, Modeled Practices, Adaptation Opportunities, and Feedback. The communication skills addressed are rooted in concepts found within the Reaching Common Ground communication training. A randomized control study investigating the effectiveness of the Breaking Bad News module found that medical students as well as resident physicians improved their communication skills as measured by an Objective Structured Clinical Examination. Four other similarly designed modules were also created: Living Through Treatment, Transitions: From Curable to Treatable/From Treatable to End-of-Life, Spirituality, and Family. © The Author(s) 2016.

  16. Issues and challenges with integrating patient-reported outcomes in clinical trials supported by the National Cancer Institute-sponsored clinical trials networks.

    Science.gov (United States)

    Bruner, Deborah Watkins; Bryan, Charlene J; Aaronson, Neil; Blackmore, C Craig; Brundage, Michael; Cella, David; Ganz, Patricia A; Gotay, Carolyn; Hinds, Pamela S; Kornblith, Alice B; Movsas, Benjamin; Sloan, Jeff; Wenzel, Lari; Whalen, Giles

    2007-11-10

    The objective of this report is to provide a historical overview of and the issues and challenges inherent in the incorporation of patient-reported outcomes (PROs) into multinational cancer clinical trials in the cancer cooperative groups. An online survey of 12 cancer cooperative groups from the United States, Canada, and Europe was conducted between June and August of 2006. Each of the cooperative groups designated one respondent, who was a member of one of the PRO committees within the cooperative group. There was a 100% response rate, and all of the cancer clinical trial cooperative groups reported conducting PRO research. PRO research has been conducted in the cancer cooperative groups for an average of 15 years (range, 6 to 30 years), and all groups had multidisciplinary committees focused on the design of PRO end points and the choice of appropriate PRO measures for cancer clinical trials. The cooperative groups reported that 5% to 50% of cancer treatment trials and an estimated 50% to 75% of cancer control trials contained PRO primary and secondary end points. There was considerable heterogeneity among the cooperative groups with respect to the formal and informal policies and procedures or cooperative group culture towards PROs, investigator training/mentorship, and resource availability for the measurement and conduct of PRO research within the individual cooperatives. The challenges faced by the cooperative groups to the incorporation of PROs into cancer clinical trials are varied. Some common opportunities for improvement include the adoption of standardized training/mentorship mechanisms for investigators for the conduct of PRO assessments and data collection and the development of minimal criteria for PRO measure acceptability. A positive cultural shift has occurred in most of the cooperative groups related to the incorporation of PROs in clinical trials; however, financial and other resource barriers remain and need to be addressed.

  17. Issues and Challenges With Integrating Patient-Reported Outcomes in Clinical Trials Supported by the National Cancer Institute–Sponsored Clinical Trials Networks

    Science.gov (United States)

    Bruner, Deborah Watkins; Bryan, Charlene J.; Aaronson, Neil; Blackmore, C. Craig; Brundage, Michael; Cella, David; Ganz, Patricia A.; Gotay, Carolyn; Hinds, Pamela S.; Kornblith, Alice B.; Movsas, Benjamin; Sloan, Jeff; Wenzel, Lari; Whalen, Giles

    2016-01-01

    Purpose The objective of this report is to provide a historical overview of and the issues and challenges inherent in the incorporation of patient-reported outcomes (PROs) into multinational cancer clinical trials in the cancer cooperative groups. Methods An online survey of 12 cancer cooperative groups from the United States, Canada, and Europe was conducted between June and August of 2006. Each of the cooperative groups designated one respondent, who was a member of one of the PRO committees within the cooperative group. Results There was a 100% response rate, and all of the cancer clinical trial cooperative groups reported conducting PRO research. PRO research has been conducted in the cancer cooperative groups for an average of 15 years (range, 6 to 30 years), and all groups had multidisciplinary committees focused on the design of PRO end points and the choice of appropriate PRO measures for cancer clinical trials. The cooperative groups reported that 5% to 50% of cancer treatment trials and an estimated 50% to 75% of cancer control trials contained PRO primary and secondary end points. There was considerable heterogeneity among the cooperative groups with respect to the formal and informal policies and procedures or cooperative group culture towards PROs, investigator training/mentorship, and resource availability for the measurement and conduct of PRO research within the individual cooperatives. Conclusion The challenges faced by the cooperative groups to the incorporation of PROs into cancer clinical trials are varied. Some common opportunities for improvement include the adoption of standardized training/mentorship mechanisms for investigators for the conduct of PRO assessments and data collection and the development of minimal criteria for PRO measure acceptability. A positive cultural shift has occurred in most of the cooperative groups related to the incorporation of PROs in clinical trials; however, financial and other resource barriers remain and need

  18. The classification of secondary colorectal liver cancer in human biopsy samples using angular dispersive x-ray diffraction and multivariate analysis

    Science.gov (United States)

    Theodorakou, Chrysoula; Farquharson, Michael J.

    2009-08-01

    The motivation behind this study is to assess whether angular dispersive x-ray diffraction (ADXRD) data, processed using multivariate analysis techniques, can be used for classifying secondary colorectal liver cancer tissue and normal surrounding liver tissue in human liver biopsy samples. The ADXRD profiles from a total of 60 samples of normal liver tissue and colorectal liver metastases were measured using a synchrotron radiation source. The data were analysed for 56 samples using nonlinear peak-fitting software. Four peaks were fitted to all of the ADXRD profiles, and the amplitude, area, amplitude and area ratios for three of the four peaks were calculated and used for the statistical and multivariate analysis. The statistical analysis showed that there are significant differences between all the peak-fitting parameters and ratios between the normal and the diseased tissue groups. The technique of soft independent modelling of class analogy (SIMCA) was used to classify normal liver tissue and colorectal liver metastases resulting in 67% of the normal tissue samples and 60% of the secondary colorectal liver tissue samples being classified correctly. This study has shown that the ADXRD data of normal and secondary colorectal liver cancer are statistically different and x-ray diffraction data analysed using multivariate analysis have the potential to be used as a method of tissue classification.

  19. The International Classification of Functioning (ICF) core set for breast cancer from the perspective of women with the condition.

    Science.gov (United States)

    Cooney, Marese; Galvin, Rose; Connolly, Elizabeth; Stokes, Emma

    2013-05-01

    The ICF Core Set for breast cancer was generated by international experts for women who have had surgery and radiation but it has not yet been validated. The objective of the study was to validate the ICF Core Set from the perspective of women with breast cancer. A qualitative focus group methodology was used. The sessions were transcribed verbatim. Meaning units were identified by two independent researchers. The agreed list was subsequently linked to ICF categories by two independent researchers according to pre-defined linking rules. Data saturation determined the number of focus groups conducted. Quality of the data analyses was assured by multiple coding and peer review. Thirty-four women participated in seven focus groups. A total of 1621 meaning units were identified which were linked to 74 of the existing 80 Core Set categories. Additional ICF categories not currently included in the Core Set were identified by the women. The validity of the Core Set was largely supported. However, some categories currently not covered by the ICF Core Set for Breast Cancer will need to be considered for inclusion if the Core Set is to reflect all women who have had treatment for breast cancer

  20. Study protocol for Young & Strong: a cluster randomized design to increase attention to unique issues faced by young women with newly diagnosed breast cancer.

    Science.gov (United States)

    Greaney, Mary L; Sprunck-Harrild, Kim; Ruddy, Kathryn J; Ligibel, Jennifer; Barry, William T; Baker, Emily; Meyer, Meghan; Emmons, Karen M; Partridge, Ann H

    2015-01-31

    Each year, approximately 11% of women diagnosed with breast cancer in the United States are 45 years of age or younger. These women have concerns specific to or accentuated by their age, including fertility-related concerns, and have higher rates of psychosocial distress than women diagnosed at older ages. Current guidelines recommend that fertility risks be considered early in all treatment plans; however, the extant research indicates that attention to fertility by the healthcare team is limited. Importantly, attention to fertility may be a proxy for whether or not other important issues warranting attention in younger women with breast cancer are addressed, including genetic risks, psychosocial distress, sexual functioning, and body image concerns. The Young & Strong study tests the efficacy of an intervention designed for young women recently diagnosed with breast cancer and their oncologists with the intention to: 1) increase attention to fertility as an important surrogate for other issues facing young women, 2) educate and support young women and their providers, and 3) reduce psychosocial distress among young women with breast cancer. The study employs a cluster randomized design including 14 academic institutions and 40 community sites across the U.S. assigned to either the study intervention arm or contact-time comparison intervention arm. Academic institutions enroll up to 15 patients per site while community sites enroll up to 10 patients. Patient eligibility requirements include: an initial diagnosis of stage I-III invasive breast cancer within three months prior, without a known recurrence or metastatic breast cancer; 18-45 years of age at diagnosis; ability to read and write in English. The primary outcome is oncologists' attention to fertility concerns as determined by medical record review. Secondary outcomes include differences in patient satisfaction with care and psychosocial distress between the two study arms. Study findings will provide

  1. Communication in cancer care: Psycho social, interactional, and cultural issues. A general overview and the example of India

    Directory of Open Access Journals (Sweden)

    SANTOSH K CHATURVEDI

    2014-11-01

    Full Text Available Communication is a core aspect of psycho-oncology care. This article examines key psychosocial, cultural, and technological factors that affect this communication. Drawing from advances in clinical work and accumulating bodies of empirical evidence, the authors identify determining factors for high quality, efficient, and sensitive communication and support for those affected by cancer. Cancer care in India is highlighted as a salient example. Cultural factors affecting cancer communication in India include beliefs about health and illness, societal values, integration of spiritual care, family roles, and expectations concerning disclosure of cancer information, and rituals around death and dying. The rapidly emerging area of e-health significantly impacts cancer communication and support globally. In view of current globalization, understanding these multidimensional psychosocial, and cultural factors that shape communication are essential for providing comprehensive, appropriate and sensitive cancer care.

