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. Issues surrounding the classification of accounting information

    Directory of Open Access Journals (Sweden)

    Huibrecht Van der Poll

    2011-06-01

    Full Text Available The act of classifying information created by accounting practices is ubiquitous in the accounting process; from recording to reporting, it has almost become second nature. The classification has to correspond to the requirements and demands of the changing environment in which it is practised. Evidence suggests that the current classification of items in financial statements is not keeping pace with the needs of users and the new financial constructs generated by the industry. This study addresses the issue of classification in two ways: by means of a critical analysis of classification theory and practices and by means of a questionnaire that was developed and sent to compilers and users of financial statements. A new classification framework for accounting information in the balance sheet and income statement is proposed.

  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. Cancer classification in the genomic era: five contemporary problems.

    Science.gov (United States)

    Song, Qingxuan; Merajver, Sofia D; Li, Jun Z

    2015-10-19

    Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., "lung cancer" designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor cohorts, have provided not only new insights into the biological diversity of human cancers but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here, we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. (1) How many cancer subtypes are there? (2) How can we evaluate the robustness of a new classification system? (3) How are classification systems affected by intratumor heterogeneity and tumor evolution? (4) How should we interpret cancer subtypes? (5) Can multiple classification systems co-exist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Exploration of these problems is essential for data-driven refinement of cancer classification

  5. Molecular Classification and Correlates in Colorectal Cancer

    OpenAIRE

    Ogino, Shuji; Goel, Ajay

    2008-01-01

    Molecular classification of colorectal cancer is evolving. As our understanding of colorectal carcinogenesis improves, we are incorporating new knowledge into the classification system. In particular, global genomic status [microsatellite instability (MSI) status and chromosomal instability (CIN) status] and epigenomic status [CpG island methylator phenotype (CIMP) status] play a significant role in determining clinical, pathological and biological characteristics of colorectal cancer. In thi...

  6. 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, ...

  7. Cancer survivors. Work related issues.

    Science.gov (United States)

    Schultz, Pamela N; Beck, Martha L; Stava, Charles; Sellin, Rena V

    2002-05-01

    New and more effective treatments for cancer have resulted in individuals living longer with a better quality of life. Many more survivors are employed in the workplace. Cancer is no longer only an issue for survivors and their families; it has become an issue for the employer and the workplace. This article describes survey results of 4,364 long term cancer survivors in which they were asked to respond to items describing their ability to work, job discrimination, and quality of life. Thirty-five percent of survivors were working at the time they completed the survey, and 8.5% considered themselves unable to work. This research has shown that age, gender, ethnic group, and cancer type affected the working status of the survivors. Of survivors continuing to work, 7.3% indicated they had experienced job discrimination. The results indicate most cancer survivors do not perceive employment related problems, and are readily assimilated into the work force. Job discrimination and the ability to work is a quality of life issue.

  8. On the Issue in Classification of Financial Control Types

    Directory of Open Access Journals (Sweden)

    Lvova I. G.

    2014-10-01

    Full Text Available The article is devoted to the issues in classification types (forms of financial supervision, in order to regulate legal budget relationship. The author analyzes the existing in scientific literature approaches to the concept and content of internal and external controls

  9. Gastric cancer: epidemiology, prevention, classification, and treatment

    Directory of Open Access Journals (Sweden)

    Sitarz R

    2018-02-01

    Full Text Available Robert Sitarz,1–3 Małgorzata Skierucha,1,2 Jerzy Mielko,1 G Johan A Offerhaus,3 Ryszard Maciejewski,2 Wojciech P Polkowski1 1Department of Surgical Oncology, Medical University of Lublin, Lublin, Poland; 2Department of Human Anatomy, Medical University of Lublin, Lublin, Poland; 3Department of Pathology, University Medical Centre, Utrecht, The Netherlands Abstract: Gastric cancer is the second most common cause of cancer-related deaths in the world, the epidemiology of which has changed within last decades. A trend of steady decline in gastric cancer incidence rates is the effect of the increased standards of hygiene, conscious nutrition, and Helicobacter pylori eradication, which together constitute primary prevention. Avoidance of gastric cancer remains a priority. However, patients with higher risk should be screened for early detection and chemoprevention. Surgical resection enhanced by standardized lymphadenectomy remains the gold standard in gastric cancer therapy. This review briefly summarizes the most important aspects of gastric cancers, which include epidemiology, risk factors, classification, diagnosis, prevention, and treatment. The paper is mostly addressed to physicians who are interested in updating the state of art concerning gastric carcinoma from easily accessible and credible source. Keywords: gastric cancer, epidemiology, classification, risk factors, treatment

  10. Novelty detection for breast cancer image classification

    Science.gov (United States)

    Cichosz, Pawel; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał; Oleszkiewicz, Witold

    2016-09-01

    Using classification learning algorithms for medical applications may require not only refined model creation techniques and careful unbiased model evaluation, but also detecting the risk of misclassification at the time of model application. This is addressed by novelty detection, which identifies instances for which the training set is not sufficiently representative and for which it may be safer to restrain from classification and request a human expert diagnosis. The paper investigates two techniques for isolated instance identification, based on clustering and one-class support vector machines, which represent two different approaches to multidimensional outlier detection. The prediction quality for isolated instances in breast cancer image data is evaluated using the random forest algorithm and found to be substantially inferior to the prediction quality for non-isolated instances. Each of the two techniques is then used to create a novelty detection model which can be combined with a classification model and used at the time of prediction to detect instances for which the latter cannot be reliably applied. Novelty detection is demonstrated to improve random forest prediction quality and argued to deserve further investigation in medical applications.

  11. Lauren classification and individualized chemotherapy in gastric cancer

    OpenAIRE

    MA, JUNLI; SHEN, HONG; KAPESA, LINDA; ZENG, SHAN

    2016-01-01

    Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histol...

  12. 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…

  13. 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; Silva de Castro, C; 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

    2012-05-01

    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. © 2012 John Wiley & Sons A/S.

  14. 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

  15. Lauren classification and individualized chemotherapy in gastric cancer.

    Science.gov (United States)

    Ma, Junli; Shen, Hong; Kapesa, Linda; Zeng, Shan

    2016-05-01

    Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histological subtypes of gastric cancer proposed by the Lauren classification exhibit a number of distinct clinical and molecular characteristics, including histogenesis, cell differentiation, epidemiology, etiology, carcinogenesis, biological behaviors and prognosis. Gastric cancer exhibits varied sensitivity to chemotherapy drugs and significant heterogeneity; therefore, the disease may be a target for individualized therapy. The Lauren classification may provide the basis for individualized treatment for advanced gastric cancer, which is increasingly gaining attention in the scientific field. However, few studies have investigated individualized treatment that is guided by pathological classification. The aim of the current review is to analyze the two major histological subtypes of gastric cancer, as proposed by the Lauren classification, and to discuss the implications of this for personalized chemotherapy.

  16. [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.

  17. 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

  18. 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.

  19. The classification of osteonecrosis in patients with cancer: validation of a new radiological classification system

    International Nuclear Information System (INIS)

    Niinimäki, T.; Niinimäki, J.; Halonen, J.; Hänninen, P.; Harila-Saari, A.; Niinimäki, R.

    2015-01-01

    Aim: To validate a new, non-joint-specific radiological classification system that is suitable regardless of the site of the osteonecrosis (ON) in patients with cancer. Material and methods: Critical deficiencies in the existing ON classification systems were identified and a new, non-joint-specific radiological classification system was developed. Seventy-two magnetic resonance imaging (MRI) images of patients with cancer and ON lesions were graded, and the validation of the new system was performed by assessing inter- and intra-observer reliability. Results: Intra-observer reliability of ON grading was good or very good, with kappa values of 0.79–0.86. Interobserver agreement was lower but still good, with kappa values of 0.62–0.77. Ninety-eight percent of all intra- or interobserver differences were within one grade. Interobserver reliability of assessing the location of ON was very good, with kappa values of 0.93–0.98. Conclusion: All the available radiological ON classification systems are joint specific. This limitation has spurred the development of multiple systems, which has led to the insufficient use of classifications in ON studies among patients with cancer. The introduced radiological classification system overcomes the problem of joint-specificity, was found to be reliable, and can be used to classify all ON lesions regardless of the affected site. - Highlights: • Patients with cancer may have osteonecrosis lesions at multiple sites. • There is no non-joint-specific osteonecrosis classification available. • We introduced a new non-joint-specific osteonecrosis classification. • The validation was performed by assessing inter- and intra-observer reliability. • The classification was reliable and could be used regardless of the affected site.

  20. 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.

  1. 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...

  2. A Classification Framework Applied to Cancer Gene Expression Profiles

    Directory of Open Access Journals (Sweden)

    Hussein Hijazi

    2013-01-01

    Full Text Available Classification of cancer based on gene expression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM, bagging, and random forest on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression increase the prediction accuracy as compared to using gene expression alone.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

    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 < 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.)

  4. 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.)

  5. Battling with breast cancer - addressing the issues

    Energy Technology Data Exchange (ETDEWEB)

    Amin, S; Wahid, N; Wasim, B; Tabassum, S [Patel Hospital Gulshan-e-Iqbal, Karachi (Pakistan)

    2011-06-15

    In the background of the current situation of breast cancer in Pakistan, with its rising incidence and mortality, non afford ability and inaccessibility to screening, diagnosis and treatment, Patel Hospital took up the task of addressing these issues at a local level, by initiating an annual free breast camp in the year 2006. In 2008 an inclusion criteria was defined to focus on high risk women for breast cancer. A comparative analysis over a period of three years was done. In the focused camps, in which 28% patients were found to have a positive family history. Most women were symptomatic. Total 11 patients were diagnosed to have cancer after evaluation. Six patients underwent definitive treatment. A problem with lack of awareness, regarding screening and treatment protocols was identified. Family history seems to be an important risk factor in our set up signifying the need to introduce extensive screening programmes. (author)

  6. Battling with breast cancer - addressing the issues

    International Nuclear Information System (INIS)

    Amin, S.; Wahid, N.; Wasim, B.; Tabassum, S.

    2011-01-01

    In the background of the current situation of breast cancer in Pakistan, with its rising incidence and mortality, non afford ability and inaccessibility to screening, diagnosis and treatment, Patel Hospital took up the task of addressing these issues at a local level, by initiating an annual free breast camp in the year 2006. In 2008 an inclusion criteria was defined to focus on high risk women for breast cancer. A comparative analysis over a period of three years was done. In the focused camps, in which 28% patients were found to have a positive family history. Most women were symptomatic. Total 11 patients were diagnosed to have cancer after evaluation. Six patients underwent definitive treatment. A problem with lack of awareness, regarding screening and treatment protocols was identified. Family history seems to be an important risk factor in our set up signifying the need to introduce extensive screening programmes. (author)

  7. Influence of nuclei segmentation on breast cancer malignancy classification

    Science.gov (United States)

    Jelen, Lukasz; Fevens, Thomas; Krzyzak, Adam

    2009-02-01

    Breast Cancer is one of the most deadly cancers affecting middle-aged women. Accurate diagnosis and prognosis are crucial to reduce the high death rate. Nowadays there are numerous diagnostic tools for breast cancer diagnosis. In this paper we discuss a role of nuclear segmentation from fine needle aspiration biopsy (FNA) slides and its influence on malignancy classification. Classification of malignancy plays a very important role during the diagnosis process of breast cancer. Out of all cancer diagnostic tools, FNA slides provide the most valuable information about the cancer malignancy grade which helps to choose an appropriate treatment. This process involves assessing numerous nuclear features and therefore precise segmentation of nuclei is very important. In this work we compare three powerful segmentation approaches and test their impact on the classification of breast cancer malignancy. The studied approaches involve level set segmentation, fuzzy c-means segmentation and textural segmentation based on co-occurrence matrix. Segmented nuclei were used to extract nuclear features for malignancy classification. For classification purposes four different classifiers were trained and tested with previously extracted features. The compared classifiers are Multilayer Perceptron (MLP), Self-Organizing Maps (SOM), Principal Component-based Neural Network (PCA) and Support Vector Machines (SVM). The presented results show that level set segmentation yields the best results over the three compared approaches and leads to a good feature extraction with a lowest average error rate of 6.51% over four different classifiers. The best performance was recorded for multilayer perceptron with an error rate of 3.07% using fuzzy c-means segmentation.

  8. Gender and cultural issues in psychiatric nosological classification systems.

    Science.gov (United States)

    van de Water, Tanya; Suliman, Sharain; Seedat, Soraya

    2016-08-01

    Much has changed since the two dominant mental health nosological systems, the International Classification of Diseases (ICD) and the Diagnostic and Statistical Manual of Mental Disorders (DSM), were first published in 1900 and 1952, respectively. Despite numerous modifications to stay up to date with scientific and cultural changes (eg, exclusion of homosexuality as a disorder) and to improve the cultural sensitivity of psychiatric diagnoses, the ICD and DSM have only recently renewed attempts at harmonization. Previous nosological iterations demonstrate the oscillation in the importance placed on the biological focus, highlighting the tension between a gender- and culture-free nosology (solely biological) and a contextually relevant understanding of mental illness. In light of the release of the DSM 5, future nosological systems, such as the ICD 11, scheduled for release in 2017, and the Research Development Criteria (RDoC), can learn from history and apply critiques. This article aims to critically consider gender and culture in previous editions of the ICD and DSM to inform forthcoming classifications.

  9. Cancer classification using the Immunoscore: a worldwide task force.

    Science.gov (United States)

    Galon, Jérôme; Pagès, Franck; Marincola, Francesco M; Angell, Helen K; Thurin, Magdalena; Lugli, Alessandro; Zlobec, Inti; Berger, Anne; Bifulco, Carlo; Botti, Gerardo; Tatangelo, Fabiana; Britten, Cedrik M; Kreiter, Sebastian; Chouchane, Lotfi; Delrio, Paolo; Arndt, Hartmann; Asslaber, Martin; Maio, Michele; Masucci, Giuseppe V; Mihm, Martin; Vidal-Vanaclocha, Fernando; Allison, James P; Gnjatic, Sacha; Hakansson, Leif; Huber, Christoph; Singh-Jasuja, Harpreet; Ottensmeier, Christian; Zwierzina, Heinz; Laghi, Luigi; Grizzi, Fabio; Ohashi, Pamela S; Shaw, Patricia A; Clarke, Blaise A; Wouters, Bradly G; Kawakami, Yutaka; Hazama, Shoichi; Okuno, Kiyotaka; Wang, Ena; O'Donnell-Tormey, Jill; Lagorce, Christine; Pawelec, Graham; Nishimura, Michael I; Hawkins, Robert; Lapointe, Réjean; Lundqvist, Andreas; Khleif, Samir N; Ogino, Shuji; Gibbs, Peter; Waring, Paul; Sato, Noriyuki; Torigoe, Toshihiko; Itoh, Kyogo; Patel, Prabhu S; Shukla, Shilin N; Palmqvist, Richard; Nagtegaal, Iris D; Wang, Yili; D'Arrigo, Corrado; Kopetz, Scott; Sinicrope, Frank A; Trinchieri, Giorgio; Gajewski, Thomas F; Ascierto, Paolo A; Fox, Bernard A

    2012-10-03

    Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J

  10. Issues reporting PSA in prostate cancer

    International Nuclear Information System (INIS)

    Lange, Paul H.

    1996-01-01

    The National Cancer Institute Prostate; Lung; Colon; Ovarian Cancer Screening (PLCO) project is a multi-center trial developed to investigate the effectiveness of DRE and PSA testing in the early detection and outcome of patients with prostate cancer. Accordingly, the Prostate Cancer Intervention versus Observation Trial (PIVOT) has been launched and is a randomized trial comparing radical prostatectomy versus expectant management for ALCaP. PSA: Initially PSA was thought to be of little value for diagnosis because 20% of men undergoing radical prostatectomy have 'normal' PSA and patients with apparently only symptomatic BPH have 'elevated' levels as follows: 4-10 ng/ml (Tandem-R) - 20%, >10 ng/ml -3%. Yet, PSA has looked attractive as a diagnostic tool in many studies; for example, when PSA was used in a screening approach as the first test which then drove further evaluation (Catalona, Brawer). It was shown that the positive predictive value for PSA's between 4 and 10 is approximately 20% and > 10 approximately 55%. The value of serial PSA's (velocity) is unknown but is under intense study: one major issue is determination of what represents a significant rise (details to be presented). Studies have also revealed that a DRE and PSA are important for optimal results. About 18% of clinically detectable cancers are only DRE positive while about 25 - 30% are only PSA positive. When both a DRE and PSA are used together, very few clinically apparent cancers are missed (3-5%). Recent ROC curves suggest that 4 ng/ml is reasonable. Recently, PSA values for men without apparent cancer were stratified by age, and taking the 2SD, age specific reference values were generated as follows: age 40-49 (0-2.5 ng/ml), 50-59 (0-3.5), 60-69 (0-4.5), 70-70 (0-6.5). Finally, there is the issue about different PSA assays regarding the compatabilities/reliability of the upper limit of normal and serial values. Much of the confusion is because there is no international PSA standard and

  11. Classification framework of knowledge transfer issues across value networks

    NARCIS (Netherlands)

    Bagheri, S.; Kusters, R.J.; Trienekens, J.J.M.; van der Zandt, Hugo; Cavalieri, S.; Ceretti, E.; Tolio, T.; Pezzotta, G.

    2016-01-01

    Co-creating integrated solutions with customers requires collaboration of different partners within a value network. In this emerging context, knowledge is considered as a foundation for value co-creation. Therefore, identifying different types of issues, with which value network actors in knowledge

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

    African Journals Online (AJOL)

    Objectives: Bladder cancer (BCA) is aworldwide disease and shows a wide range of geographical variation. The aim of this study is to analyze the prevalence of schistosomal and non-schistosomal associated BCA as well as compare our findings with the 2004 WHO consensus classification of urothelial neoplasms and ...

  13. Classification of mitocans, anti-cancer drugs acting on mitochondria

    Czech Academy of Sciences Publication Activity Database

    Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

    2013-01-01

    Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Gene tics ; Molecular Biology Impact factor: 3.524, year: 2013

  14. Classification of mitocans, anti-cancer drugs acting on mitochondria

    Czech Academy of Sciences Publication Activity Database

    Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

    2013-01-01

    Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.524, year: 2013

  15. 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.

  16. Gastric cancer: epidemiology, prevention, classification, and treatment

    OpenAIRE

    Sitarz, Robert; Skierucha, Małgorzata; Mielko, Jerzy; Offerhaus, G Johan A; Maciejewski, Ryszard; Polkowski, Wojciech P

    2018-01-01

    Robert Sitarz,1–3 Małgorzata Skierucha,1,2 Jerzy Mielko,1 G Johan A Offerhaus,3 Ryszard Maciejewski,2 Wojciech P Polkowski1 1Department of Surgical Oncology, Medical University of Lublin, Lublin, Poland; 2Department of Human Anatomy, Medical University of Lublin, Lublin, Poland; 3Department of Pathology, University Medical Centre, Utrecht, The Netherlands Abstract: Gastric cancer is the second most common cause of cancer-related deaths in the world, the epidemiology of which has ch...

  17. Classification of alarm processing techniques and human performance issues

    International Nuclear Information System (INIS)

    Kim, I.S.; O'Hara, J.M.

    1993-01-01

    Human factors reviews indicate that conventional alarm systems based on the one sensor, one alarm approach, have many human engineering deficiencies, a paramount example being too many alarms during major disturbances. As an effort to resolve these deficiencies, various alarm processing systems have been developed using different techniques. To ensure their contribution to operational safety, the impacts of those systems on operating crew performance should be carefully evaluated. This paper briefly reviews some of the human factors research issues associated with alarm processing techniques and then discusses a framework with which to classify the techniques. The dimensions of this framework can be used to explore the effects of alarm processing systems on human performance

  18. Classification of alarm processing techniques and human performance issues

    Energy Technology Data Exchange (ETDEWEB)

    Kim, I.S.; O' Hara, J.M.

    1993-01-01

    Human factors reviews indicate that conventional alarm systems based on the one sensor, one alarm approach, have many human engineering deficiencies, a paramount example being too many alarms during major disturbances. As an effort to resolve these deficiencies, various alarm processing systems have been developed using different techniques. To ensure their contribution to operational safety, the impacts of those systems on operating crew performance should be carefully evaluated. This paper briefly reviews some of the human factors research issues associated with alarm processing techniques and then discusses a framework with which to classify the techniques. The dimensions of this framework can be used to explore the effects of alarm processing systems on human performance.

  19. Classification of alarm processing techniques and human performance issues

    Energy Technology Data Exchange (ETDEWEB)

    Kim, I.S.; O`Hara, J.M.

    1993-05-01

    Human factors reviews indicate that conventional alarm systems based on the one sensor, one alarm approach, have many human engineering deficiencies, a paramount example being too many alarms during major disturbances. As an effort to resolve these deficiencies, various alarm processing systems have been developed using different techniques. To ensure their contribution to operational safety, the impacts of those systems on operating crew performance should be carefully evaluated. This paper briefly reviews some of the human factors research issues associated with alarm processing techniques and then discusses a framework with which to classify the techniques. The dimensions of this framework can be used to explore the effects of alarm processing systems on human performance.

  20. 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...... in patients with cancer, IASP NeuPSIG diagnostic criteria adaptation and assessment, and standardized PRO assessment for NP screening. Median consensus scores (MED) and interquartile ranges (IQR) were calculated to measure expert consensus after both rounds. Twenty-nine experts answered, and good agreement...... was proposed. Clinical research on PRO in the screening phase and on the application of the algorithm will be needed to examine their effectiveness in classifying NP in cancer patients....

  1. 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.

  2. Cancer classification using the Immunoscore: a worldwide task force

    Directory of Open Access Journals (Sweden)

    Galon Jérôme

    2012-10-01

    Full Text Available Abstract Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification summarizes data on tumor burden (T, presence of cancer cells in draining and regional lymph nodes (N and evidence for metastases (M. However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the ‘Immunoscore’ into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of

  3. Impact of full field digital mammography on the classification and mammographic characteristics of interval breast cancers

    Energy Technology Data Exchange (ETDEWEB)

    Knox, Mark, E-mail: marktknox@gmail.com; O’Brien, Angela, E-mail: angelaobrien@doctors.org.uk; Szabó, Endre, E-mail: endrebacsi@freemail.hu; Smith, Clare S., E-mail: csmith@mater.ie; Fenlon, Helen M., E-mail: helen.fenlon@cancerscreening.ie; McNicholas, Michelle M., E-mail: michelle.mcnicholas@cancerscreening.ie; Flanagan, Fidelma L., E-mail: fidelma.flanagan@cancerscreening.ie

    2015-06-15

    Highlights: • Digital mammography has changed the presentation of interval breast cancer. • Less interval breast cancers are associated with microcalcifications following FFDM. • Interval breast cancer audit remains a key feature of any breast screening program. - Abstract: Objective: Full field digital mammography (FFDM) is increasingly replacing screen film mammography (SFM) in breast screening programs. Interval breast cancers are an issue in all screening programs and the purpose of our study is to assess the impact of FFDM on the classification of interval breast cancers at independent blind review and to compare the mammographic features of interval cancers at FFDM and SFM. Materials and methods: This study included 138 cases of interval breast cancer, 76 following an FFDM screening examination and 62 following screening with SFM. The prior screening mammogram was assessed by each of five consultant breast radiologists who were blinded to the site of subsequent cancer. Subsequent review of the diagnostic mammogram was performed and cases were classified as missed, minimal signs, occult or true interval. Mammographic features of the interval cancer at diagnosis and any abnormality identified on the prior screening mammogram were recorded. Results: The percentages of cancers classified as missed at FFDM and SFM did not differ significantly, 10.5% (8 of 76) at FFDM and 8.1% (5 of 62) at SFM (p = .77). There were significantly less interval cancers presenting as microcalcifications (alone or in association with another abnormality) following screening with FFDM, 16% (12 of 76) than following a SFM examination, 32% (20 of 62) (p = .02). Conclusion: Interval breast cancers continue to pose a problem at FFDM. The switch to FFDM has changed the mammographic presentation of interval breast cancer, with less interval cancers presenting in association with microcalcifications.

  4. Impact of full field digital mammography on the classification and mammographic characteristics of interval breast cancers

    International Nuclear Information System (INIS)

    Knox, Mark; O’Brien, Angela; Szabó, Endre; Smith, Clare S.; Fenlon, Helen M.; McNicholas, Michelle M.; Flanagan, Fidelma L.

    2015-01-01

    Highlights: • Digital mammography has changed the presentation of interval breast cancer. • Less interval breast cancers are associated with microcalcifications following FFDM. • Interval breast cancer audit remains a key feature of any breast screening program. - Abstract: Objective: Full field digital mammography (FFDM) is increasingly replacing screen film mammography (SFM) in breast screening programs. Interval breast cancers are an issue in all screening programs and the purpose of our study is to assess the impact of FFDM on the classification of interval breast cancers at independent blind review and to compare the mammographic features of interval cancers at FFDM and SFM. Materials and methods: This study included 138 cases of interval breast cancer, 76 following an FFDM screening examination and 62 following screening with SFM. The prior screening mammogram was assessed by each of five consultant breast radiologists who were blinded to the site of subsequent cancer. Subsequent review of the diagnostic mammogram was performed and cases were classified as missed, minimal signs, occult or true interval. Mammographic features of the interval cancer at diagnosis and any abnormality identified on the prior screening mammogram were recorded. Results: The percentages of cancers classified as missed at FFDM and SFM did not differ significantly, 10.5% (8 of 76) at FFDM and 8.1% (5 of 62) at SFM (p = .77). There were significantly less interval cancers presenting as microcalcifications (alone or in association with another abnormality) following screening with FFDM, 16% (12 of 76) than following a SFM examination, 32% (20 of 62) (p = .02). Conclusion: Interval breast cancers continue to pose a problem at FFDM. The switch to FFDM has changed the mammographic presentation of interval breast cancer, with less interval cancers presenting in association with microcalcifications

  5. 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.

  6. Using fuzzy association rule mining in cancer classification

    International Nuclear Information System (INIS)

    Mahmoodian, Hamid; Marhaban, M.H.; Abdulrahim, Raha; Rosli, Rozita; Saripan, Iqbal

    2011-01-01

    Full text: The classification of the cancer tumors based on gene expression profiles has been extensively studied in numbers of studies. A wide variety of cancer datasets have been implemented by the various methods of gene selec tion and classification to identify the behavior of the genes in tumors and find the relationships between them and outcome of diseases. Interpretability of the model, which is developed by fuzzy rules and linguistic variables in this study, has been rarely considered. In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. The results show that fuzzy classifier can classify the tumors with high performance while presenting the relationships between the genes by linguistic variables

  7. [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.

  8. X-ray diagnosis of esophageal cancer and application of Borrmann's classification

    International Nuclear Information System (INIS)

    Chin, Soo Yil

    1985-01-01

    In 126 cases and who were diagnosed as esophageal cancer and treated by radiation at Cancer Research Hospital, K. A. E. R. I., from January 1974 to July 1979, a study on the x-ray diagnosis of esophageal cancer was carried out mainly as to the type classification. The ordinary classification od esophageal cancer by x-ray picture was reviewed and Borrmann's classification using gastric cancer was tried to apply to the macroscopic classification of esophageal cancer, and also the application of this classification to x-ray diagnosis was discussed. And the effect of radiotherapy as to each type of cancer according to the ordinary x-ray classification and Borrmann's classification was studied too. The results were as follows: 1. The ordinary x-ray classification was not simple, because the degree of progression of cancer, difference of mural invasion, and position and method of radiography could make misinterpretation of the type of cancer and the therapeutic effect by radiation as to each type according to this classification did not represent a significant characteristic too, although the radiation was most effective in the polypoidal type and least effective in funnel type. 2. The Borrmann's classification was relatively easy even on the radiogram because of little overlapping between each type and the type became more evident on the resected specimen after operation. And also some correlation was recognized between the type of Borrmann's classification and radiotherapeutic effect. The effect was best in type I and It was gradually decreased in type II, III, and IV in the other. The radiotherapy was ineffective in about three quarters of type IV. 3. The Borrmann's classification is now employed to the carcinoma of large bowel, as well as to the gastric cancer. If it is applied to the esophageal cancer, the macroscopic classification for the cancer of digestive tract can be systemized and it will be convenient in clinical study.