  2. Communication in cancer care: Psycho social, interactional, and cultural issues. A general overview and the example of India

    OpenAIRE

    SANTOSH K CHATURVEDI; Fay J Strohschein; Fay J Strohschein; Gayatri eSaraf; Carmen G Loiselle; Carmen G Loiselle

    2014-01-01

    Communication is a core aspect of psycho-oncology care. This article examines key psychosocial, cultural, and technological factors that affect this communication. Drawing from advances in clinical work and accumulating bodies of empirical evidence, the authors identify determining factors for high quality, efficient, and sensitive communication and support for those affected by cancer. Cancer care in India is highlighted as a salient example. Cultural factors affecting cancer communication...

  3. MALDI Imaging Mass Spectrometry (MALDI-IMS―Application of Spatial Proteomics for Ovarian Cancer Classification and Diagnosis

    Directory of Open Access Journals (Sweden)

    Johan O. R. Gustafsson

    2011-01-01

    Full Text Available MALDI imaging mass spectrometry (MALDI-IMS allows acquisition of mass data for metabolites, lipids, peptides and proteins directly from tissue sections. IMS is typically performed either as a multiple spot profiling experiment to generate tissue specific mass profiles, or a high resolution imaging experiment where relative spatial abundance for potentially hundreds of analytes across virtually any tissue section can be measured. Crucially, imaging can be achieved without prior knowledge of tissue composition and without the use of antibodies. In effect MALDI-IMS allows generation of molecular data which complement and expand upon the information provided by histology including immuno-histochemistry, making its application valuable to both cancer biomarker research and diagnostics. The current state of MALDI-IMS, key biological applications to ovarian cancer research and practical considerations for analysis of peptides and proteins on ovarian tissue are presented in this review.

  4. The newly proposed clinical and post-neoadjuvant treatment staging classifications for gastric adenocarcinoma for the American Joint Committee on Cancer (AJCC) staging.

    Science.gov (United States)

    In, Haejin; Ravetch, Ethan; Langdon-Embry, Marisa; Palis, Bryan; Ajani, Jaffer A; Hofstetter, Wayne L; Kelsen, David P; Sano, Takeshi

    2018-01-01

    New stage grouping classifications for clinical (cStage) and post-neoadjuvant treatment (ypStage) stage for gastric adenocarcinoma have been proposed for the eighth edition of the AJCC manual. This article summarizes the analysis for these stages. Gastric adenocarcinoma patients diagnosed in 2004-2009 were identified from the National Cancer Database (NCDB). The cStage cohort included both surgical and nonsurgical cases, and the ypStage cohort included only patients who had chemotherapy or radiation therapy before surgery. Survival differences between the stage groups were determined by the log-rank test and prognostic accuracy was assessed by concordance index. Analysis was performed using SAS 9.4 (SAS, Cary, NC, USA). Five strata for cStage and four strata for ypStage were developed. The 5-year survival rates for cStages were 56.77%, 47.39%, 33.1%, 25.9%, and 5.0% for stages I, IIa, IIb, III, and IV, respectively, and the rates for ypStage were 74.2%, 46.3%, 19.2%, and 11.6% for stages I, II, III, and IV, respectively. The log-rank test showed that survival differences were well stratified and stage groupings were ordered and distinct (p < 0.0001). The proposed cStage and ypStage classification was sensitive and specific and had high prognostic accuracy (cStage: c index = 0.81, 95% CI, 0.79-0.83; ypStage: c index = 0.80, 95% CI, 0.73-0.87). The proposed eighth edition establishes two new staging schemata that provide essential prognostic data for patients before treatment and for patients who have undergone surgery following neoadjuvant therapy. These additions are a significant advance to the AJCC staging manual and will provide critical guidance to clinicians in making informed decisions throughout the treatment course.

  5. Body issues, sexual satisfaction, and relationship status satisfaction in long-term childhood cancer survivors and healthy controls

    NARCIS (Netherlands)

    Lehmann, Vicky; Hagedoorn, Mariet; Gerhardt, Cynthia A.; Fults, Marci; Olshefski, Randal S.; Sanderman, Robbert; Tuinman, Marrit A.

    ObjectiveResearch on body image and sexual satisfaction after adult onset cancer has shown significant and lasting impairments regarding survivors' sexuality and romantic relationships. However, knowledge about these topics and their associations in adult survivors of childhood cancer is largely

  6. ISSVA classification.

    Science.gov (United States)

    Dasgupta, Roshni; Fishman, Steven J

    2014-08-01

    Mulliken and Glowacki, in 1982 created a classification system of vascular anomalies which divided vascular anomalies into tumors and malformations which provided the framework for great advances in the management of these patients. This classification system was recently expanded at the 2014 ISSVA workshop in Melbourne. This revision again provides much greater detail including newly named anomalies and identified genes to account for recent advances in knowledge and clinical associations. Copyright © 2014. Published by Elsevier Inc.

  7. The comparison of the scope of the content and classification methods on topographical maps of Polish territory annexed by Russia issued at the turn of 19th and 20th century

    Directory of Open Access Journals (Sweden)

    Panecki Tomasz

    2015-03-01

    Full Text Available The aim of the article was a comparison of the content’s scope, classification and presentation methods on topographical maps issued at the turn of 19th and 20th century covering the territory of former Russian partition. Three of such maps were chosen for the analysis, namely: Russian (scale 1:84,000, Austrian (scale 1:75,000 and German (scale 1:100,000. As a starting point of the study served an attempt at reconstruction of map legends, as, a coherent symbology key (i.e. map legend can be found neither for Russian nor German map. It was conducted by employing the symbology keys prepared in the Interwar Period, as for the Russian map there was no legend enclosed, while in the case of German the legend enclosed featured only the road network. Apart from the legends, an analysis of the map sheets covering four areas was conducted. Those areas were, as follow: Brest, Dęblin, Pinsk and Pułtusk vicinites. The next stage was to elaborate a legend comparison with summary in the form of a table for particular thematic layers: settlement and built-up area, transport network, sacral buildings facilities and other buildings, land cover, hydrography, relief, and borders. An assumption was made that despite the apparent similarity of the scales (1:75,000, 1:84,000, 1:100,000 and source materials the maps analysed are distinct in terms of presentation of the geohistorical landscape. The settlements on the Russian map were illustrated in a schematic manner, while the other maps approached the subject more meticulously. The discrepancies involve also such areas as: road network, land cover, and waters, which were categorised along different sets of criterion. It happened that some categories present on the Russian map were absent from the Austrian and German. It involved such objects as: fascine roads, wooden churches or radiostations. Those differences stem from not only the “military mode” of elaboration of the German and Austrian map, but also

  8. Profiling cancer

    DEFF Research Database (Denmark)

    Ciro, Marco; Bracken, Adrian P; Helin, Kristian

    2003-01-01

    In the past couple of years, several very exciting studies have demonstrated the enormous power of gene-expression profiling for cancer classification and prediction of patient survival. In addition to promising a more accurate classification of cancer and therefore better treatment of patients......, gene-expression profiling can result in the identification of novel potential targets for cancer therapy and a better understanding of the molecular mechanisms leading to cancer....

  9. Cancer

    Science.gov (United States)

    ... Prostate cancer Lung cancer Colorectal cancer In US women, other than skin cancer the three most common cancers are: Breast cancer Lung cancer Colorectal cancer Some cancers are more common in certain parts of the world. For example, in Japan, there are many cases of stomach cancer . But ...

  10. EBM-based Clinical Guidelines for Pancreatic Cancer (2013) issued by the Japan Pancreas Society: a synopsis.

    Science.gov (United States)

    Yamaguchi, Koji; Okusaka, Takuji; Shimizu, Kyoko; Furuse, Junji; Ito, Yoshinori; Hanada, Keiji; Shimosegawa, Tooru

    2014-10-01

    Clinical practice guidelines for pancreatic cancer based on evidence-based medicine (2006) were published by the Japan Pancreas Society (Committee for revision of clinical guidelines for pancreatic cancer) in March 2009 in Japanese, revised to Clinical Practice Guidelines for Pancreatic Cancer based on evidence-based medicine (2009) in July 2009 in Japanese and further revised to Clinical Practice Guidelines for Pancreatic Cancer (2013) in October 2013 in Japanese. These guidelines were established according to evidence-based medicine. A total of 629 papers were collected from among 4612 reports concerning pancreatic cancer listed in PubMed and Igakuchuo Zasshi between May 2007 and January 2011. This new set of guidelines was written by members of the Committee for the Revision of Clinical Practice Guidelines for Pancreatic Cancer in the Japan Pancreas Society. The guidelines provide an algorithm for the diagnosis (Fig. 1) and treatment (Fig. 2) of pancreatic cancer and address six subjects (Diagnosis, Surgery, Adjuvant therapy, Radiation therapy, Chemotherapy and stent therapy), with 35 clinical questions and 57 recommendations. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  11. Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2016-01-01

    Full Text Available Among non-small cell lung cancer (NSCLC, adenocarcinoma (AC, and squamous cell carcinoma (SCC are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR, can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.

  12. Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples.

    Science.gov (United States)

    Fekete, Tibor; Rásó, Erzsébet; Pete, Imre; Tegze, Bálint; Liko, István; Munkácsy, Gyöngyi; Sipos, Norbert; Rigó, János; Györffy, Balázs

    2012-07-01

    Transcriptomic analysis of global gene expression in ovarian carcinoma can identify dysregulated genes capable to serve as molecular markers for histology subtypes and survival. The aim of our study was to validate previous candidate signatures in an independent setting and to identify single genes capable to serve as biomarkers for ovarian cancer progression. As several datasets are available in the GEO today, we were able to perform a true meta-analysis. First, 829 samples (11 datasets) were downloaded, and the predictive power of 16 previously published gene sets was assessed. Of these, eight were capable to discriminate histology subtypes, and none was capable to predict survival. To overcome the differences in previous studies, we used the 829 samples to identify new predictors. Then, we collected 64 ovarian cancer samples (median relapse-free survival 24.5 months) and performed TaqMan Real Time Polimerase Chain Reaction (RT-PCR) analysis for the best 40 genes associated with histology subtypes and survival. Over 90% of subtype-associated genes were confirmed. Overall survival was effectively predicted by hormone receptors (PGR and ESR2) and by TSPAN8. Relapse-free survival was predicted by MAPT and SNCG. In summary, we successfully validated several gene sets in a meta-analysis in large datasets of ovarian samples. Additionally, several individual genes identified were validated in a clinical cohort. Copyright © 2011 UICC.

  13. Male Fertility Issues

    Science.gov (United States)

    Fertility issues are common in boys and men getting cancer treatment. Fertility preservation options include sperm banking, testicular shielding, testicular sperm extraction (TESE), and testicular tissue freezing. Support and clinical trials are listed.

  14. Clavien classification of complications after the initial series of robot-assisted radical prostatectomy: the Cancer Institute of New Jersey/Robert Wood Johnson Medical School experience.

    Science.gov (United States)

    Jeong, Jeongyun; Choi, Eun Yong; Kim, Isaac Yi

    2010-09-01

    To study the safety and feasibility of robot-assisted radical prostatectomy (RARP) for the surgical management of localized prostate cancer, we analyzed perioperative parameters and the pattern of complications in our patients who underwent RARP. After the performance of more than 600 RARP over a 4-year period by a single surgeon using the daVinci® robot system at the Cancer Institute of New Jersey/Robert Wood Johnson Medical School, we reviewed the medical records of the first 200 patients retrospectively. All patients were divided into four groups according to the order of case numbers to compare intergroup differences in preoperative characteristics and perioperative parameters. Perioperative complications were determined in all patients, and complications were classified according to the Clavien classification system. The mean operative time was 212 minutes, and the mean blood loss was 189 mL. The mean length of hospital stay was 1.13 days. Overall, 12% (24 men) experienced various perioperative complications among the 200 patients. Of the total 24 patients, 5 (20.8%) men experienced intraoperative complications, and 19 (79.2%) men showed postoperative complications. Rectal injury occurred in two (8.3%) men, and the injury was repaired primarily using two-layer suture techniques without any sequelae. Three (12.5%) patients had femoral neuropathy, and urinary retention developed in 7 (25.0%) patients. Among our 200 patients, no transfusion was needed intraoperatively and postoperatively. There were nine (4.5%) patients in the Clavien grade I complications category, and another 9 (4.5%) men were classified as grade II complications. Six (3.0%) men had grade IIIb complications, and there were no grade IV or V complications. In our initial series of RARP procedures, we experienced low morbidity, with the overall complication rate of 12%. After implementing minor modifications, most of the early complications were prevented. Rectal injuries, if recognized

  15. A new algorithm for integrated analysis of miRNA-mRNA interactions based on individual classification reveals insights into bladder cancer.

    Science.gov (United States)

    Hecker, Nikolai; Stephan, Carsten; Mollenkopf, Hans-Joachim; Jung, Klaus; Preissner, Robert; Meyer, Hellmuth-A

    2013-01-01

    MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression. It has been proposed that miRNAs play an important role in cancer development and progression. Their ability to affect multiple gene pathways by targeting various mRNAs makes them an interesting class of regulators. We have developed an algorithm, Classification based Analysis of Paired Expression data of RNA (CAPE RNA), which is capable of identifying altered miRNA-mRNA regulation between tissues samples that assigns interaction states to each sample without preexisting stratification of groups. The distribution of the assigned interaction states compared to given experimental groups is used to assess the quality of a predicted interaction. We demonstrate the applicability of our approach by analyzing urothelial carcinoma and normal bladder tissue samples derived from 24 patients. Using our approach, normal and tumor tissue samples as well as different stages of tumor progression were successfully stratified. Also, our results suggest interesting differentially regulated miRNA-mRNA interactions associated with bladder tumor progression. The need for tools that allow an integrative analysis of microRNA and mRNA expression data has been addressed. With this study, we provide an algorithm that emphasizes on the distribution of samples to rank differentially regulated miRNA-mRNA interactions. This is a new point of view compared to current approaches. From bootstrapping analysis, our ranking yields features that build strong classifiers. Further analysis reveals genes identified as differentially regulated by miRNAs to be enriched in cancer pathways, thus suggesting biologically interesting interactions.

  16. When fear of cancer recurrence becomes a clinical issue: a qualitative analysis of features associated with clinical fear of cancer recurrence.

    Science.gov (United States)

    Mutsaers, Brittany; Jones, Georden; Rutkowski, Nicole; Tomei, Christina; Séguin Leclair, Caroline; Petricone-Westwood, Danielle; Simard, Sébastien; Lebel, Sophie

    2016-10-01

    Fear of cancer recurrence (FCR) is a common experience for cancer survivors. However, it remains unclear what characteristics differentiate non-clinical from clinical levels of FCR. The goal of this study was to investigate the potential hallmarks of clinical FCR. A convenience sample of 40 participants (n = 19 female) was drawn from another study (Lebel et al. in Qual Life Res 25:311-321. doi: 10.1007/s11136-015-1088-2 , 2016). The semi-structured interview for fear of cancer recurrence (Simard and Savard in J Cancer Surviv 9:481-491. doi: 10.1007/s11764-015-0424-4 , 2015) was used to identify participants with non-clinical and clinical FCR and qualitative analysis of these interviews was performed. Individuals with clinical FCR reported the following features: death-related thoughts, feeling alone, belief that the cancer would return, experiencing intolerance of uncertainty, having cancer-related thoughts and imagery that were difficult to control, daily and recurrent, lasted 30 minutes or more, increased over time, caused distress and impacted their daily life. Triggers of FCR and coping strategies did not appear to be features of clinical FCR as they were reported by participants with a range of FCR scores. While features of clinical FCR found in this analysis such as intrusive thoughts, distress and impact on functioning confirmed previous FCR research, other features spontaneously emerged from the interviews including "death-related thoughts," "feeling alone," and "belief that the cancer will return." The participants' descriptions of cancer-specific fear and worry suggest that FCR is a distinct phenomenon related to cancer survivorship, despite similarities with psychological disorders (e.g., Anxiety Disorders). Future research investigating the construct of FCR, and the distinguishing features of clinical FCR across a range of cancer types and gender is required.