  9. 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.

  10. 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.

  11. Side effects of cancer therapies. International classification and documentation systems

    International Nuclear Information System (INIS)

    Seegenschmiedt, M.H.

    1998-01-01

    The publication presents and explains verified, international classification and documentation systems for side effects induced by cancer treatments, applicable in general and clinical practice and clinical research, and covers in a clearly arranged manner the whole range of treatments, including acute and chronic side effects of chemotherapy and radiotherapy, surgery, or combined therapies. The book fills a long-felt need in tumor documentation and is a major contribution to quality assurance in clinical oncology in German-speaking countries. As most parts of the book are bilingual, presenting German and English texts and terminology, it satisfies the principles of interdisciplinarity and internationality. The tabulated form chosen for presentation of classification systems and criteria facilitate the user's approach as well as application in daily work. (orig./CB) [de

  12. 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%.

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. Breast cancer molecular subtype classification using deep features: preliminary results

    Science.gov (United States)

    Zhu, Zhe; Albadawy, Ehab; Saha, Ashirbani; Zhang, Jun; Harowicz, Michael R.; Mazurowski, Maciej A.

    2018-02-01

    Radiogenomics is a field of investigation that attempts to examine the relationship between imaging characteris- tics of cancerous lesions and their genomic composition. This could offer a noninvasive alternative to establishing genomic characteristics of tumors and aid cancer treatment planning. While deep learning has shown its supe- riority in many detection and classification tasks, breast cancer radiogenomic data suffers from a very limited number of training examples, which renders the training of the neural network for this problem directly and with no pretraining a very difficult task. In this study, we investigated an alternative deep learning approach referred to as deep features or off-the-shelf network approach to classify breast cancer molecular subtypes using breast dynamic contrast enhanced MRIs. We used the feature maps of different convolution layers and fully connected layers as features and trained support vector machines using these features for prediction. For the feature maps that have multiple layers, max-pooling was performed along each channel. We focused on distinguishing the Luminal A subtype from other subtypes. To evaluate the models, 10 fold cross-validation was performed and the final AUC was obtained by averaging the performance of all the folds. The highest average AUC obtained was 0.64 (0.95 CI: 0.57-0.71), using the feature maps of the last fully connected layer. This indicates the promise of using this approach to predict the breast cancer molecular subtypes. Since the best performance appears in the last fully connected layer, it also implies that breast cancer molecular subtypes may relate to high level image features

  18. 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...

  19. 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...

  20. Resolving Radiological Classification and Release Issues for Many DOE Solid Wastes and Salvageable Materials

    Energy Technology Data Exchange (ETDEWEB)

    Hochel, R.C.

    1999-06-14

    The cost effective radiological classification and disposal of solid materials with potential volume contamination, in accordance with applicable U.S. Department of Energy (DOE) Orders, suffers from an inability to unambiguously distinguish among transuranic waste, low-level waste, and unconditional-release materials. Depending on the classification, disposal costs can vary by a hundred-fold. But in many cases, the issues can be easily resolved by a combination of process information, some simple measurements, and calculational predictions from a computer model for radiation shielding.The proper classification and disposal of many solid wastes requires a measurement regime that is able to show compliance with a variety of institutional and regulatory contamination limits. Although this is not possible for all solid wastes, there are many that do lend themselves to such measures. Several examples are discussed which demonstrate the possibilities, including one which was successfully applied to bulk contamination.The only barriers to such broader uses are the slow-to-change institutional perceptions and procedures. For many issues and materials, the measurement tools are available; they need only be applied.

  1. Resolving Radiological Classification and Release Issues for Many DOE Solid Wastes and Salvageable Materials

    International Nuclear Information System (INIS)

    Hochel, R.C.

    1999-01-01

    The cost effective radiological classification and disposal of solid materials with potential volume contamination, in accordance with applicable U.S. Department of Energy (DOE) Orders, suffers from an inability to unambiguously distinguish among transuranic waste, low-level waste, and unconditional-release materials in a generic way allowing in-situ measurement and verification. Depending on a material''s classification, disposal costs can vary by a hundred-fold. With these large costs at risk, the issues involved in making defensible decisions are ripe for closer scrutiny. In many cases, key issues can be easily resolved by a combination of process information, some simple measurements, and calculational predictions from a computer model for radiation shielding. The proper classification and disposal of many solid wastes requires a measurement regime that is able to show compliance with a variety of institutional and regulatory contamination limits. Ultimate responsibility for this, of course, rests with radiological control or health physics organization of the individual site, but there are many measurements which can be performed by operations and generation organizations to simplify the process and virtually guarantee acceptance. Although this is not possible for all potential solid wastes, there are many that do lend themselves to such measures, particularly some of large volumes and realizable cost savings. Mostly what is needed for this to happen are a few guiding rules, measurement procedures, and cross checks for potential pitfalls. Several examples are presented here and discussed that demonstrate the possibilities, including one which was successfully applied to bulk contamination

  2. Resolving Radiological Classification and Release Issues for Many DOE Solid Wastes and Salvageable Materials

    International Nuclear Information System (INIS)

    Hochel, R.C.

    1999-01-01

    The cost effective radiological classification and disposal of solid materials with potential volume contamination, in accordance with applicable U.S. Department of Energy (DOE) Orders, suffers from an inability to unambiguously distinguish among transuranic waste, low-level waste, and unconditional-release materials. Depending on the classification, disposal costs can vary by a hundred-fold. But in many cases, the issues can be easily resolved by a combination of process information, some simple measurements, and calculational predictions from a computer model for radiation shielding.The proper classification and disposal of many solid wastes requires a measurement regime that is able to show compliance with a variety of institutional and regulatory contamination limits. Although this is not possible for all solid wastes, there are many that do lend themselves to such measures. Several examples are discussed which demonstrate the possibilities, including one which was successfully applied to bulk contamination.The only barriers to such broader uses are the slow-to-change institutional perceptions and procedures. For many issues and materials, the measurement tools are available; they need only be applied

  3. Controversial Issues in Thyroid Cancer Management.

    Science.gov (United States)

    Tuttle, R Michael

    2018-04-13

    The lack of prospective randomized clinical trials for most management topics in differentiated thyroid cancer force us to make management recommendations based on retrospective observational data which is often incomplete, subject to selection bias, and conflicting. Therefore, it is not surprising that many aspects of thyroid cancer management remain controversial and not well defined. This review will examine the controversies surrounding three important topics in thyroid cancer management: (1) the option of thyroid lobectomy as initial therapy for thyroid cancer, (2) the proper use of preoperative neck imaging to optimize the completeness of the initial surgical procedure, and (3) the selective use RAI therapy as remnant ablation, adjuvant treatment or treatment of known persistent/recurrent disease. As thyroid cancer management moves toward a much more risk adapted approach to personalized management recommendations, clinicians and patients must balance the risks and benefits of the potential management options to arrive at a management plan that is optimized based on both patient preferences/values and the philosophy/experience of the local disease management team. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

  4. Molecular diagnosis of prostate cancer: Topical issues

    Directory of Open Access Journals (Sweden)

    E. N. Knyazev

    2014-12-01

    Full Text Available Prostate cancer (PC is the second most common cancer and the fifth highest malignancy mortality rate in men worldwide. Although PC is detectable in 15-20% of men during life, its death risk is only about 3%. This means that not all PC cases require the same management tactics. The given review analyzes the current investigations searching for molecular biological markers to predict the course of PC and to choose its treatment policy, including that in the development of resistance to androgen-deprivation therapy.

  5. Issues in cervical cancer incidence and treatment in HIV.

    Science.gov (United States)

    Einstein, Mark H; Phaëton, Rébécca

    2010-09-01

    Cervical disease burden continues to be especially high in HIV-infected women, even in the era of effective antiretroviral medications. This review discusses the multiple issues surrounding HIV-associated cervical cancer. Also, the unique treatment-related issues in HIV-associated cervical cancer are addressed. The incidence of invasive cervical cancer has remained stable in industrialized nations; however, it is only estimated in developing countries secondary to a relative lack of data collection and registries. Trends in HIV-associated cervical cancer have changed in the highly active antiretroviral therapy (HAART) era. Recent molecular pathways suggest that the natural progression of human papillomavirus infection, the causal agent in all cervical cancers, may be related to immune system dysfunction as well as HIV/human papillomavirus synergistic mechanisms. When highly active retroviral therapies are used, invasive cervical cancer treatments are impacted by concomitant drug toxicities that could potentially limit therapeutic benefit of either HAART or the standard of care treatment for locally advanced cervical cancer, concomitant chemoradiotherapy. The significance and care of the patient with invasive cervical cancer is becoming a geographically relevant phenomenon such that it may be time to re-address the global definition. Further studies in treatment issues and drug-drug interactions with cervical cancer treatments in the setting of HIV are paramount.

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

    OpenAIRE

    Nahid, Abdullah-Al; Kong, Yinan

    2017-01-01

    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 w...

  7. Gene selection for cancer classification with the help of bees.

    Science.gov (United States)

    Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

    2016-08-10

    Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

  8. Nutrition therapy issues in esophageal cancer.

    Science.gov (United States)

    Miller, Keith R; Bozeman, Matthew C

    2012-08-01

    Esophageal cancer has traditionally been a disease with poor long term outcomes in terms of both survival and quality of life. In combination with surgical and pharmacologic therapy, nutrition support has been demonstrated to improve patient tolerance of treatment, quality of life, and longterm outcomes. An aggressive multi-disciplinary approach is warranted with nutrition support remaining a cornerstone in management. Historically, nutrition support has focused on adequate caloric provision to prevent weight loss and allow for tolerance of treatment regimens. Alterations in metabolism occur in these patients making their use of available calories inefficient and the future of nutritional support may lie in the ability to alter this deranged metabolism. The purpose of this article is to review the current literature surrounding the etiology, treatment, and role of nutrition support in improving outcomes in esophageal cancer.

  9. Management of endometrial cancer: issues and controversies.

    Science.gov (United States)

    Bogani, G; Dowdy, S C; Cliby, W A; Ghezzi, F; Rossetti, D; Frigerio, L; Mariani, A

    2016-01-01

    Although endometrial cancer (EC) is the most common gynecologic cancer in developed countries, several aspects of its management are still controversial. In particular, the need to perform lymphadenectomy represents an important matter of discussion. Because of the discordant results in the literature, it is still not possible to draft any definitive conclusions regarding the therapeutic value of lymph node dissection. The present review discusses the role of lymphadenectomy in the setting of EC, risk factors for lymphatic spread, identification of patients at risk for lymph node dissemination, and the current evidence for adjuvant therapies in patients with positive nodes. Reasons for the difficulty in demonstrating any therapeutic value of pelvic and para-aortic lymphadenectomy are also discussed.

  10. Silica and lung cancer: a controversial issue.

    Science.gov (United States)

    Pairon, J C; Brochard, P; Jaurand, M C; Bignon, J

    1991-06-01

    The role of crystalline silica in lung cancer has long been the subject of controversy. In this article, we review the main experimental and epidemiological studies dealing with this problem. Some evidence for a genotoxic potential of crystalline silica has been obtained in the rare in vitro studies published to date. In vivo studies have shown that crystalline silica is carcinogenic in the rat; the tumour types appear to vary according to the route of administration. In addition, an association between carcinogenic and fibrogenic potency has been observed in various animal species exposed to crystalline silica. An excess of lung cancer related to occupational exposure to crystalline silica is reported in many epidemiological studies, regardless of the presence of silicosis. However, most of these studies are difficult to interpret because they do not correctly take into account associated carcinogens such as tobacco smoke and other occupational carcinogens. An excess of lung cancer is generally reported in studies based on silicosis registers. Overall, experimental and human studies suggest an association between exposure to crystalline silica and an excess of pulmonary malignancies. Although the data available are not sufficient to establish a clear-cut causal relationship in humans, an association between the onset of pneumoconiosis and pulmonary malignancies is probable. In contrast, experimental observations have given rise to a pathophysiological mechanism that might account for a putative carcinogenic potency of crystalline silica.

  11. Vitamins and cancer prevention: issues and dilemmas.

    Science.gov (United States)

    Young, V R; Newberne, P M

    1981-03-01

    Vitamins are a class of organic compounds that are components of an adequate diet. They or their derivatives function as coenzymes, cellular antioxidants, and/or regulators of gene expression. Fourteen vitamins are recognized in human nutrition (Vitamins A, D, E, K, B1, B2, B6, B12, C, niacin, folacin, pantothenic acid, biotin, choline), with deficiencies or excesses in intake leading to changes in protein, nucleic acid, carbohydrates, fat and/or mineral metabolism. Thus, the integrity of physiological systems, including those associated with detoxification, cellular repair, immune processes, and neural and endocrine function, depends upon the nutritional and vitamin status of the host. For these reasons, it may be anticipated that the adequacy of the vitamin supply to cells and tissues would affect the development, progress, and outcome of cancers. In this review, the definition and functions of and requirements and recommended allowance for vitamins are discussed briefly before exploring the evidence, largely from studies in experimental animals, that indicates the nature of the link between vitamins and cancer. Although evidence based on studies in animal systems reveals that vitamin intake and status can modulate the outcome of experimental carcinogenesis, the findings are often conflicting and difficult to interpret. Furthermore, it is not yet possible to develop a suitable prediction of the role of the individual vitamins in tumor development. The significance of these observations for human nutrition and cancer prevention, particularly in reference to ascorbic acid (vitamin C), vitamin E, and B-complex vitamins is considered. Vitamin A and retinoid compounds are discussed elsewhere in the symposium. The many popular misconceptions and unsound advice concerning vitamins and health, including "fake" vitamins-pangamic acid ("vitamin B15") and laetrile ("vitamin B17")-are also discussed. On the basis of current evidence, it would be inappropriate to recommend

  12. 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.

  13. Resolving Radiological Classification and Release Issues for Many DOE Solid Wastes and Salvageable Materials

    Energy Technology Data Exchange (ETDEWEB)

    Hochel, R.C.

    1999-11-19

    The cost effective radiological classification and disposal of solid materials with potential volume contamination, in accordance with applicable U.S. Department of Energy (DOE) Orders, suffers from an inability to unambiguously distinguish among transuranic waste, low-level waste, and unconditional-release materials in a generic way allowing in-situ measurement and verification. Depending on a material''s classification, disposal costs can vary by a hundred-fold. With these large costs at risk, the issues involved in making defensible decisions are ripe for closer scrutiny. In many cases, key issues can be easily resolved by a combination of process information, some simple measurements, and calculational predictions from a computer model for radiation shielding. The proper classification and disposal of many solid wastes requires a measurement regime that is able to show compliance with a variety of institutional and regulatory contamination limits. Ultimate responsibility for this, of course, rests with radiological control or health physics organization of the individual site, but there are many measurements which can be performed by operations and generation organizations to simplify the process and virtually guarantee acceptance. Although this is not possible for all potential solid wastes, there are many that do lend themselves to such measures, particularly some of large volumes and realizable cost savings. Mostly what is needed for this to happen are a few guiding rules, measurement procedures, and cross checks for potential pitfalls. Several examples are presented here and discussed that demonstrate the possibilities, including one which was successfully applied to bulk contamination.

  14. 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

  15. [Psychosocial issues of long-term cancer survivors].

    Science.gov (United States)

    Weis, J; Faller, H

    2012-04-01

    Although cancer incidence rates are increasing, recent statistical studies suggest that cancer patients are showing higher cure rates as well as improved overall survival rates for most cancer locations. These advances are explained by improved strategies in early diagnoses as well as improved cancer therapies. Therefore, the number of long-term cancer survivors has also increased, but only few studies, especially within the last years, have focused on psychosocial issues of this subgroup. Some studies show that overall quality of life of long-term cancer survivors is quite high and comparable to that of the normal population. Nevertheless, a substantial percentage of former patients shows reduced quality of life and suffers from various sequelae of cancer and its treatment. This review focuses on the most common psychosocial issue of long-term survivors such as reduced psychological wellbeing, neuropsychological deficits and cancer-related fatigue syndrome. Finally, recommendations for problem-oriented interventions as well as improvement of psychosocial care of long-term survivors are given.

  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. Three-class classification in computer-aided diagnosis of breast cancer by support vector machine

    Science.gov (United States)

    Sun, Xuejun; Qian, Wei; Song, Dansheng

    2004-05-01

    Design of classifier in computer-aided diagnosis (CAD) scheme of breast cancer plays important role to its overall performance in sensitivity and specificity. Classification of a detected object as malignant lesion, benign lesion, or normal tissue on mammogram is a typical three-class pattern recognition problem. This paper presents a three-class classification approach by using two-stage classifier combined with support vector machine (SVM) learning algorithm for classification of breast cancer on mammograms. The first classification stage is used to detect abnormal areas and normal breast tissues, and the second stage is for classification of malignant or benign in detected abnormal objects. A series of spatial, morphology and texture features have been extracted on detected objects areas. By using genetic algorithm (GA), different feature groups for different stage classification have been investigated. Computerized free-response receiver operating characteristic (FROC) and receiver operating characteristic (ROC) analyses have been employed in different classification stages. Results have shown that obvious performance improvement in both sensitivity and specificity was observed through proposed classification approach compared with conventional two-class classification approaches, indicating its effectiveness in classification of breast cancer on mammograms.

  18. Detection and classification of Breast Cancer in Wavelet Sub-bands of Fractal Segmented Cancerous Zones.

    Science.gov (United States)

    Shirazinodeh, Alireza; Noubari, Hossein Ahmadi; Rabbani, Hossein; Dehnavi, Alireza Mehri

    2015-01-01

    Recent studies on wavelet transform and fractal modeling applied on mammograms for the detection of cancerous tissues indicate that microcalcifications and masses can be utilized for the study of the morphology and diagnosis of cancerous cases. It is shown that the use of fractal modeling, as applied to a given image, can clearly discern cancerous zones from noncancerous areas. In this paper, for fractal modeling, the original image is first segmented into appropriate fractal boxes followed by identifying the fractal dimension of each windowed section using a computationally efficient two-dimensional box-counting algorithm. Furthermore, using appropriate wavelet sub-bands and image Reconstruction based on modified wavelet coefficients, it is shown that it is possible to arrive at enhanced features for detection of cancerous zones. In this paper, we have attempted to benefit from the advantages of both fractals and wavelets by introducing a new algorithm. By using a new algorithm named F1W2, the original image is first segmented into appropriate fractal boxes, and the fractal dimension of each windowed section is extracted. Following from that, by applying a maximum level threshold on fractal dimensions matrix, the best-segmented boxes are selected. In the next step, the segmented Cancerous zones which are candidates are then decomposed by utilizing standard orthogonal wavelet transform and db2 wavelet in three different resolution levels, and after nullifying wavelet coefficients of the image at the first scale and low frequency band of the third scale, the modified reconstructed image is successfully utilized for detection of breast cancer regions by applying an appropriate threshold. For detection of cancerous zones, our simulations indicate the accuracy of 90.9% for masses and 88.99% for microcalcifications detection results using the F1W2 method. For classification of detected mictocalcification into benign and malignant cases, eight features are identified and

  19. Fluorescently labeled bevacizumab in human breast cancer: defining the classification threshold

    Science.gov (United States)

    Koch, Maximilian; de Jong, Johannes S.; Glatz, Jürgen; Symvoulidis, Panagiotis; Lamberts, Laetitia E.; Adams, Arthur L. L.; Kranendonk, Mariëtte E. G.; Terwisscha van Scheltinga, Anton G. T.; Aichler, Michaela; Jansen, Liesbeth; de Vries, Jakob; Lub-de Hooge, Marjolijn N.; Schröder, Carolien P.; Jorritsma-Smit, Annelies; Linssen, Matthijs D.; de Boer, Esther; van der Vegt, Bert; Nagengast, Wouter B.; Elias, Sjoerd G.; Oliveira, Sabrina; Witkamp, Arjen J.; Mali, Willem P. Th. M.; Van der Wall, Elsken; Garcia-Allende, P. Beatriz; van Diest, Paul J.; de Vries, Elisabeth G. E.; Walch, Axel; van Dam, Gooitzen M.; Ntziachristos, Vasilis

    2017-07-01

    In-vivo fluorescently labelled drug (bevacizumab) breast cancer specimen where obtained from patients. We propose a new structured method to determine the optimal classification threshold in targeted fluorescence intra-operative imaging.

  20. Cancer Classification Based on Support Vector Machine Optimized by Particle Swarm Optimization and Artificial Bee Colony.

    Science.gov (United States)

    Gao, Lingyun; Ye, Mingquan; Wu, Changrong

    2017-11-29

    Intelligent optimization algorithms have advantages in dealing with complex nonlinear problems accompanied by good flexibility and adaptability. In this paper, the FCBF (Fast Correlation-Based Feature selection) method is used to filter irrelevant and redundant features in order to improve the quality of cancer classification. Then, we perform classification based on SVM (Support Vector Machine) optimized by PSO (Particle Swarm Optimization) combined with ABC (Artificial Bee Colony) approaches, which is represented as PA-SVM. The proposed PA-SVM method is applied to nine cancer datasets, including five datasets of outcome prediction and a protein dataset of ovarian cancer. By comparison with other classification methods, the results demonstrate the effectiveness and the robustness of the proposed PA-SVM method in handling various types of data for cancer classification.

  1. Experiences of ethical issues when caring for children with cancer.

    Science.gov (United States)

    Bartholdson, Cecilia; Lützén, Kim; Blomgren, Klas; Pergert, Pernilla

    2015-01-01

    The treatment for pediatric cancer is often physically, socially, and psychologically demanding and often gives rise to ethical issues. The purpose of this study was to describe healthcare professionals' experiences of ethical issues and ways to deal with these when caring for children with cancer. A study-specific questionnaire was given to healthcare professionals at a pediatric hospital in Sweden. Qualitative content analysis was used to analyze answers to open-ended questions. The data were sorted into 2 domains based on the objective of the study. In the next step, the data in each domain were inductively coded, generating categories and subcategories. The main ethical issues included concerns of (1) infringing on autonomy, (2) deciding on treatment levels, and (3) conflicting perspectives that constituted a challenge to collaboration. Professionals desired teamwork and reflection to deal with ethical concerns, and they needed resources for dealing with ethics. Interprofessional consideration needs to be improved. Forums and time for ethics reflections need to be offered to deal with ethical concerns in childhood cancer care. Experiences of ethical concerns and dealing with these in caring for children with cancer evoked strong feelings and moral perplexity among nursing staff. The study raises a challenging question: How can conflicting perspectives, lack of interprofessional consideration, and obstacles related to parents' involvement be "turned around," that is, contribute to a holistic perspective of ethics in cancer care of children?

  2. Identifying colon cancer risk modules with better classification performance based on human signaling network.

    Science.gov (United States)

    Qu, Xiaoli; Xie, Ruiqiang; Chen, Lina; Feng, Chenchen; Zhou, Yanyan; Li, Wan; Huang, Hao; Jia, Xu; Lv, Junjie; He, Yuehan; Du, Youwen; Li, Weiguo; Shi, Yuchen; He, Weiming

    2014-10-01

    Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. Copyright © 2013. Published by Elsevier Inc.

  3. Cancer survival classification using integrated data sets and intermediate information.

    Science.gov (United States)

    Kim, Shinuk; Park, Taesung; Kon, Mark

    2014-09-01

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

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

    Science.gov (United States)

    Tarone, Robert E

    2018-01-01

    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.

  5. 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

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

    International Nuclear Information System (INIS)

    Stone, Vicki; Nowack, Bernd; Baun, Anders; Brink, Nico van den; Kammer, Frank von der; Dusinska, Maria; Handy, Richard; Hankin, Steven; Hasselloev, Martin; Joner, Erik; Fernandes, Teresa 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 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 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 required

  7. Efficacy of hidden markov model over support vector machine on multiclass classification of healthy and cancerous cervical tissues

    Science.gov (United States)

    Mukhopadhyay, Sabyasachi; Kurmi, Indrajit; Pratiher, Sawon; Mukherjee, Sukanya; Barman, Ritwik; Ghosh, Nirmalya; Panigrahi, Prasanta K.

    2018-02-01

    In this paper, a comparative study between SVM and HMM has been carried out for multiclass classification of cervical healthy and cancerous tissues. In our study, the HMM methodology is more promising to produce higher accuracy in classification.

  8. 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.

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

    Science.gov (United States)

    Nahid, Abdullah-Al; Kong, Yinan

    2017-01-01

    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.

  10. Spiritual issues and quality of life assessment in cancer care.

    Science.gov (United States)

    Efficace, Fabio; Marrone, Robert

    2002-11-01

    Being diagnosed with cancer forces most human beings to face their own death. The comfortable sense of both invulnerability and immortality is shattered, making the patient thoroughly aware that life is finite and limited. Approaching death, cancer patients commonly embark on an inner journey involving a search for meaning as well as a reordering of priorities involving physical, psychological, social, and spiritual needs. Although interest in the role of spirituality, relating to both adjustment to cancer and the overall quality of life of cancer patients, has increased in recent years, most of the commonly used quality of life (QOL) instruments in oncology typically do not include spiritual issues. In this article, it is argued that assessing QOL effectively should involve all aspects of the personality, including mind, body, and spirit as well. This article also reviews recent studies, which have shown that spiritual well-being, although a many-sided and difficult construct to define, is closely related to the QOL of cancer patients. It is also suggested that further research is needed to understand how the new focus on spirituality can contribute to a more comprehensive assessment of patient's QOL in cancer care.

  11. A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs.

    Science.gov (United States)

    Li, Feifei; Piao, Minghao; Piao, Yongjun; Li, Meijing; Ryu, Keun Ho

    2014-10-01

    Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

  12. 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.

  13. 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.

  14. Classification of cancerous cells based on the one-class problem approach

    Science.gov (United States)

    Murshed, Nabeel A.; Bortolozzi, Flavio; Sabourin, Robert

    1996-03-01

    One of the most important factors in reducing the effect of cancerous diseases is the early diagnosis, which requires a good and a robust method. With the advancement of computer technologies and digital image processing, the development of a computer-based system has become feasible. In this paper, we introduce a new approach for the detection of cancerous cells. This approach is based on the one-class problem approach, through which the classification system need only be trained with patterns of cancerous cells. This reduces the burden of the training task by about 50%. Based on this approach, a computer-based classification system is developed, based on the Fuzzy ARTMAP neural networks. Experimental results were performed using a set of 542 patterns taken from a sample of breast cancer. Results of the experiment show 98% correct identification of cancerous cells and 95% correct identification of non-cancerous cells.

  15. Psychological, social, and behavioral issues for young adults with cancer.

    Science.gov (United States)

    Zebrack, Brad J

    2011-05-15

    Theories of human development suggest that, although all cancer patients experience a common set of life disruptions, they experience them differently, focus on different issues, and attach different levels of importance to different aspects of the experience depending on the time in life at which they were diagnosed. During the critical developmental transition from childhood to adulthood, older adolescents and young adults in particular have typical concerns with establishing identity, developing a positive body image and sexual identity, separating from parents, increasing involvement with peers and dating, and beginning to make decisions about careers or employment, higher education, and/or family. Accordingly, cancer-related issues such as premature confrontation with mortality, changes in physical appearance, increased dependence on parents, disruptions in social life and school/employment because of treatment, loss of reproductive capacity, and health-related concerns about the future may be particularly distressing for adolescents and young adults. Psychosocial and behavioral interventions for young adult cancer patients and survivors often involve assisting these individuals in retaining or returning to function in significant social roles, such as spouse, parent, student, worker, or friend. Successful interventions will enable these young people to overcome the detrimental impact of a health crisis and strengthen the internal and external coping resources available to them. © 2011 American Cancer Society

  16. 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.