  17. The PREgnancy and FERtility (PREFER) study: an Italian multicenter prospective cohort study on fertility preservation and pregnancy issues in young breast cancer patients.

    Science.gov (United States)

    Lambertini, Matteo; Anserini, Paola; Fontana, Valeria; Poggio, Francesca; Iacono, Giuseppina; Abate, Annalisa; Levaggi, Alessia; Miglietta, Loredana; Bighin, Claudia; Giraudi, Sara; D'Alonzo, Alessia; Blondeaux, Eva; Buffi, Davide; Campone, Francesco; Merlo, Domenico F; Del Mastro, Lucia

    2017-05-19

    Fertility and pregnancy issues are of key importance for young breast cancer patients. Despite several advances in the field, there are still multiple unmet needs and barriers in discussing and dealing with these concerns. To address the significant challenges related to fertility and pregnancy issues, the PREgnancy and FERtility (PREFER) study was developed as a national comprehensive program aiming to optimize care and improve knowledge around these topics. The PREFER study is a prospective cohort study conducted across several Italian institution affiliated with the Gruppo Italiano Mammella (GIM) group evaluating patterns of care and clinical outcomes of young breast cancer patients dealing with fertility and pregnancy issues. It is composed of two distinctive studies: PREFER-FERTILITY and PREFER-PREGNANCY. The PREFER-FERTILITY study is enrolling premenopausal patients aged 18-45 years, diagnosed with non-metastatic breast cancer, who are candidates to (neo)adjuvant chemotherapy and not previously exposed to anticancer therapies. The primary objective is to obtain and centralize data about patients' preferences and choices towards the available fertility preserving procedures. The success and safety of these strategies and the hormonal changes during chemotherapy and study follow-up are secondary objectives. The PREFER-PREGNANCY study is enrolling survivors achieving a pregnancy after prior history of breast cancer and patients diagnosed with pregnancy-associated breast cancer (PABC). The primary objectives are to obtain and centralize data about the management and clinical outcomes of these women. Patients' survival outcomes, and the fetal, obstetrical and paediatric care of their children are secondary objectives. For both studies, the initial planned recruitment period is 5 years and patients will remain in active follow-up for up to 15 years. The PREFER-FERTILITY study was first activated in November 2012, and the PREFER-PREGNANCY study in May 2013

  18. Multiplex Approach in Classification, Diagnosis, and Prognostication in Acute Myeloid Leukemia: An Experience from Tertiary Cancer Center in South India.

    Science.gov (United States)

    Khera, Rachna; Ahmed, Faiq; Mundada, Manasi Chetan; Devi, Sandhya G; Murthy, Sudha S; Lavanya, Nambaru; Rajappa, Senthil J; Mallavarapu, Krishna Mohan; Santa, A

    2017-01-01

    Acute myeloid leukemia (AML) is a heterogeneous group of disorders classified as per FAB subtypes and more recently by WHO by underlying genetic abnormalities. This study aims to analyze the morphology, immunophenotype, cytogenetic and molecular abnormalities in around 200 patients of AML diagnosed over a period of 7 years at our institute and to determine relative frequency of various subtypes (based on FAB and WHO classification). An attempt to characterize the associations between hematological parameters, immunophenotype and these subtypes was also made. All cases diagnosed as AML on morphology, cytochemistry and/or immunophenotyping and tested for recurrent genetic abnormalities during period of Jan 2008-July 2014 were included in the study. Age of presentation was younger in our AML patients as compared to western literature. Amongst FAB and WHO subtypes, M2 and t (15;17) PML-RARA were the most common groups respectively. As expected, CD33, CD13, were the most commonly expressed markers followed by HLA-DR, CD117, CD34 and CD14. Aberrant expression was seen in 62(41.6%) cases, most common was CD7 (15.4%), followed by CD56 (14.8%), CD19 (6.7%) and CD2 (4.7%). Significant associations between immunophenotypic markers and FAB subtypes as well as WHO subtypes were established. This is a hospital based study, giving a detailed account of frequencies of AML subtypes, hematological parameters and immunophenotypic markers in AML patients at our institute. Being a large and one of its kind study to establish significant associations between various haematological and immunophenotypic parameters with respective AML subtypes and genetic abnormalities, it might prove to be very useful in Indian setup where facilities for cytogenetic analysis are not available in many laboratories.

  19. Human colon cancers as a major problem in poland and in the world – medical and environmental issues

    Directory of Open Access Journals (Sweden)

    Sylwia Katarzyna Król

    2011-12-01

    Full Text Available Many epidemiological data have shown an increasing incidence and mortality of colon cancer cases in the past several years, not only in Poland but all over the world as well. Each year, approximately a million new cases of colon cancer are diagnosed and that is the cause of death of almost half a million patients in the world. The aim of this article is to present the epidemiology and the current state of scientific knowledge concerning etiology and pathogenesis of neoplastic diseases in human large intestine. Furthermore, this short review describes the essential risk factors and suggests the simple and effective ways of colon cancer prevention.Colorectal cancer is one of the most frequently diagnosed cancers in EU countries. Scientific studies have proved that genetic and hereditary factors have a strong influence on carcinogenesis in human colon. Moreover, environmental factors, such as dietary contribute to the development of colon neoplasm. The most useful tool to reduce high morbidity and mortality is a prevention. Screening tests in nonsymptomatic people from high-risk groups or populations enable diagnosis in the early stage of colorectal cancer. Many publications have reported that modification of lifestyle and daily diet also play a significant role in prevention.

  20. Patients' and Health Care Providers' Evaluation of Quality of Life Issues in Advanced Cancer Using Functional Assessment of Chronic Illness Therapy - Palliative Care Module (FACIT-Pal) Scale.

    Science.gov (United States)

    Khan, Luluel; Zeng, Liang; Cella, David; Thavarajah, Nemica; Chen, Emily; Zhang, Liying; Bennett, Margaret; Peckham, Kenneth; De Costa, Sandra; Beaumont, Jennifer L; Tsao, May; Danjoux, Cyril; Barnes, Elizabeth; Sahgal, Arjun; Chow, Edward

    2012-10-01

    To examine the agreement of Health Care Providers (HCPs) and patients' evaluation of quality of life on the Functional Assessment of Chronic Illness therapy - Palliative care module (FACIT-Pal) scale. Sixty advanced cancer patients and fifty-six health care providers involved in their care at Sunnybrook Health Sciences Centre completed a modified version of the FACIT- Pal. In the survey, patients and HCPs indicated the 10 top issues affecting the quality of life of patients with advanced cancer most profoundly. The percentage of participants selecting each item as one of their 10 most relevant items was calculated in HCPs and patients. There were differences in relative rankings of QOL issues among patients and HCPs. Among the top 10 items which were identified from both patients and HCPs, there were differences in the rankings. Patients ranked emotional support from family (40.9%) as most important followed by pain (38.6%), lack of energy (31.8%) and able to enjoy life (29.6%). HCPs ranked in the following order: pain (73.2%), lack of energy (63.4%), nausea (51.2%) and dyspnea (51.2%) whereas patients rated nausea at 18.2 % and dyspnea at 9.09%. There is a discrepancy between scores of patients and HCPs as they may prioritize differently. HCPs tended to put more emphasis on physical symptoms, whereas patients had emotional and global issues as priorities.

  1. Application of the International Classification of Functioning, Disability and Health (ICF) to people with dysphagia following non-surgical head and neck cancer management.

    Science.gov (United States)

    Nund, Rebecca L; Scarinci, Nerina A; Cartmill, Bena; Ward, Elizabeth C; Kuipers, Pim; Porceddu, Sandro V

    2014-12-01

    The International Classification of Functioning, Disability, and Health (ICF) is an internationally recognized framework which allows its user to describe the consequences of a health condition on an individual in the context of their environment. With growing recognition that dysphagia can have broad ranging physical and psychosocial impacts, the aim of this paper was to identify the ICF domains and categories that describe the full functional impact of dysphagia following non-surgical head and neck cancer (HNC) management, from the perspective of the person with dysphagia. A secondary analysis was conducted on previously published qualitative study data which explored the lived experiences of dysphagia of 24 individuals with self-reported swallowing difficulties following HNC management. Categories and sub-categories identified by the qualitative analysis were subsequently mapped to the ICF using the established linking rules to develop a set of ICF codes relevant to the impact of dysphagia following HNC management. The 69 categories and sub-categories that had emerged from the qualitative analysis were successfully linked to 52 ICF codes. The distribution of these codes across the ICF framework revealed that the components of Body Functions, Activities and Participation, and Environmental Factors were almost equally represented. The findings confirm that the ICF is a valuable framework for representing the complexity and multifaceted impact of dysphagia following HNC. This list of ICF codes, which reflect the diverse impact of dysphagia associated with HNC on the individual, can be used to guide more holistic assessment and management for this population.