  17. 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.

  18. 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.

  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. Emotional and sexual health in cancer: partner and relationship issues.

    Science.gov (United States)

    Wittmann, Daniela

    2016-03-01

    During the past decade, partners have been seen as integral to cancer survivors' emotional and sexual well-being. The couple is viewed as the unit that copes with the impact of cancer on the most intimate aspects of the relationship, including sexuality. This review aims to provide an update on research reported in the past 2 years on partners and couples. Two thematic areas emerge: cancer-related distress management through increased communication, intimacy and building coping skills, and recovery of sexual intimacy. Observational studies have deepened our understanding of both areas and interventions are increasingly tested through more sophisticated methodologies. There is a developing consensus on desired outcomes, including more informed expectations of functional outcomes and enabling grief, communication, acceptance of the 'new normal,' and dyadic coping. The most significant challenge to this area of cancer survivorship is the lack of implementation of psychosocial research findings in usual care. However, clinicians can start the conversation and use concepts identified as relevant and useful in research, such as expectations, grief, or 'new sexual health normal' and include partners in their care for cancer survivors. Future steps include continued work on conceptualization of these issues, the development of appropriate measures and interventions, and further dissemination of dyadic data analytic methodology.

  1. 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

  2. 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.

  3. Ethical, social and counselling issues in hereditary cancer susceptibility.

    Science.gov (United States)

    Garber, J E; Patenaude, A F

    1995-01-01

    Genetic testing for hereditary susceptibility to disease is new. Much has been learned from experience with Huntington's disease and other non-malignant conditions. There are some differences in the case of predisposition testing for cancer: there is often the perception that cancer is preventable and sometimes curable, in contrast to other hereditary conditions. Testing raises many issues new to the medical community and to the public as well. There is great concern that the explosive technology be used responsibly, so that the potential benefits of genetic knowledge are not eclipsed by the risks to autonomy, privacy and justice. Practical concerns about insurability and discrimination may inhibit some at risk individuals from taking advantage of this powerful technology. There has been considerable effort already in the UK, Europe and the USA at the research and social levels to create protection for individuals found to carry genetic susceptibility to disease.

  4. Mastectomy or breast conserving surgery? Factors affecting type of surgical treatment for breast cancer – a classification tree approach

    International Nuclear Information System (INIS)

    Martin, Michael A; Meyricke, Ramona; O'Neill, Terry; Roberts, Steven

    2006-01-01

    A critical choice facing breast cancer patients is which surgical treatment – mastectomy or breast conserving surgery (BCS) – is most appropriate. Several studies have investigated factors that impact the type of surgery chosen, identifying features such as place of residence, age at diagnosis, tumor size, socio-economic and racial/ethnic elements as relevant. Such assessment of 'propensity' is important in understanding issues such as a reported under-utilisation of BCS among women for whom such treatment was not contraindicated. Using Western Australian (WA) data, we further examine the factors associated with the type of surgical treatment for breast cancer using a classification tree approach. This approach deals naturally with complicated interactions between factors, and so allows flexible and interpretable models for treatment choice to be built that add to the current understanding of this complex decision process. Data was extracted from the WA Cancer Registry on women diagnosed with breast cancer in WA from 1990 to 2000. Subjects' treatment preferences were predicted from covariates using both classification trees and logistic regression. Tumor size was the primary determinant of patient choice, subjects with tumors smaller than 20 mm in diameter preferring BCS. For subjects with tumors greater than 20 mm in diameter factors such as patient age, nodal status, and tumor histology become relevant as predictors of patient choice. Classification trees perform as well as logistic regression for predicting patient choice, but are much easier to interpret for clinical use. The selected tree can inform clinicians' advice to patients

  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. 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.

  7. Masculinity and urogenital cancer: sensitive issues in health care.

    Science.gov (United States)

    Nobis, Regina; Sand, Inger; Elofsson, Kristina

    2007-02-01

    The aim of this literature review was to analyse the approaches adopted by patients, health professionals, spouses and other care-givers towards sensitive issues related to male urogenital cancer, and to describe how these findings can be applied in health care practice. The findings revealed five identifiable domains, namely 'the barrier to talking', 'the barrier of sensitivity', 'the barrier of masculinity', 'the barrier to seeking health care' and 'the communicative barrier'. The conclusion was that the phenomenon of a barrier is strongly connected with hegemonic masculinity. The review of literature confirmed that, for many men, talking about genitally-related health problems is not easy and that health care professionals need to learn more about gender and masculinity in order to address urogenitally sensitive issues.

  8. 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...

  9. 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.

  10. 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.

  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. Significance and Application of Digital Breast Tomosynthesis for the BI-RADS Classification of Breast Cancer.

    Science.gov (United States)

    Cai, Si-Qing; Yan, Jian-Xiang; Chen, Qing-Shi; Huang, Mei-Ling; Cai, Dong-Lu

    2015-01-01

    Full-field digital mammography (FFDM) with dense breasts has a high rate of missed diagnosis, and digital breast tomosynthesis (DBT) could reduce organization overlapping and provide more reliable images for BI-RADS classification. This study aims to explore application of COMBO (FFDM+DBT) for effect and significance of BI-RADS classification of breast cancer. In this study, we selected 832 patients who had been treated from May 2013 to November 2013. Classify FFDM and COMBO examination according to BI-RADS separately and compare the differences for glands in the image of the same patient in judgment, mass characteristics display and indirect signs. Employ Paired Wilcoxon rank sum test was used in 79 breast cancer patients to find differences between two examine methods. The results indicated that COMBO pattern is able to observe more details in distribution of glands when estimating content. Paired Wilcoxon rank sum test showed that overall classification level of COMBO is higher significantly compared to FFDM to BI-RADS diagnosis and classification of breast (PBI-RADS classification in breast cancer in clinical.

  13. Stepwise classification of cancer samples using clinical and molecular data

    Directory of Open Access Journals (Sweden)

    Obulkasim Askar

    2011-10-01

    Full Text Available Abstract Background Combining clinical and molecular data types may potentially improve prediction accuracy of a classifier. However, currently there is a shortage of effective and efficient statistical and bioinformatic tools for true integrative data analysis. Existing integrative classifiers have two main disadvantages: First, coarse combination may lead to subtle contributions of one data type to be overshadowed by more obvious contributions of the other. Second, the need to measure both data types for all patients may be both unpractical and (cost inefficient. Results We introduce a novel classification method, a stepwise classifier, which takes advantage of the distinct classification power of clinical data and high-dimensional molecular data. We apply classification algorithms to two data types independently, starting with the traditional clinical risk factors. We only turn to relatively expensive molecular data when the uncertainty of prediction result from clinical data exceeds a predefined limit. Experimental results show that our approach is adaptive: the proportion of samples that needs to be re-classified using molecular data depends on how much we expect the predictive accuracy to increase when re-classifying those samples. Conclusions Our method renders a more cost-efficient classifier that is at least as good, and sometimes better, than one based on clinical or molecular data alone. Hence our approach is not just a classifier that minimizes a particular loss function. Instead, it aims to be cost-efficient by avoiding molecular tests for a potentially large subgroup of individuals; moreover, for these individuals a test result would be quickly available, which may lead to reduced waiting times (for diagnosis and hence lower the patients distress. Stepwise classification is implemented in R-package stepwiseCM and available at the Bioconductor website.

  14. 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.

  15. Immunogenomic Classification of Colorectal Cancer and Therapeutic Implications

    NARCIS (Netherlands)

    Roelands, Jessica; Kuppen, Peter J. K.; Vermeulen, Louis; Maccalli, Cristina; Decock, Julie; Wang, Ena; Marincola, Francesco M.; Bedognetti, Davide; Hendrickx, Wouter

    2017-01-01

    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

  16. 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

  17. Recursive Partitioning Analysis for New Classification of Patients With Esophageal Cancer Treated by Chemoradiotherapy

    International Nuclear Information System (INIS)

    Nomura, Motoo; Shitara, Kohei; Kodaira, Takeshi; Kondoh, Chihiro; Takahari, Daisuke; Ura, Takashi; Kojima, Hiroyuki; Kamata, Minoru; Muro, Kei; Sawada, Satoshi

    2012-01-01

    Background: The 7th edition of the American Joint Committee on Cancer staging system does not include lymph node size in the guidelines for staging patients with esophageal cancer. The objectives of this study were to determine the prognostic impact of the maximum metastatic lymph node diameter (ND) on survival and to develop and validate a new staging system for patients with esophageal squamous cell cancer who were treated with definitive chemoradiotherapy (CRT). Methods: Information on 402 patients with esophageal cancer undergoing CRT at two institutions was reviewed. Univariate and multivariate analyses of data from one institution were used to assess the impact of clinical factors on survival, and recursive partitioning analysis was performed to develop the new staging classification. To assess its clinical utility, the new classification was validated using data from the second institution. Results: By multivariate analysis, gender, T, N, and ND stages were independently and significantly associated with survival (p < 0.05). The resulting new staging classification was based on the T and ND. The four new stages led to good separation of survival curves in both the developmental and validation datasets (p < 0.05). Conclusions: Our results showed that lymph node size is a strong independent prognostic factor and that the new staging system, which incorporated lymph node size, provided good prognostic power, and discriminated effectively for patients with esophageal cancer undergoing CRT.

  18. Evaluation Methodology between Globalization and Localization Features Approaches for Skin Cancer Lesions Classification

    Science.gov (United States)

    Ahmed, H. M.; Al-azawi, R. J.; Abdulhameed, A. A.

    2018-05-01

    Huge efforts have been put in the developing of diagnostic methods to skin cancer disease. In this paper, two different approaches have been addressed for detection the skin cancer in dermoscopy images. The first approach uses a global method that uses global features for classifying skin lesions, whereas the second approach uses a local method that uses local features for classifying skin lesions. The aim of this paper is selecting the best approach for skin lesion classification. The dataset has been used in this paper consist of 200 dermoscopy images from Pedro Hispano Hospital (PH2). The achieved results are; sensitivity about 96%, specificity about 100%, precision about 100%, and accuracy about 97% for globalization approach while, sensitivity about 100%, specificity about 100%, precision about 100%, and accuracy about 100% for Localization Approach, these results showed that the localization approach achieved acceptable accuracy and better than globalization approach for skin cancer lesions classification.

  19. Breast cancer tumor classification using LASSO method selection approach

    International Nuclear Information System (INIS)

    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.

    2016-10-01

    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)

  20. 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)

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Classification of human cancers based on DNA copy number amplification modeling

    Directory of Open Access Journals (Sweden)

    Knuutila Sakari

    2008-05-01

    Full Text Available Abstract Background DNA amplifications alter gene dosage in cancer genomes by multiplying the gene copy number. Amplifications are quintessential in a considerable number of advanced cancers of various anatomical locations. The aims of this study were to classify human cancers based on their amplification patterns, explore the biological and clinical fundamentals behind their amplification-pattern based classification, and understand the characteristics in human genomic architecture that associate with amplification mechanisms. Methods We applied a machine learning approach to model DNA copy number amplifications using a data set of binary amplification records at chromosome sub-band resolution from 4400 cases that represent 82 cancer types. Amplification data was fused with background data: clinical, histological and biological classifications, and cytogenetic annotations. Statistical hypothesis testing was used to mine associations between the data sets. Results Probabilistic clustering of each chromosome identified 111 amplification models and divided the cancer cases into clusters. The distribution of classification terms in the amplification-model based clustering of cancer cases revealed cancer classes that were associated with specific DNA copy number amplification models. Amplification patterns – finite or bounded descriptions of the ranges of the amplifications in the chromosome – were extracted from the clustered data and expressed according to the original cytogenetic nomenclature. This was achieved by maximal frequent itemset mining using the cluster-specific data sets. The boundaries of amplification patterns were shown to be enriched with fragile sites, telomeres, centromeres, and light chromosome bands. Conclusions Our results demonstrate that amplifications are non-random chromosomal changes and specifically selected in tumor tissue microenvironment. Furthermore, statistical evidence showed that specific chromosomal features

  6. From Molecular Classification to Targeted Therapeutics: The Changing Face of Systemic Therapy in Metastatic Gastroesophageal Cancer

    Directory of Open Access Journals (Sweden)

    Adrian Murphy

    2015-01-01

    Full Text Available Histological classification of adenocarcinoma or squamous cell carcinoma for esophageal cancer or using the Lauren classification for intestinal and diffuse type gastric cancer has limited clinical utility in the management of advanced disease. Germline mutations in E-cadherin (CDH1 or mismatch repair genes (Lynch syndrome were identified many years ago but given their rarity, the identification of these molecular alterations does not substantially impact treatment in the advanced setting. Recent molecular profiling studies of upper GI tumors have added to our knowledge of the underlying biology but have not led to an alternative classification system which can guide clinician’s therapeutic decisions. Recently the Cancer Genome Atlas Research Network has proposed four subtypes of gastric cancer dividing tumors into those positive for Epstein-Barr virus, microsatellite unstable tumors, genomically stable tumors, and tumors with chromosomal instability. Unfortunately to date, many phase III clinical trials involving molecularly targeted agents have failed to meet their survival endpoints due to their use in unselected populations. Future clinical trials should utilize molecular profiling of individual tumors in order to determine the optimal use of targeted therapies in preselected patients.