  2. Incidence and survival of lymphohematopoietic neoplasms according to the World Health Organization classification: a population-based study from the Victorian Cancer Registry in Australia.

    Science.gov (United States)

    Jayasekara, Harindra; Karahalios, Amalia; Juneja, Surender; Thursfield, Vicky; Farrugia, Helen; English, Dallas R; Giles, Graham G

    2010-03-01

    We studied the incidence and relative survival of 39 837 cases of lymphohematopoietic neoplasms (LHN) reported to the Victorian Cancer Registry during 1982-2004, classified according to the World Health Organization (WHO) classification. We modeled excess mortality using Poisson regression to estimate differences in survival by age, sex, and time period. Age-standardized incidence rates varied across subtypes of lymphoid and myeloid neoplasms. All major subtypes predominantly affected the elderly except Hodgkin lymphoma (incidence peaks at 20-24 and 75-79 years) and acute lymphoblastic leukemia (0-9 years). After an initial rise, overall lymphoid and myeloid incidence stabilized in the mid-1990s. The 5-year relative survival was 58% for lymphoid and 35% for myeloid neoplasms. Survival improved during 1990-2004 for diffuse large B-cell lymphoma, follicular lymphoma, acute myeloid leukemia, chronic myeloid leukemia, and myelodysplastic syndromes (p  < 0.001) and declined with advancing age for all subtypes (p <  0.001). Female sex was associated with higher survival for most myeloid subtypes. The results represent a rare epidemiological characterization of the whole range of LHN according to WHO subtypes.

  3. Combined application of information theory on laboratory results with classification and regression tree analysis: analysis of unnecessary biopsy for prostate cancer.

    Science.gov (United States)

    Hwang, Sang-Hyun; Pyo, Tina; Oh, Heung-Bum; Park, Hyun Jun; Lee, Kwan-Jeh

    2013-01-16

    The probability of a prostate cancer-positive biopsy result varies with PSA concentration. Thus, we applied information theory on classification and regression tree (CART) analysis for decision making predicting the probability of a biopsy result at various PSA concentrations. From 2007 to 2009, prostate biopsies were performed in 664 referred patients in a tertiary hospital. We created 2 CART models based on the information theory: one for moderate uncertainty (PSA concentration: 2.5-10 ng/ml) and the other for high uncertainty (PSA concentration: 10-25 ng/ml). The CART model for moderate uncertainty (n=321) had 3 splits based on PSA density (PSAD), hypoechoic nodules, and age and the other CART for high uncertainty (n=160) had 2 splits based on prostate volume and percent-free PSA. In this validation set, the patients (14.3% and 14.0% for moderate and high uncertainty groups, respectively) could avoid unnecessary biopsies without false-negative results. Using these CART models based on uncertainty information of PSA, the overall reduction in unnecessary prostate biopsies was 14.0-14.3% and CART models were simplified. Using uncertainty of laboratory results from information theoretic approach can provide additional information for decision analysis such as CART. Copyright © 2012 Elsevier B.V. All rights reserved.

  4. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  5. Delay in diagnosis of cancer as a patient safety issue - a root cause analysis based on a representative case report

    Directory of Open Access Journals (Sweden)

    Mansour Paul

    2011-07-01

    Full Text Available Abstract Background It is well known in the literature that imaging has almost no value for diagnosis of superficial bladder cancer. However, wide gap exists between knowledge on diagnosis of bladder cancer and actual clinical practice. Case presentation Delay in diagnosis of bladder cancer in a male person with tetraplegia occurred because of reliance on negative flexible cystoscopy and single biopsy, negative ultrasound examination of urinary bladder, and computerised tomography of pelvis. Difficulties in scheduling cystoscopy also contributed to a delay of nearly ten months between the onset of haematuria and establishing a histological diagnosis of vesical malignancy in this patient. The time interval between transurethral resection and cystectomy was 42 days. This delay was mainly due to scheduling of surgery. Conclusion We learn from this case that doctors should be aware of the limitations of negative flexible cystoscopy and single biopsy, cytology of urine, ultrasound examination of urinary bladder, and computed tomography of pelvis for diagnosis of bladder cancer in spinal cord injury patients. Random bladder biopsies must be considered under general anaesthesia when there is high suspicion of bladder cancer. Spinal cord injury patients with lesions above T-6 may develop autonomic dysreflexia; therefore, one should be extremely well prepared to prevent or manage autonomic dysreflexia when performing cystoscopy and bladder biopsy. Spinal cord injury patients, who pass blood in urine, should be accorded top priority in scheduling of investigations and surgical procedures.

  6. Key issues affecting quality of life and patient-reported outcomes in prostate cancer: an analysis conducted in 2128 patients with initial psychometric assessment of the prostate cancer symptom scale (PCSS).

    Science.gov (United States)

    Msaouel, Pavlos; Gralla, Richard J; Jones, Randy A; Hollen, Patricia J

    2017-09-01

    Evidence-based quality of life (QL) questionnaires require the identification of issues of importance to patients. The primary aim of this study was to inform providers on patient-expressed issues while enhancing the content validity of instruments assessing QL and patient-reported outcomes (PROs) in prostate cancer. The study provided additional psychometric properties for the new PRO and QL instrument, the Prostate Cancer Symptom Scale (PCSS). An anonymous web-based survey of 2128 patients with prostate cancer was conducted with patients rating 18 QL items on a five-point scale. Most respondents (74%) were aged 55-74 years, had early stage disease at diagnosis (81%) and were diagnosed within 2 years of the survey (81%). The top five-rated issues were: overall QL, ability to perform normal activities, maintaining independence, ability to sleep and not being a burden. These items were ranked as either 'very important' or 'important' by at least 88% of patients. None of the most highly ranked issues were symptoms. Instead, the highest ranked items were global issues reflecting the impact of symptoms on patients. In addition to the enhanced content validity findings, good reliability results and initial support for construct validity are reported for the PCSS. This is the largest survey providing patient-expressed background for content validity for QL and PRO measures. The findings of this study should aid development of newer practical questionnaires, such as the PCSS, which can be adapted to electronic platforms enhancing rapid and accurate PRO and QL evaluation. 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/.

  7. Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning.

    Science.gov (United States)

    Wang, Xinggang; Yang, Wei; Weinreb, Jeffrey; Han, Juan; Li, Qiubai; Kong, Xiangchuang; Yan, Yongluan; Ke, Zan; Luo, Bo; Liu, Tao; Wang, Liang

    2017-11-13

    Prostate cancer (PCa) is a major cause of death since ancient time documented in Egyptian Ptolemaic mummy imaging. PCa detection is critical to personalized medicine and varies considerably under an MRI scan. 172 patients with 2,602 morphologic images (axial 2D T2-weighted imaging) of the prostate were obtained. A deep learning with deep convolutional neural network (DCNN) and a non-deep learning with SIFT image feature and bag-of-word (BoW), a representative method for image recognition and analysis, were used to distinguish pathologically confirmed PCa patients from prostate benign conditions (BCs) patients with prostatitis or prostate benign hyperplasia (BPH). In fully automated detection of PCa patients, deep learning had a statistically higher area under the receiver operating characteristics curve (AUC) than non-deep learning (P = 0.0007 deep learning method and 0.70 (95% CI 0.63-0.77) for non-deep learning method, respectively. Our results suggest that deep learning with DCNN is superior to non-deep learning with SIFT image feature and BoW model for fully automated PCa patients differentiation from prostate BCs patients. Our deep learning method is extensible to image modalities such as MR imaging, CT and PET of other organs.