  7. A protein and mRNA expression-based classification of gastric cancer.

    Science.gov (United States)

    Setia, Namrata; Agoston, Agoston T; Han, Hye S; Mullen, John T; Duda, Dan G; Clark, Jeffrey W; Deshpande, Vikram; Mino-Kenudson, Mari; Srivastava, Amitabh; Lennerz, Jochen K; Hong, Theodore S; Kwak, Eunice L; Lauwers, Gregory Y

    2016-07-01

    The overall survival of gastric carcinoma patients remains poor despite improved control over known risk factors and surveillance. This highlights the need for new classifications, driven towards identification of potential therapeutic targets. Using sophisticated molecular technologies and analysis, three groups recently provided genetic and epigenetic molecular classifications of gastric cancer (The Cancer Genome Atlas, 'Singapore-Duke' study, and Asian Cancer Research Group). Suggested by these classifications, here, we examined the expression of 14 biomarkers in a cohort of 146 gastric adenocarcinomas and performed unsupervised hierarchical clustering analysis using less expensive and widely available immunohistochemistry and in situ hybridization. Ultimately, we identified five groups of gastric cancers based on Epstein-Barr virus (EBV) positivity, microsatellite instability, aberrant E-cadherin, and p53 expression; the remaining cases constituted a group characterized by normal p53 expression. In addition, the five categories correspond to the reported molecular subgroups by virtue of clinicopathologic features. Furthermore, evaluation between these clusters and survival using the Cox proportional hazards model showed a trend for superior survival in the EBV and microsatellite-instable related adenocarcinomas. In conclusion, we offer as a proposal a simplified algorithm that is able to reproduce the recently proposed molecular subgroups of gastric adenocarcinoma, using immunohistochemical and in situ hybridization techniques.

  8. An NRG Oncology/GOG study of molecular classification for risk prediction in endometrioid endometrial cancer.

    Science.gov (United States)

    Cosgrove, Casey M; Tritchler, David L; Cohn, David E; Mutch, David G; Rush, Craig M; Lankes, Heather A; Creasman, William T; Miller, David S; Ramirez, Nilsa C; Geller, Melissa A; Powell, Matthew A; Backes, Floor J; Landrum, Lisa M; Timmers, Cynthia; Suarez, Adrian A; Zaino, Richard J; Pearl, Michael L; DiSilvestro, Paul A; Lele, Shashikant B; Goodfellow, Paul J

    2018-01-01

    The purpose of this study was to assess the prognostic significance of a simplified, clinically accessible classification system for endometrioid endometrial cancers combining Lynch syndrome screening and molecular risk stratification. Tumors from NRG/GOG GOG210 were evaluated for mismatch repair defects (MSI, MMR IHC, and MLH1 methylation), POLE mutations, and loss of heterozygosity. TP53 was evaluated in a subset of cases. Tumors were assigned to four molecular classes. Relationships between molecular classes and clinicopathologic variables were assessed using contingency tests and Cox proportional methods. Molecular classification was successful for 982 tumors. Based on the NCI consensus MSI panel assessing MSI and loss of heterozygosity combined with POLE testing, 49% of tumors were classified copy number stable (CNS), 39% MMR deficient, 8% copy number altered (CNA) and 4% POLE mutant. Cancer-specific mortality occurred in 5% of patients with CNS tumors; 2.6% with POLE tumors; 7.6% with MMR deficient tumors and 19% with CNA tumors. The CNA group had worse progression-free (HR 2.31, 95%CI 1.53-3.49) and cancer-specific survival (HR 3.95; 95%CI 2.10-7.44). The POLE group had improved outcomes, but the differences were not statistically significant. CNA class remained significant for cancer-specific survival (HR 2.11; 95%CI 1.04-4.26) in multivariable analysis. The CNA molecular class was associated with TP53 mutation and expression status. A simple molecular classification for endometrioid endometrial cancers that can be easily combined with Lynch syndrome screening provides important prognostic information. These findings support prospective clinical validation and further studies on the predictive value of a simplified molecular classification system. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. 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.

  10. Computed tomography and the TNM classification of lung cancer

    International Nuclear Information System (INIS)

    Sparup, J.; Friis, M.; Brenoee, J.; Vejlsted, H.; Villumsen, B.; Olesen, K.P.; Borgeskov, S.; Bertelsen, S.

    1990-01-01

    Computed tomography (CT)of the thorax and upper abdomen was prospectively evaluated in 84 patients with potentially operable lung cancer. Invasion into the thoracic wall and the mediastinal structures was not accurately demonstrated by CT. For metastatic mediastinal lymph nodes, the sensitivity and specificity of CT were, respectively, 86 per cent and 61 per cent and the positive and negative predictive indices 49 per cent and 91 per cent. For T1, T2 and T3 tumours the negative indices were 100 per cent, 96 per cent and 71 per cent. Positive predictive index did not differ between squamous cell carcinoma and adenocarcinoma. Adrenal metastases were CT-suspected in 17 cases and liver metastases in eight, but were verified by ultrasonography in only one and four cases. CT should be used in preoperative investigation of lung cancer, irrespective of stage. Demonstration of thoracic-wall or mediastinal invasion need not exclude tumour resection. Preoperative mediastinoscopy is indicated if CT shows nodal metastases or if there are signs of tumour invasion, but not in CT-negative T1 or T2 tumour. Abdominal metastases indicated by CT should be investigated with CT-guided needle biopsy. (authors)

  11. FEATURE EXTRACTION BASED WAVELET TRANSFORM IN BREAST CANCER DIAGNOSIS USING FUZZY AND NON-FUZZY CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Pelin GORGEL

    2013-01-01

    Full Text Available This study helps to provide a second eye to the expert radiologists for the classification of manually extracted breast masses taken from 60 digital mammıgrams. These mammograms have been acquired from Istanbul University Faculty of Medicine Hospital and have 78 masses. The diagnosis is implemented with pre-processing by using feature extraction based Fast Wavelet Transform (FWT. Afterwards Adaptive Neuro-Fuzzy Inference System (ANFIS based fuzzy subtractive clustering and Support Vector Machines (SVM methods are used for the classification. It is a comparative study which uses these methods respectively. According to the results of the study, ANFIS based subtractive clustering produces ??% while SVM produces ??% accuracy in malignant-benign classification. The results demonstrate that the developed system could help the radiologists for a true diagnosis and decrease the number of the missing cancerous regions or unnecessary biopsies.

  12. A Quebec survey of issues in cancer pain management.

    Science.gov (United States)

    MacDonald, Neil; Ayoub, Joseph; Farley, Justine; Foucault, Claudette; Lesage, Pauline; Mayo, Nancy

    2002-01-01

    We report the results of a cancer pain survey mailed to Quebec hematologist-oncologists and palliative care physicians in 1999. The survey was designed to sample views on the current status of pain management and on obstacles to the provision of adequate pain relief for patients. The survey, formulated by an ethics network centered at the Clinical Research Institute of Montreal, was distributed to all members of the Association of Hematologist-Oncologists of Quebec and to all physician members of the Quebec Palliative Care Association. Responses were obtained from 138 Palliative Care Association members (response rate 61%) and 76 hematologist-oncologists (response rate 45%). Major obstacles reported included inadequate assessment of both contributory psychosocial issues and severity of pain, patient reluctance to take opioids, and inadequate access to non-drug techniques for pain relief. Access to opioids was not regarded as a problem. Both groups felt generally competent in their ability to manage various aspects of cancer pain therapy. They gave little credit to their formal medical school or residency training. Fifty-six percent of the palliative care group and 57% of the hemato-oncologists rated their medical school experience as only "poor" or "fair" on a 4-point scale. Residency ratings were modestly better. We conclude that medical faculties should assign a high priority to teaching health professionals patient assessment techniques. Simple symptom assessment scales should be routinely used in oncology/palliative care practice. Medical school training in pain management is not highly regarded and should be enhanced. We also note that, based on response to the scenario of a patient presenting with severe pain, many physicians, while feeling competent in the use of opioids, may be overly conservative in their initial use.

  13. 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

  14. Rough set soft computing cancer classification and network: one stone, two birds.

    Science.gov (United States)

    Zhang, Yue

    2010-07-15

    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.

  15. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

    DEFF Research Database (Denmark)

    Hoadley, Katherine A; Yau, Christina; Wolf, Denise M

    2014-01-01

    Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform...... on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset...

  16. Early detection of lung cancer from CT images: nodule segmentation and classification using deep learning

    Science.gov (United States)

    Sharma, Manu; Bhatt, Jignesh S.; Joshi, Manjunath V.

    2018-04-01

    Lung cancer is one of the most abundant causes of the cancerous deaths worldwide. It has low survival rate mainly due to the late diagnosis. With the hardware advancements in computed tomography (CT) technology, it is now possible to capture the high resolution images of lung region. However, it needs to be augmented by efficient algorithms to detect the lung cancer in the earlier stages using the acquired CT images. To this end, we propose a two-step algorithm for early detection of lung cancer. Given the CT image, we first extract the patch from the center location of the nodule and segment the lung nodule region. We propose to use Otsu method followed by morphological operations for the segmentation. This step enables accurate segmentation due to the use of data-driven threshold. Unlike other methods, we perform the segmentation without using the complete contour information of the nodule. In the second step, a deep convolutional neural network (CNN) is used for the better classification (malignant or benign) of the nodule present in the segmented patch. Accurate segmentation of even a tiny nodule followed by better classification using deep CNN enables the early detection of lung cancer. Experiments have been conducted using 6306 CT images of LIDC-IDRI database. We achieved the test accuracy of 84.13%, with the sensitivity and specificity of 91.69% and 73.16%, respectively, clearly outperforming the state-of-the-art algorithms.

  17. Classification of breast cancer patients using somatic mutation profiles and machine learning approaches.

    Science.gov (United States)

    Vural, Suleyman; Wang, Xiaosheng; Guda, Chittibabu

    2016-08-26

    The high degree of heterogeneity observed in breast cancers makes it very difficult to classify the cancer patients into distinct clinical subgroups and consequently limits the ability to devise effective therapeutic strategies. Several classification strategies based on ER/PR/HER2 expression or the expression profiles of a panel of genes have helped, but such methods often produce misleading results due to their dynamic nature. In contrast, somatic DNA mutations are relatively stable and lead to initiation and progression of many sporadic cancers. Hence in this study, we explore the use of gene mutation profiles to classify, characterize and predict the subgroups of breast cancers. We analyzed the whole exome sequencing data from 358 ethnically similar breast cancer patients in The Cancer Genome Atlas (TCGA) project. Somatic and non-synonymous single nucleotide variants identified from each patient were assigned a quantitative score (C-score) that represents the extent of negative impact on the gene function. Using these scores with non-negative matrix factorization method, we clustered the patients into three subgroups. By comparing the clinical stage of patients, we identified an early-stage-enriched and a late-stage-enriched subgroup. Comparison of the mutation scores of early and late-stage-enriched subgroups identified 358 genes that carry significantly higher mutations rates in the late stage subgroup. Functional characterization of these genes revealed important functional gene families that carry a heavy mutational load in the late state rich subgroup of patients. Finally, using the identified subgroups, we also developed a supervised classification model to predict the stage of the patients. This study demonstrates that gene mutation profiles can be effectively used with unsupervised machine-learning methods to identify clinically distinguishable breast cancer subgroups. The classification model developed in this method could provide a reasonable

  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...

  19. 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.

  20. 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.

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

    International Nuclear Information System (INIS)

    Liu, Song; Guan, Wenxian; Wang, Hao; Pan, Liang; Zhou, Zhuping; Yu, Haiping; Liu, Tian; Yang, Xiaofeng; He, Jian; Zhou, Zhengyang

    2014-01-01

    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 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 Lauren

  2. 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 .

  3. 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%.

  4. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    Directory of Open Access Journals (Sweden)

    Reinders Marcel JT

    2009-11-01

    Full Text Available Abstract Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical

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

    Directory of Open Access Journals (Sweden)

    List Markus

    2014-06-01

    Full Text Available Selecting the most promising treatment strategy for breast cancer crucially depends on determining the correct subtype. In recent years, gene expression profiling has been investigated as an alternative to histochemical methods. Since databases like TCGA provide easy and unrestricted access to gene 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 selection problem. However, more diverse data from other OMICS technologies are available, including methylation. We hypothesize that combining methylation and gene expression data could already lead to a largely improved classification model, since the resulting model will reflect differences not only on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10-20% and classification error of 1-50%, depending on breast cancer subtype and model. The gene expression model was clearly superior to the methylation model, which was also reflected in the combined model, which mainly selected features from gene expression data. However, the methylation model was able to identify unique features not considered as relevant by the gene expression model, which might provide deeper insights into breast cancer subtype differentiation on an epigenetic level.

  6. Automatic classification of ovarian cancer types from cytological images using deep convolutional neural networks.

    Science.gov (United States)

    Wu, Miao; Yan, Chuanbo; Liu, Huiqiang; Liu, Qian

    2018-06-29

    Ovarian cancer is one of the most common gynecologic malignancies. Accurate classification of ovarian cancer types (serous carcinoma, mucous carcinoma, endometrioid carcinoma, transparent cell carcinoma) is an essential part in the different diagnosis. Computer-aided diagnosis (CADx) can provide useful advice for pathologists to determine the diagnosis correctly. In our study, we employed a Deep Convolutional Neural Networks (DCNN) based on AlexNet to automatically classify the different types of ovarian cancers from cytological images. The DCNN consists of five convolutional layers, three max pooling layers, and two full reconnect layers. Then we trained the model by two group input data separately, one was original image data and the other one was augmented image data including image enhancement and image rotation. The testing results are obtained by the method of 10-fold cross-validation, showing that the accuracy of classification models has been improved from 72.76 to 78.20% by using augmented images as training data. The developed scheme was useful for classifying ovarian cancers from cytological images. © 2018 The Author(s).