  8. Classification of biosensor time series using dynamic time warping: applications in screening cancer cells with characteristic biomarkers

    Science.gov (United States)

    Rai, Shesh N; Trainor, Patrick J; Khosravi, Farhad; Kloecker, Goetz; Panchapakesan, Balaji

    2016-01-01

    The development of biosensors that produce time series data will facilitate improvements in biomedical diagnostics and in personalized medicine. The time series produced by these devices often contains characteristic features arising from biochemical interactions between the sample and the sensor. To use such characteristic features for determining sample class, similarity-based classifiers can be utilized. However, the construction of such classifiers is complicated by the variability in the time domains of such series that renders the traditional distance metrics such as Euclidean distance ineffective in distinguishing between biological variance and time domain variance. The dynamic time warping (DTW) algorithm is a sequence alignment algorithm that can be used to align two or more series to facilitate quantifying similarity. In this article, we evaluated the performance of DTW distance-based similarity classifiers for classifying time series that mimics electrical signals produced by nanotube biosensors. Simulation studies demonstrated the positive performance of such classifiers in discriminating between time series containing characteristic features that are obscured by noise in the intensity and time domains. We then applied a DTW distance-based k-nearest neighbors classifier to distinguish the presence/absence of mesenchymal biomarker in cancer cells in buffy coats in a blinded test. Using a train–test approach, we find that the classifier had high sensitivity (90.9%) and specificity (81.8%) in differentiating between EpCAM-positive MCF7 cells spiked in buffy coats and those in plain buffy coats. PMID:27942497

  9. A lymphocyte spatial distribution graph-based method for automated classification of recurrence risk on lung cancer images

    Science.gov (United States)

    Garciá-Arteaga, Juan D.; Corredor, Germán.; Wang, Xiangxue; Velcheti, Vamsidhar; Madabhushi, Anant; Romero, Eduardo

    2017-11-01

    Tumor-infiltrating lymphocytes occurs when various classes of white blood cells migrate from the blood stream towards the tumor, infiltrating it. The presence of TIL is predictive of the response of the patient to therapy. In this paper, we show how the automatic detection of lymphocytes in digital H and E histopathological images and the quantitative evaluation of the global lymphocyte configuration, evaluated through global features extracted from non-parametric graphs, constructed from the lymphocytes' detected positions, can be correlated to the patient's outcome in early-stage non-small cell lung cancer (NSCLC). The method was assessed on a tissue microarray cohort composed of 63 NSCLC cases. From the evaluated graphs, minimum spanning trees and K-nn showed the highest predictive ability, yielding F1 Scores of 0.75 and 0.72 and accuracies of 0.67 and 0.69, respectively. The predictive power of the proposed methodology indicates that graphs may be used to develop objective measures of the infiltration grade of tumors, which can, in turn, be used by pathologists to improve the decision making and treatment planning processes.

  10. Body issues, sexual satisfaction, and relationship status satisfaction in long-term childhood cancer survivors and healthy controls.

    Science.gov (United States)

    Lehmann, Vicky; Hagedoorn, Mariët; Gerhardt, Cynthia A; Fults, Marci; Olshefski, Randal S; Sanderman, Robbert; Tuinman, Marrit A

    2016-02-01

    Research on body image and sexual satisfaction after adult onset cancer has shown significant and lasting impairments regarding survivors' sexuality and romantic relationships. However, knowledge about these topics and their associations in adult survivors of childhood cancer is largely lacking. Participants completed web-based questionnaires concerning body image, body dissociation, sexual satisfaction, and relationship status satisfaction (i.e., satisfaction with either being in a relationship or being single). Survivors (n = 87) and controls (n = 87) were matched on age and gender, with a mean age of 27 years (range: 20-40). Survivors were most often diagnosed with leukemia (46%), at an average of 16 years prior to study participation (range: 6-33 years). Similar numbers of survivors and controls were single (n = 24/31), in a committed relationship (n = 33/23), or married (n = 30/33). Survivors and controls reported comparable levels of body image, body dissociation, sexual experiences, and sexual and status satisfaction (d = 0.15-0.28). Higher status satisfaction was associated with being in a relationship (compared with being single, β = 0.439), more positive body image (β = 0.196), and higher sexual satisfaction (β = 0.200). Adult survivors of childhood cancer were comparable to healthy peers regarding views of their bodies and psychosexual development, which was unexpected. Independent of whether people experienced cancer or not, their status satisfaction was associated with their relationship status, body image, and sexual satisfaction. Future research should explore why sexual and body problems are identified after adult onset cancer, whereas this seems to be less of a problem in childhood cancer survivors. Copyright © 2015 John Wiley & Sons, Ltd.

  11. Xenolog classification.

    Science.gov (United States)

    Darby, Charlotte A; Stolzer, Maureen; Ropp, Patrick J; Barker, Daniel; Durand, Dannie

    2017-03-01

    Orthology analysis is a fundamental tool in comparative genomics. Sophisticated methods have been developed to distinguish between orthologs and paralogs and to classify paralogs into subtypes depending on the duplication mechanism and timing, relative to speciation. However, no comparable framework exists for xenologs: gene pairs whose history, since their divergence, includes a horizontal transfer. Further, the diversity of gene pairs that meet this broad definition calls for classification of xenologs with similar properties into subtypes. We present a xenolog classification that uses phylogenetic reconciliation to assign each pair of genes to a class based on the event responsible for their divergence and the historical association between genes and species. Our classes distinguish between genes related through transfer alone and genes related through duplication and transfer. Further, they separate closely-related genes in distantly-related species from distantly-related genes in closely-related species. We present formal rules that assign gene pairs to specific xenolog classes, given a reconciled gene tree with an arbitrary number of duplications and transfers. These xenology classification rules have been implemented in software and tested on a collection of ∼13 000 prokaryotic gene families. In addition, we present a case study demonstrating the connection between xenolog classification and gene function prediction. The xenolog classification rules have been implemented in N otung 2.9, a freely available phylogenetic reconciliation software package. http://www.cs.cmu.edu/~durand/Notung . Gene trees are available at http://dx.doi.org/10.7488/ds/1503 . durand@cmu.edu. Supplementary data are available at Bioinformatics online.

  12. Correlation of EGFR mutation status with predominant histologic subtype of adenocarcinoma according to the new lung adenocarcinoma classification of the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society.

    Science.gov (United States)

    Villa, Celina; Cagle, Philip T; Johnson, Melissa; Patel, Jyoti D; Yeldandi, Anjana V; Raj, Rishi; DeCamp, Malcolm M; Raparia, Kirtee

    2014-10-01

    Epidermal growth factor receptor (EGFR) mutations have been identified as predictors of response to EGFR tyrosine kinase inhibitors in non-small cell lung cancer. To investigate the relationship of EGFR mutation status to the histologic subtype of adenocarcinoma according to the new International Association for the Study of Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) classification. We screened EGFR mutation in 200 consecutive lung adenocarcinoma resection specimens diagnosed between 2008 and 2011. Among 200 lung adenocarcinomas, EGFR mutations were identified in 41 tumors (20.5%). The mean age in the EGFR-mutant group was 64.8 years and this group consisted of 78% females and 22% males. Most patients with EGFR-positive lung cancers were never-smokers (51%) as compared to 8% with EGFR-negative cancers (P adenocarcinoma was lepidic (44%) in EGFR-mutant lung cancers as compared to 69% with acinar pattern in EGFR wild-type lung cancers (P adenocarcinomas, 8 (36%) had EGFR mutations, accounting for 20% of adenocarcinomas with EGFR mutations (P adenocarcinoma was lepidic (44%) in EGFR-mutant lung cancers (P lung adenocarcinomas of other subtypes.

  13. Systematic review of the health-related quality of life issues facing adolescents and young adults with cancer

    NARCIS (Netherlands)

    Sodergren, S.C.; Husson, O.; Robinson, J.; Rohde, G.E.; Tomaszewska, I.M.; Vivat, B.; Dyar, R.; Darlington, A.S.

    2017-01-01

    PURPOSE: For adolescents and young adults (AYAs), the impact of a cancer diagnosis and subsequent treatment is likely to be distinct from other age groups given the unique and complex psychosocial challenges of this developmental phase. In this review of the literature, we report the health-related

  14. Review article: Practical management issues for the Helicobacter pylori-infected patient at risk of gastric cancer

    NARCIS (Netherlands)

    Tytgat, G. N.

    1998-01-01

    The public health implications of H. pylori infection are considerable in view of the universality of the infection and its attributable risk in cancer causation. Education of the population as to hygiene and nutrition are prerequisites. Total testing/screening and treatment of the infected

  15. Methodological challenges in quality of life research among Turkish and Moroccan ethnic minority cancer patients: translation, recruitment and ethical issues

    NARCIS (Netherlands)

    Hoopman, R.; Terwee, C.B.; Muller, M.T.; Ory, F.; Aaronson, N.K.

    2009-01-01

    The large population of first generation Turkish and Moroccan immigrants who moved to Western Europe in the 1960s and 1970s is now reaching an age at which the incidence of chronic diseases, including cancer, rises sharply. To date, little attention has been paid to the health-related quality of

  16. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  17. Media coverage of women's health issues: is there a bias in the reporting of an association between hormone replacement therapy and breast cancer?