  7. Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules

    International Nuclear Information System (INIS)

    Teschendorff, Andrew E; Gomez, Sergio; Arenas, Alex; El-Ashry, Dorraya; Schmidt, Marcus; Gehrmann, Mathias; Caldas, Carlos

    2010-01-01

    Elucidating the activation pattern of molecular pathways across a given tumour type is a key challenge necessary for understanding the heterogeneity in clinical response and for developing novel more effective therapies. Gene expression signatures of molecular pathway activation derived from perturbation experiments in model systems as well as structural models of molecular interactions ('model signatures') constitute an important resource for estimating corresponding activation levels in tumours. However, relatively few strategies for estimating pathway activity from such model signatures exist and only few studies have used activation patterns of pathways to refine molecular classifications of cancer. Here we propose a novel network-based method for estimating pathway activation in tumours from model signatures. We find that although the pathway networks inferred from cancer expression data are highly consistent with the prior information contained in the model signatures, that they also exhibit a highly modular structure and that estimation of pathway activity is dependent on this modular structure. We apply our methodology to a panel of 438 estrogen receptor negative (ER-) and 785 estrogen receptor positive (ER+) breast cancers to infer activation patterns of important cancer related molecular pathways. We show that in ER negative basal and HER2+ breast cancer, gene expression modules reflecting T-cell helper-1 (Th1) and T-cell helper-2 (Th2) mediated immune responses play antagonistic roles as major risk factors for distant metastasis. Using Boolean interaction Cox-regression models to identify non-linear pathway combinations associated with clinical outcome, we show that simultaneous high activation of Th1 and low activation of a TGF-beta pathway module defines a subtype of particularly good prognosis and that this classification provides a better prognostic model than those based on the individual pathways. In ER+ breast cancer, we find that

  8. 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 microarrays could be used to classify colorectal tumors. Methods. We used the Affymetrix oligonucleotide arrays to analyze the expression of more than 5,000 genes in samples from the sigmoid and upper rectum of the left colon. Five samples were from normal mucosa and five samples from each...... 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....

  9. 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.

  10. [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.

  11. CrossLink: a novel method for cross-condition classification of cancer subtypes.

    Science.gov (United States)

    Ma, Chifeng; Sastry, Konduru S; Flore, Mario; Gehani, Salah; Al-Bozom, Issam; Feng, Yusheng; Serpedin, Erchin; Chouchane, Lotfi; Chen, Yidong; Huang, Yufei

    2016-08-22

    We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another. To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature. We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles. A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms.

  12. In vivo subsite classification and diagnosis of oral cancers using Raman spectroscopy

    Directory of Open Access Journals (Sweden)

    Aditi Sahu

    2016-09-01

    Full Text Available Oral cancers suffer from poor disease-free survival rates due to delayed diagnosis. Noninvasive, rapid, objective approaches as adjuncts to visual inspection can help in better management of oral cancers. Raman spectroscopy (RS has shown potential in identification of oral premalignant and malignant conditions and also in the detection of early cancer changes like cancer-field-effects (CFE at buccal mucosa subsite. Anatomic differences between different oral subsites have also been reported using RS. In this study, anatomical differences between subsites and their possible influence on healthy vs pathological classification were evaluated on 85 oral cancer and 72 healthy subjects. Spectra were acquired from buccal mucosa, lip and tongue in healthy, contralateral (internal healthy control, premalignant and cancer conditions using fiber-optic Raman spectrometer. Mean spectra indicate predominance of lipids in healthy buccal mucosa, contribution of both lipids and proteins in lip while major dominance of protein in tongue spectra. From healthy to tumor, changes in protein secondary-structure, DNA and heme-related features were observed. Principal component linear discriminant analysis (PC-LDA followed by leave-one-out-cross-validation (LOOCV was used for data analysis. Findings indicate buccal mucosa and tongue are distinct entities, while lip misclassifies with both these subsites. Additionally, the diagnostic algorithm for individual subsites gave improved classification efficiencies with respect to the pooled subsites model. However, as the pooled subsites model yielded 98% specificity and 100% sensitivity, this model may be more useful for preliminary screening applications. Large-scale validation studies are a pre-requisite before envisaging future clinical applications.

  13. 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.

  14. Classification of prostate cancer grade using temporal ultrasound: in vivo feasibility study

    Science.gov (United States)

    Ghavidel, Sahar; Imani, Farhad; Khallaghi, Siavash; Gibson, Eli; Khojaste, Amir; Gaed, Mena; Moussa, Madeleine; Gomez, Jose A.; Siemens, D. Robert; Leveridge, Michael; Chang, Silvia; Fenster, Aaron; Ward, Aaron D.; Abolmaesumi, Purang; Mousavi, Parvin

    2016-03-01

    Temporal ultrasound has been shown to have high classification accuracy in differentiating cancer from benign tissue. In this paper, we extend the temporal ultrasound method to classify lower grade Prostate Cancer (PCa) from all other grades. We use a group of nine patients with mostly lower grade PCa, where cancerous regions are also limited. A critical challenge is to train a classifier with limited aggressive cancerous tissue compared to low grade cancerous tissue. To resolve the problem of imbalanced data, we use Synthetic Minority Oversampling Technique (SMOTE) to generate synthetic samples for the minority class. We calculate spectral features of temporal ultrasound data and perform feature selection using Random Forests. In leave-one-patient-out cross-validation strategy, an area under receiver operating characteristic curve (AUC) of 0.74 is achieved with overall sensitivity and specificity of 70%. Using an unsupervised learning approach prior to proposed method improves sensitivity and AUC to 80% and 0.79. This work represents promising results to classify lower and higher grade PCa with limited cancerous training samples, using temporal ultrasound.

  15. Classification tree analysis of second neoplasms in survivors of childhood cancer

    International Nuclear Information System (INIS)

    Jazbec, Janez; Todorovski, Ljupčo; Jereb, Berta

    2007-01-01

    Reports on childhood cancer survivors estimated cumulative probability of developing secondary neoplasms vary from 3,3% to 25% at 25 years from diagnosis, and the risk of developing another cancer to several times greater than in the general population. In our retrospective study, we have used the classification tree multivariate method on a group of 849 first cancer survivors, to identify childhood cancer patients with the greatest risk for development of secondary neoplasms. In observed group of patients, 34 develop secondary neoplasm after treatment of primary cancer. Analysis of parameters present at the treatment of first cancer, exposed two groups of patients at the special risk for secondary neoplasm. First are female patients treated for Hodgkin's disease at the age between 10 and 15 years, whose treatment included radiotherapy. Second group at special risk were male patients with acute lymphoblastic leukemia who were treated at the age between 4,6 and 6,6 years of age. The risk groups identified in our study are similar to the results of studies that used more conventional approaches. Usefulness of our approach in study of occurrence of second neoplasms should be confirmed in larger sample study, but user friendly presentation of results makes it attractive for further studies

  16. Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles

    Directory of Open Access Journals (Sweden)

    Wong G William

    2008-06-01

    Full Text Available Abstract Background Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detection of this cancer type is urgently needed. In recent years, proteomics profiling techniques combined with various data analysis methods have been successfully used to gain critical insights into processes and mechanisms underlying pathologic conditions, particularly as they relate to cancer. However, the high dimensionality of proteomics data combined with their relatively small sample sizes poses a significant challenge to current data mining methodology where many of the standard methods cannot be applied directly. Here, we propose a novel methodological framework using machine learning method, in which decision tree based classifier ensembles coupled with feature selection methods, is applied to proteomics data generated from premalignant pancreatic cancer. Results This study explores the utility of three different feature selection schemas (Student t test, Wilcoxon rank sum test and genetic algorithm to reduce the high dimensionality of a pancreatic cancer proteomic dataset. Using the top features selected from each method, we compared the prediction performances of a single decision tree algorithm C4.5 with six different decision-tree based classifier ensembles (Random forest, Stacked generalization, Bagging, Adaboost, Logitboost and Multiboost. We show that ensemble classifiers always outperform single decision tree classifier in having greater accuracies and smaller prediction errors when applied to a pancreatic cancer proteomics dataset. Conclusion In our cross validation framework, classifier ensembles generally have better classification accuracies compared to that of a single decision tree when applied to a pancreatic cancer proteomic dataset, thus suggesting its utility in future proteomics data analysis. Additionally, the use of feature selection

  17. [Clinical Study of 2014 ISUP New Grade Group Classification for Prostate Cancer Patients Treated by Androgen Deprivation Therapy].

    Science.gov (United States)

    Uno, Masahiro; Kawase, Makoto; Kato, Daiki; Ishida, Takashi; Kato, Seiichi; Fujimoto, Yoshinori

    2018-01-01

    The 2014 International Society of Urological Pathology (ISUP) has proposed a new grade group (GG) classification for Gleason scores (GS). The usefulness of the new GG classification was investigated with 518 prostate cancer patients who underwent androgen deprivation therapy. According to the new GG classification, Stages B‒D and the new GG classification relapse-free rate for each stage were calculated using the Kaplan‒Meier method. The new GG classification revealed a significant difference for the relapse-free rate only between some groups. Analysis using the Cox proportional hazards model indicated that the risk of relapse was higher in GGs 4 and 5 than in GG 1. The usefulness about the relapse-free rate in androgen deprivation therapy of the 2014 ISUP new grade group classification a waits future examination.

  18. 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...... classifying the expected extent of the primary surgery and need for postoperative care. On the basis of the operative procedures performed, women were allocated into 1 of the 3 corresponding COVA 1 to 3 groups. The outcome measure was the predictive value of the pre-COVA score compared with the actual COVA......-COVA classification predicted the actual COVA group in 79 (49%) FIGO stages I to IIIB and in 85 (45%) FIGO stages IIIC to IV. Conclusions The COVA classification system is a simple and useful tool in the MDT setting where specialists make treatment decisions based on advanced technology. The use of pre...

  19. 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,

  20. Students with Cancer: Presenting Issues and Effective Solutions

    Science.gov (United States)

    Root, Melissa M.; Bray, Melissa A.; Maykel, Cheryl; Cross, Karen; Shankar, Nilani L.; Theodore, Lea A.

    2016-01-01

    Practitioners working with children diagnosed with cancer in the school environment must consider several facets in order to effectively work with the child and family. The remission rate for children with cancer is relatively high, so one must consider whether the child is anticipating treatment, actively in treatment, or posttreatment when one…

  1. 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

  2. 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.

  3. 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.

  4. Methodological issues in detecting gene-gene interactions in breast cancer susceptibility: a population-based study in Ontario

    Directory of Open Access Journals (Sweden)

    Onay Venus

    2007-08-01

    Full Text Available Abstract Background There is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development. Methods In this study, we systematically studied SNP-SNP interactions among 19 SNPs from 18 key genes involved in major cancer pathways in a sample of 398 breast cancer cases and 372 controls from Ontario. We discuss the methodological issues associated with the detection of SNP-SNP interactions in this dataset by applying and comparing three commonly used methods: the logistic regression model, classification and regression trees (CART, and the multifactor dimensionality reduction (MDR method. Results Our analyses show evidence for several simple (two-way and complex (multi-way SNP-SNP interactions associated with breast cancer. For example, all three methods identified XPD-[Lys751Gln]*IL10-[G(-1082A] as the most significant two-way interaction. CART and MDR identified the same critical SNPs participating in complex interactions. Our results suggest that the use of multiple statistical approaches (or an integrated approach rather than a single methodology could be the best strategy to elucidate complex gene interactions that have generally very different patterns. Conclusion The strategy used here has the potential to identify complex biological relationships among breast cancer genes and processes. This will lead to the discovery of novel biological information, which will improve breast cancer risk management.

  5. 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.

  6. 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.

  7. Fertility Issues in Girls and Women with Cancer

    Science.gov (United States)

    ... than embryo freezing. Embryo freezing (also called embryo banking or embryo cryopreservation ) is a procedure in which ... your website or other digital platform? Our syndication services page shows you how. National Cancer Institute at ...

  8. The invasive cervical cancer review: psychological issues surrounding disclosure.

    Science.gov (United States)

    Sherman, S M; Moss, E; Redman, C W E

    2013-04-01

    An audit of the screening history of all new cervical cancer cases has been a requirement since April 2007. While NHS cervical screening programmes (NHSCSP) guidance requires that women diagnosed with cervical cancer are offered the findings of the audit, as yet there has been no research to investigate the psychological impact that meeting to discuss the findings might have on patients. This is in spite of the fact that cytological under-call may play a role in as many as 20% of cervical cancer cases. This review draws on the literature concerning breaking bad news, discussing cancer and disclosing medical errors, in order to gain insight into both the negative and positive consequences that may accompany a cervical screening review meeting. We conclude that while patients are likely to experience some distress at disclosure, there are also likely to be positive aspects, such as greater trust and improved perception of care. © 2013 Blackwell Publishing Ltd.

  9. 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...

  10. Employment and work-related issues in cancer survivors.

    Science.gov (United States)

    Mehnert, Anja

    2011-02-01

    Purpose of this systematic literature review was to identify current knowledge about employment in cancer survivors. Sixty-four studies met inclusion criteria that were original papers published between 01/2000 and 11/2009. Overall, 63.5% of cancer survivors (range 24-94%) returned to work. The mean duration of absence from work was 151 days. Factors significantly associated with a greater likelihood of being employed or return to work were perceived employer accommodation, flexible working arrangements, counseling, training and rehabilitation services, younger age and cancer sites of younger individuals, higher levels of education, male gender, less physical symptoms, lower length of sick leave and continuity of care. Cancer survivors had a significantly increased risk for unemployment, early retirement and were less likely to be re-employed. Between 26% and 53% of cancer survivors lost their job or quit working over a 72-month period post diagnosis. Between 23% and 75% of patients who lost their job were re-employed. A high proportion of patients experienced at least temporary changes in work schedules, work hours, wages and a decline in work ability compared to non-cancer groups. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  11. ParSel: Parallel Selection of Micro-RNAs for Survival Classification in Cancers.

    Science.gov (United States)

    Sinha, Debajyoti; Sengupta, Debarka; Bandyopadhyay, Sanghamitra

    2017-07-01

    It is known that tumor micro-RNAs (miRNA) can define patient survival and treatment response. We present a framework to identify miRNAs which are predictive of cancer survival. The framework attempts to rank the miRNAs by exploring their collaborative role in gene regulation. Our approach tests a significantly large number of combinatorial cases leveraging parallel computation. We carefully avoided parametric assumptions involved in evaluations of miRNA expressions but used rigorous statistical computation to assign an importance score to a miRNA. Experimental results on three cancer types namely, KIRC, OV and GBM verify that the top ranked miRNAs obtained using the proposed framework produce better classification accuracy as compared to some best practice variable selection methods. Some of these top ranked miRNA are also known to be associated with related diseases. © 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. 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.