    Science.gov (United States)

    Whiteman, M K; Cui, Y; Flaws, J A; Langenberg, P; Bush, T L

    2001-01-01

    Media coverage of scientific research plays a major role in shaping public opinion and influencing medical practice. When an association is controversial, such as with hormone replacement therapy (HRT) and breast cancer, it is important that a balanced picture of the scientific literature be reported. The objective of this study was to assess whether scientific publications that do and do not support an HRT/breast cancer association were cited in the media in proportions similar to those with which they appear in the scientific literature. Scientific publications reporting on the HRT/breast cancer association published from January 1, 1995, to June 30, 2000, were identified through a systematic Medline search. Media reports from newspapers, magazines, television, and radio that reported on HRT and breast cancer were retrieved from an online database. Investigators independently recorded characteristics of the scientific publications and media reports. A total of 32 scientific publications were identified: 20 (62.5%) concluded there was an increased risk of breast cancer associated with HRT (positive publications), and 12 (37.5%) concluded there was no evidence for an association (null publications). Nearly half (47%) of the scientific publications were not cited by the media. There were 203 media citations of scientific publications: 82% were of positive publications and 18% were of null publications, representing a significant excess of citations of positive publications (p Media coverage of this controversial issue is based on a limited sample of the scientific publications. Moreover, the excess of media citations for positive scientific publications suggests a bias against null scientific publications.

  18. Classification and Regression Tree Analysis of Clinical Patterns to Predict the Survival of Patients with Advanced Non-small Cell Lung Cancer Treated with Erlotinib

    Directory of Open Access Journals (Sweden)

    Yutao LIU

    2011-10-01

    Full Text Available Background and objective Erlotinib is a targeted therapy drug for non-small cell lung cancer (NSCLC. It has been proven that, there was evidence of various survival benefits derived from erlotinib in patients with different clinical features, but the results are conflicting. The aim of this study is to identify novel predictive factors and explore the interactions between clinical variables as well as their impact on the survival of Chinese patients with advanced NSCLC heavily treated with erlotinib. Methods The clinical and follow-up data of 105 Chinese NSCLC patients referred to the Cancer Hospital and Institute, Chinese Academy of Medical Sciences from September 2006 to September 2009 were analyzed. Multivariate analysis of progressive-free survival (PFS was performed using recursive partitioning referred to as the classification and regression tree (CART analysis. Results The median PFS of 105 eligible consecutive Chinese NSCLC patients was 5.0 months (95%CI: 2.9-7.1. CART analysis was performed for the initial, second, and third split in the lymph node involvement, the time of erlotinib administration, and smoking history. Four terminal subgroups were formed. The longer values for the median PFS were 11.0 months (95%CI: 8.9-13.1 for the subgroup with no lymph node metastasis and 10.0 months (95%CI: 7.9-12.1 for the subgroup with lymph node involvement, but not over the second-line erlotinib treatment with a smoking history ≤35 packs per year. The shorter values for the median PFS were 2.3 months (95%CI: 1.6-3.0 for the subgroup with lymph node metastasis and over the second-line erlotinib treatment, and 1.3 months (95%CI: 0.5-2.1 for the subgroup with lymph node metastasis, but not over the second-line erlotinib treatment with a smoking history >35 packs per year. Conclusion Lymph node metastasis, the time of erlotinib administration, and smoking history are closely correlated with the survival of advanced NSCLC patients with first- to

  19. Modern classification of neoplasms: reconciling differences between morphologic and molecular approaches

    Directory of Open Access Journals (Sweden)

    Berman Jules

    2005-08-01

    Full Text Available Abstract Background For over 150 years, pathologists have relied on histomorphology to classify and diagnose neoplasms. Their success has been stunning, permitting the accurate diagnosis of thousands of different types of neoplasms using only a microscope and a trained eye. In the past two decades, cancer genomics has challenged the supremacy of histomorphology by identifying genetic alterations shared by morphologically diverse tumors and by finding genetic features that distinguish subgroups of morphologically homogeneous tumors. Discussion The Developmental Lineage Classification and Taxonomy of Neoplasms groups neoplasms by their embryologic origin. The putative value of this classification is based on the expectation that tumors of a common developmental lineage will share common metabolic pathways and common responses to drugs that target these pathways. The purpose of this manuscript is to show that grouping tumors according to their developmental lineage can reconcile certain fundamental discrepancies resulting from morphologic and molecular approaches to neoplasm classification. In this study, six issues in tumor classification are described that exemplify the growing rift between morphologic and molecular approaches to tumor classification: 1 the morphologic separation between epithelial and non-epithelial tumors; 2 the grouping of tumors based on shared cellular functions; 3 the distinction between germ cell tumors and pluripotent tumors of non-germ cell origin; 4 the distinction between tumors that have lost their differentiation and tumors that arise from uncommitted stem cells; 5 the molecular properties shared by morphologically disparate tumors that have a common developmental lineage, and 6 the problem of re-classifying morphologically identical but clinically distinct subsets of tumors. The discussion of these issues in the context of describing different methods of tumor classification is intended to underscore the clinical

  20. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    to segment breast tissue and pectoral muscle area from the background in mammogram. The second focus is the choices of metric and its influence to the feasibility of a classifier, especially on k-nearest neighbors (k-NN) algorithm, with medical applications on breast cancer prediction and calcification...... and explores these challenging areas. The first focus of the thesis is to properly combine different local feature experts and prior information to design an effective classifier. The preliminary classification results, provided by the experts, are fused in order to develop an automatic segmentation method...

  1. An Independent Validation of 2010 Tumor-Node-Metastasis Classification for Renal Cell Carcinoma: A Multi-center Study by the Urooncology Association of Turkey Renal Cancer-Study Group

    Directory of Open Access Journals (Sweden)

    Tayyar Alp Özkan

    2017-06-01

    Full Text Available Objective: The American Joint Committee on Cancer tumor-node-metastasis (TNM classification has been updated by the 7th edition in 2010. The objective of the study was to evaluate cancer-specific survival (CSS in patients with renal cell carcinoma (RCC and assess the concordance of 2002 and novel 2010 TNM primary tumor classifications. Materials and Methods: A retrospective analysis of RCC registries from 25 institutions of the Urooncology Association of Turkey Renal Cancer-Study Group was performed. Patients with RCC had a radical or partial nephrectomy. The database consisted of 1889 patients. Results: Median follow-up time was 25 months (interquartile range: 11.2-47.8. The 5-year CSS rate for pT1a, pT1b, pT2a, pT2b, pT3a and pT4 tumors were 97% [95% confidence interval (CI: 0.93-0.99], 94% (95% CI: 0.91-0.97, 88% (95% CI: 0.81-0.93, 77% (95% CI: 0.64-0.86 74% (95% CI: 0.65-0.81 and 66% (95% CI: 0.51-0.77, respectively according to the 2010 TNM classification (p<0.001. CSS comparisons between pT1a-pT1b (p=0.022, pT1b-pT2a (p=0.030, pT3a-pT3b (p<0.001 and pT3b-pT4 (p=0.020 were statistically significant. Conversely, pT2a-pT2b (p=0.070 and pT2b-pT3a (p=0.314 were not statistically significant. Multivariable analyses revealed the pT stage in the 2010 TNM classification as an independent prognostic factor for CSS (p for trend=0.002. C-indexes for 2002 and 2010 TNM classifications were 0.8683 and 0.8706, respectively. Conclusion: Subdividing pT2 does not have a CSS advantage. Moving adrenal involvement to pT4 yielded a more accurate prognosis prediction. T stage and LNI are independent prognostic factors for CSS in RCC. Overall, the novel 2010 TNM classification is slightly improved over the former one. However, shown by C-index values, this improvement is not sufficient to state that 2010 TNM outperforms the 2002 TNM.

  2. Validation of the Consensus-Definition for Cancer Cachexia and evaluation of a classification model--a study based on data from an international multicentre project (EPCRC-CSA).

    Science.gov (United States)

    Blum, D; Stene, G B; Solheim, T S; Fayers, P; Hjermstad, M J; Baracos, V E; Fearon, K; Strasser, F; Kaasa, S

    2014-08-01

    Weight loss limits cancer therapy, quality of life and survival. Common diagnostic criteria and a framework for a classification system for cancer cachexia were recently agreed upon by international consensus. Specific assessment domains (stores, intake, catabolism and function) were proposed. The aim of this study is to validate this diagnostic criteria (two groups: model 1) and examine a four-group (model 2) classification system regarding these domains as well as survival. Data from an international patient sample with advanced cancer (N = 1070) were analysed. In model 1, the diagnostic criteria for cancer cachexia [weight loss/body mass index (BMI)] were used. Model 2 classified patients into four groups 0-III, according to weight loss/BMI as a framework for cachexia stages. The cachexia domains, survival and sociodemographic/medical variables were compared across models. Eight hundred and sixty-one patients were included. Model 1 consisted of 399 cachectic and 462 non-cachectic patients. Cachectic patients had significantly higher levels of inflammation, lower nutritional intake and performance status and shorter survival. In model 2, differences were not consistent; appetite loss did not differ between group III and IV, and performance status not between group 0 and I. Survival was shorter in group II and III compared with other groups. By adding other cachexia domains to the model, survival differences were demonstrated. The diagnostic criteria based on weight loss and BMI distinguish between cachectic and non-cachectic patients concerning all domains (intake, catabolism and function) and is associated with survival. In order to guide cachexia treatment a four-group classification model needs additional domains to discriminate between cachexia stages. © The Author 2014. 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.

  3. Evaluation of a panel of expert pathologists: review of the diagnosis and histological classification of Hodgkin and non-Hodgkin lymphomas in a population-based cancer registry

    NARCIS (Netherlands)

    Strobbe, L.; Schans, S.A. van de; Heijker, S.M.; Meijer, J.W.R.; Mattijssen, E.J.; Mandigers, C.M.P.W.; Kievit, I.M. de; Raemaekers, J.M.M.; Hebeda, K.M.; Krieken, J.H. van

    2014-01-01

    Abstract Correct histological classification of malignant lymphomas is important but has always been a difficult challenge. Since 2001 the World Health Organization (WHO) classification has been used, which should make it easier to define distinct disease entities. The purpose of this study was to

  4. Cancer Patient Experience in the Teenage Young Adult Population- Key Issues and Trends Over Time: An Analysis of the United Kingdom National Cancer Patient Experience Surveys 2010-2014.

    Science.gov (United States)

    Furness, Caroline L; Smith, Lesley; Morris, Eva; Brocklehurst, Caroline; Daly, Sasha; Hough, Rachael E

    2017-09-01

    Improving outcomes for teenagers and young adults (TYA) with cancer is a key element of the national cancer strategy in England. Recognition of the unique needs of this group has led to the development of recommendations for specific models of care and delivery of this care through the provision of dedicated clinical units in principal treatment centers (PTCs) across the United Kingdom. The aim of this study was to understand the current cancer patient experience for this patient group. We aimed to determine whether treatment experience is influenced by place of treatment and whether it has changed over time using patient-reported data from national cancer patient experience surveys. This study highlights that a prolonged pathway to diagnosis remains an issue for the TYA group and identifies areas on which quality improvement measures for TYA services should focus, including communication and involvement of the patient in treatment decisions. Positive experiences for the TYA group such as involvement in research were also highlighted. Treatment within a TYA PTC was associated with positive patient perception in a number of key areas highlighting the need for future studies to fully elucidate the impact of the full range of TYA services now available in the United Kingdom on both patient experience and outcome.

  5. Challenging diagnostic issues in adenomatous polyps with epithelial misplacement in bowel cancer screening: 5 years' experience of the Bowel Cancer Screening Programme Expert Board.

    Science.gov (United States)

    Griggs, Rebecca K L; Novelli, Marco R; Sanders, D Scott A; Warren, Bryan F; Williams, Geraint T; Quirke, Philip; Shepherd, Neil A

    2017-02-01

    The diagnostic difficulties of differentiating epithelial misplacement from invasive cancer in colorectal adenomatous polyps have been recognised for many years. Nevertheless, the introduction of population screening in the UK has resulted in extraordinary diagnostic problems. Larger sigmoid colonic adenomatous polyps, which are those most likely to show epithelial misplacement, are specifically selected into such screening programmes, because these polyps are likely to bleed and screening is based on the detection of occult blood. The diagnostic challenges associated with this particular phenomenon have necessitated the institution of an 'Expert Board': this is a review of the first five years of its practice, during which time 256 polyps from 249 patients have been assessed. Indeed, the Expert Board contains three pathologists, because those pathologists do not necessarily agree, and a consensus diagnosis is required to drive appropriate patient management. However, this study has shown substantial levels of agreement between the three Expert Board pathologists, whereby the ultimate diagnosis has been changed, from that of the original referral diagnosis, by the Expert Board for half of all the polyps, in the substantial majority from malignant to benign. In 3% of polyp cases, the Expert Board consensus has been the dual diagnosis of both epithelial misplacement and adenocarcinoma, further illustrating the diagnostic difficulties. The Expert Board of the Bowel Cancer Screening Programme in the UK represents a unique and successful development in response to an extraordinary diagnostic conundrum created by the particular characteristics of bowel cancer screening. © 2016 John Wiley & Sons Ltd.

  6. Statistical issues for design and analysis of single-arm multi-stage phase II cancer clinical trials.

    Science.gov (United States)

    Jung, Sin-Ho

    2015-05-01

    Phase II trials have been very widely conducted and published every year for cancer clinical research. In spite of the fast progress in design and analysis methods, single-arm two-stage design is still the most popular for phase II cancer clinical trials. Because of their small sample sizes, statistical methods based on large sample approximation are not appropriate for design and analysis of phase II trials. As a prospective clinical research, the analysis method of a phase II trial is predetermined at the design stage and it is analyzed during and at the end of the trial as planned by the design. The analysis method of a trial should be matched with the design method. For two-stage single arm phase II trials, Simon's method has been the standards for choosing an optimal design, but the resulting data have been analyzed and published ignoring the two-stage design aspect with small sample sizes. In this article, we review analysis methods that exactly get along with the exact two-stage design method. We also discuss some statistical methods to improve the existing design and analysis methods for single-arm two-stage phase II trials. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Comparison of risk classification between EndoPredict and MammaPrint in ER-positive/HER2-negative primary invasive breast cancer

    Science.gov (United States)

    Peláez-García, Alberto; Yébenes, Laura; Berjón, Alberto; Angulo, Antonia; Zamora, Pilar; Sánchez-Méndez, José Ignacio; Espinosa, Enrique; Redondo, Andrés; Heredia-Soto, Victoria; Mendiola, Marta; Feliú, Jaime

    2017-01-01

    Purpose To compare the concordance in risk classification between the EndoPredict and the MammaPrint scores obtained for the same cancer samples on 40 estrogen-receptor positive/HER2-negative breast carcinomas. Methods Formalin-fixed, paraffin-embedded invasive breast carcinoma tissues that were previously analyzed with MammaPrint as part of routine care of the patients, and were classified as high-risk (20 patients) and low-risk (20 patients), were selected to be analyzed by the EndoPredict assay, a second generation gene expression test that combines expression of 8 genes (EP score) with two clinicopathological variables (tumor size and nodal status, EPclin score). Results The EP score classified 15 patients as low-risk and 25 patients as high-risk. EPclin re-classified 5 of the 25 EP high-risk patients into low-risk, resulting in a total of 20 high-risk and 20 low-risk tumors. EP score and MammaPrint score were significantly correlated (p = 0.008). Twelve of 20 samples classified as low-risk by MammaPrint were also low-risk by EP score (60%). 17 of 20 MammaPrint high-risk tumors were also high-risk by EP score. The overall concordance between EP score and MammaPrint was 72.5% (κ = 0.45, (95% CI, 0.182 to 0.718)). EPclin score also correlated with MammaPrint results (p = 0.004). Discrepancies between both tests occurred in 10 cases: 5 MammaPrint low-risk patients were classified as EPclin high-risk and 5 high-risk MammaPrint were classified as low-risk by EPclin and overall concordance of 75% (κ = 0.5, (95% CI, 0.232 to 0.768)). Conclusions This pilot study demonstrates a limited concordance between MammaPrint and EndoPredict. Differences in results could be explained by the inclusion of different gene sets in each platform, the use of different methodology, and the inclusion of clinicopathological parameters, such as tumor size and nodal status, in the EndoPredict test. PMID:28886093

  8. The New IASLC/ATS/ERS Lung Adenocarcinoma Classification: what the surgeon should know

    Science.gov (United States)

    Eguchi, Takashi; Kadota, Kyuichi; Park, Bernard J.; Travis, William D.; Jones, David R.; Adusumilli, Prasad S.

    2014-01-01

    In 2011, a new histologic classification of lung adenocarcinomas was proposed from a joint working group of the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS), based on the recommendation of an international and multidisciplinary panel. This classification proposed a method of comprehensive histologic subtyping (lepidic, acinar, papillary, micropapillary, and solid pattern) based on semi-quantitative assessment of histologic patterns (in 5% increments) with the ultimate goal of choosing a single, predominant pattern. Prognostic subsets could then be described for the classification. Patients with completely resected adenocarcinomas in situ (AIS) and minimally invasive adenocarcinomas (MIA) experienced low risk of recurrence. Patients with micropapillary or solid predominant tumors have a high risk for recurrence or cancer-related death. Patients with acinar and papillary predominant tumors comprise an intermediate-risk group. Herein, we review the outline of the proposed IASLC/ATS/ERS classification, a summary of published validation studies of this new classification and then discuss surgical key issues; we mainly focused on limited resection as an adequate treatment for early-stage lung adenocarcinomas as well as pre- and intraoperative diagnoses. We also review the published studies that identified the importance of histological subtypes in predicting recurrence, both rates and patterns, in early-stage lung adenocarcinomas. This new classification for the most common type of lung cancer is useful for surgeons, as its implementation would require only hematoxylin and eosin (H&E) histology slides