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

    Science.gov (United States)

    Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

    2016-01-01

    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. PMID:27642363

  14. Ultrasonographic characteristics and BI-RADS-US classification of BRCA1 mutation-associated breast cancer in Guangxi, China.

    Science.gov (United States)

    Li, Cheng; Liu, Junjie; Wang, Sida; Chen, Yuanyuan; Yuan, Zhigang; Zeng, Jian; Li, Zhixian

    2015-01-01

    To retrospectively analyze and compare the ultrasonographic characteristics and BI-RADS-US classification between patients with BRCA1 mutation-associated breast cancer and those without BRCA1 gene mutation in Guangxi, China. The study was performed in 36 lesions from 34 BRCA1 mutation-associated breast cancer patients. A total of 422 lesions from 422 breast cancer patients without BRCA1 mutations served as control group. The comparison of the ultrasonographic features and BI-RADS-US classification between two the groups were reviewed. More complex inner echo was disclosed in BRCA1 mutation-associated breast cancer patients (x(2) = 4.741, P = 0.029). The BI-RADS classification of BRCA1 mutation-associated breast cancer was lower (U = 6094.0, P = 0.022). BRCA1 mutation-associated breast cancer frequently displays as microlobulated margin and complex echo. It also shows more benign characteristics in morphology, and the BI-RADS classification is prone to be underestimated.

  15. 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

  16. 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

  17. [Molecular classification of breast cancer patients obtained through the technique of chromogenic in situ hybridization (CISH)].

    Science.gov (United States)

    Fernández, Angel; Reigosa, Aldo

    2013-12-01

    Breast cancer is a heterogeneous disease composed of a growing number of biological subtypes, with substantial variability of the disease progression within each category. The aim of this research was to classify the samples object of study according to the molecular classes of breast cancer: luminal A, luminal B, HER2 and triple negative, as a result of the state of HER2 amplification obtained by the technique of chromogenic in situ hybridization (CISH). The sample consisted of 200 biopsies fixed in 10% formalin, processed by standard techniques up to paraffin embedding, corresponding to patients diagnosed with invasive ductal carcinoma of the breast. These biopsies were obtained from patients from private practice and the Institute of Oncology "Dr. Miguel Pérez Carreño", for immunohistochemistry (IHC) of hormone receptors and HER2 made in the Hospital Metropolitano del Norte, Valencia, Venezuela. The molecular classification of the patient's tumors considering the expression of estrogen and progesterone receptors by IHC and HER2 amplification by CISH, allowed those cases originally classified as unknown, since they had an indeterminate (2+) outcome for HER2 expression by IHC, to be grouped into the different molecular classes. Also, this classification permitted that some cases, initially considered as belonging to a molecular class, were assigned to another class, after the revaluation of the HER2 status by CISH.

  18. Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

    Directory of Open Access Journals (Sweden)

    Ballester Marcos

    2010-08-01

    Full Text Available Abstract Background Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Methods Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. Results An SN was detected in 88.2% of cases (75/85 women. Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. Conclusions The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type.

  19. Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

    International Nuclear Information System (INIS)

    Ballester, Marcos; Koskas, Martin; Coutant, Charles; Chéreau, Elisabeth; Seror, Jeremy; Rouzier, Roman; Daraï, Emile

    2010-01-01

    Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN) procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. An SN was detected in 88.2% of cases (75/85 women). Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type

  20. Personalising pancreas cancer treatment: When tissue is the issue.

    Science.gov (United States)

    Sjoquist, Katrin M; Chin, Venessa T; Chantrill, Lorraine A; O'Connor, Chelsie; Hemmings, Chris; Chang, David K; Chou, Angela; Pajic, Marina; Johns, Amber L; Nagrial, Adnan M; Biankin, Andrew V; Yip, Desmond

    2014-06-28

    The treatment of advanced pancreatic cancer has not moved much beyond single agent gemcitabine until recently when protocols such as FOLFIRINOX (fluorouracil, leucovorin, irinotecan and oxaliplatin) and nab-paclitaxel-gemcitabine have demonstrated some improved outcomes. Advances in technology especially in massively parallel genome sequencing has progressed our understanding of the biology of pancreatic cancer especially the candidate signalling pathways that are involved in tumourogenesis and disease course. This has allowed identification of potentially actionable mutations that may be targeted by new biological agents. The heterogeneity of pancreatic cancer makes tumour tissue collection important with the aim of being able to personalise therapies for the individual as opposed to a one size fits all approach to treatment of the condition. This paper reviews the developments in this area of translational research and the ongoing clinical studies that will attempt to move this into the everyday oncology practice.

  1. Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering.

    Science.gov (United States)

    Nahid, Abdullah-Al; Mehrabi, Mohamad Ali; Kong, Yinan

    2018-01-01

    Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends on digital biomedical photography analysis such as histopathological images by doctors and physicians. Analyzing histopathological images is a nontrivial task, and decisions from investigation of these kinds of images always require specialised knowledge. However, Computer Aided Diagnosis (CAD) techniques can help the doctor make more reliable decisions. The state-of-the-art Deep Neural Network (DNN) has been recently introduced for biomedical image analysis. Normally each image contains structural and statistical information. This paper classifies a set of biomedical breast cancer images (BreakHis dataset) using novel DNN techniques guided by structural and statistical information derived from the images. Specifically a Convolutional Neural Network (CNN), a Long-Short-Term-Memory (LSTM), and a combination of CNN and LSTM are proposed for breast cancer image classification. Softmax and Support Vector Machine (SVM) layers have been used for the decision-making stage after extracting features utilising the proposed novel DNN models. In this experiment the best Accuracy value of 91.00% is achieved on the 200x dataset, the best Precision value 96.00% is achieved on the 40x dataset, and the best F -Measure value is achieved on both the 40x and 100x datasets.

  2. Are preoperative histology and MRI useful for classification of endometrial cancer risk?

    International Nuclear Information System (INIS)

    Body, Noemie; Lavoué, Vincent; De Kerdaniel, Olivier; Foucher, Fabrice; Henno, Sébastien; Cauchois, Aurélie; Laviolle, Bruno; Leblanc, Marc; Levêque, Jean

    2016-01-01

    The 2010 guidelines of the French National Cancer Institute (INCa) classify patients with endometrial cancer into three risk groups for lymph node invasion and recurrence on the basis of MRI and histological analysis of an endometrial specimen obtained preoperatively. The classification guides therapeutic choices, which may include pelvic and/or para-aortic lymphadenectomy. The purpose of this study was to evaluate the diagnostic performance of preoperative assessment to help identify intermediate- or high-risk patients requiring lymphadenectomy. The study included all patients who underwent surgery for endometrial cancer between January 2010 and December 2013 at either Rennes University Hospital or Vannes Regional Hospital. The criteria for eligibility included a preoperative assessment with MRI and histological examination of an endometrial sample. A histological comparison was made between the preoperative and surgical specimens. Among the 91 patients who underwent a full preoperative assessment, the diagnosis of intermediate- or high-risk endometrial cancer was established by MRI and histology with a sensitivity of 70 %, specificity of 82 %, positive predictive value (PPV) of 87 %, negative predictive value (NPV) of 61 %, positive likelihood ratio (LR+) of 3.8 and negative likelihood ratio (LR-) of 0.3. The risk group was underestimated in 32 % of patients and overestimated in 7 % of patients. MRI underestimated endometrial cancer stage in 20 % of cases, while endometrial sampling underestimated the histological type in 4 % of cases and the grade in 9 % of cases. The preoperative assessment overestimated or underestimated the risk of recurrence in nearly 40 % of cases, with errors in lesion type, grade or stage. Erroneous preoperative risk assessment leads to suboptimal initial surgical management of patients with endometrial cancer

  3. BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

    Science.gov (United States)

    Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

    2018-04-11

    The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes

  4. 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.

  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. Breast cancer and fatigue: issues for the workplace.

    Science.gov (United States)

    Mock, V

    1998-09-01

    1. Women with breast cancer are at high risk for fatigue as a side effect of treatment with surgery, radiation, and chemotherapy. The risk is compounded by the multiple roles of women who return to work during treatment. 2. The fatigue experience includes a physical component of decreased functional status, an affective component of emotional distress, and a cognitive component of difficulty concentrating. These characteristics of fatigue may present significant challenges for employees. 3. The Family Medical Leave Act provides 12 weeks of unpaid leave to receive medical treatment and/or recover from treatment for breast cancer. 4. The nurse in the workplace can assess and monitor the effects of fatigue and teach employees to manage fatigue through energy conservation, effective use of energy, and health promotion activities to restore energy levels.

  7. Cancer in the elderly. Demographic and epidemiological issues

    International Nuclear Information System (INIS)

    Terradas, M.; Santini, A.; Mara, C.

    2004-01-01

    Traditionally accepted 65 years as the point that separates adulthood from elderly while some authors refer to the age of 70 years, with this set arbitrarily. The total population of Uruguay, registered in the last General Population Census in 1996, reached 3,163,763 people. The adult of 65 or older population increases compared with previous Population Census (Table 1), while the other bands of ages tend to decrease. Analyzing other countries like USA, we see that the elderly population (over 65 years) is increasing, which changes the age structure of the population increase is expected continuous nursing group to which must be added that the age group that experiences further growth is precisely the older, more than 80 years. While in developed countries and in developing a marked increase is observed in life expectancy. In Uruguay life expectancy at birth is projected up being 72.7 years, countries with higher life expectancy being inside .The incidence of cancer increases and the need to know arises then best biological features of this disease in the elderly and in fact more than 60% of all cancers occur in people over 65 years and the impact of age has more weight when considering some specific tumors such as skin cancer Prostate, breast, lung and ovary. Regarding the incidence and mortality of different tumors in the elderly the same differs according to tumor type, age and sex .Datos epidemiological show a close relationship between age and tumor development. Elderly people are at risk of developing cancer 11 times greater than individuals under age 65 (16, 17). The causes of the high incidence presented by older people are not known and have proposed different theories to try to explain

  8. Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

    Science.gov (United States)

    Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik

    2018-05-01

    Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our

  9. 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

  10. Cancer survivorship: history, quality-of-life issues, and the evolving multidisciplinary approach to implementation of cancer survivorship care plans.

    Science.gov (United States)

    Morgan, Mary Ann

    2009-07-01

    To discuss the history of cancer survivorship, related quality-of-life issues, and cancer survivorship care plans (CSCPs). CINAHL, PubMed, published articles, and Web sites. A cancer survivor is an individual who has been diagnosed with cancer, regardless of when that diagnosis was received, who is still living. Cancer survivorship is complex and involves many aspects of care. Major areas of concern for survivors are recurrence, secondary malignancies, and long-term treatment sequelae that affect quality of life. Four essential components of survivorship care are prevention, surveillance, intervention, and coordination. A CSCP should address the survivor's long-term care, such as type of cancer, treatments received, potential side effects, and recommendations for follow-up. It should include preventive practices, how to maintain health and well-being, information on legal protections regarding employment and health insurance, and psychosocial services in the community. Survivorship care for patients with cancer requires a multidisciplinary effort and team approach. Enhanced knowledge of long-term complications of survivorship is needed for healthcare providers. Further research on evidence-based practice for cancer survivorship care also is necessary. Nurses can review CSCPs with patients, instruct them when to seek treatment, promote recommended surveillance protocols, and encourage behaviors that lead to cancer prevention and promote well-being for cancer survivors.

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

    Science.gov (United States)

    Rouanet, Marie; Lebrin, Marine; Gross, Fabian; Bournet, Barbara; Cordelier, Pierre; Buscail, Louis

    2017-06-08

    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.

  12. Special Issue on Global Health Disparities Focus on Cancer.

    Science.gov (United States)

    Lee, Haeok

    2016-01-01

    Haeok Lee, PhD, RN, FAAN who is a Korean-American nurse scientist, received her doctor al degree from the Nursing Physiology Department, College of Nursing, University of California, San Francisco (UCSF), in 1993, and her post doctor al training from College of Medicine, UCSF. Dr. Lee worked at Case Western Reserve University and University of Colorado Health Sciences Center. She has worked at the UMass Boston since 2008. Dr. Lee has established a long-term commitment to minority health, especially Asian American Pacific Islanders, as a community leader, community health educator, and community researcher, and all these services have become a foundation for her community-based participatory research. Dr. Lee's research addresses current health problems framed in the context of social, political, and economic settings, and her studies have improved racial and ethnic data and developed national health policies to address health disparities in hepatitis B virus (HBV) infections and liver cancer among minorities. Dr. Lee's research, which is noteworthy for its theoretical base, is clearly filling the gap. Especially, Dr. Lee's research is beginning to have a favorable impact on national and international health policies and continuing education programs directed toward the global elimination of cervical and liver cancer-related health disparities in underserved and understudied populations.

  13. 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.

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

    KAUST Repository

    Olayan, Rawan S.

    2012-01-01

    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.

  15. Cancer cell detection and classification using transformation invariant template learning methods

    International Nuclear Information System (INIS)

    Talware, Rajendra; Abhyankar, Aditya

    2011-01-01

    In traditional cancer cell detection, pathologists examine biopsies to make diagnostic assessments, largely based on cell morphology and tissue distribution. The process of image acquisition is very much subjective and the pattern undergoes unknown or random transformations during data acquisition (e.g. variation in illumination, orientation, translation and perspective) results in high degree of variability. Transformed Component Analysis (TCA) incorporates a discrete, hidden variable that accounts for transformations and uses the Expectation Maximization (EM) algorithm to jointly extract components and normalize for transformations. Further the TEMPLAR framework developed takes advantage of hierarchical pattern models and adds probabilistic modeling for local transformations. Pattern classification is based on Expectation Maximization algorithm and General Likelihood Ratio Tests (GLRT). Performance of TEMPLAR is certainly improved by defining area of interest on slide a priori. Performance can be further enhanced by making the kernel function adaptive during learning. (author)

  16. 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.

  17. Support vector machine classification and validation of cancer tissue samples using microarray expression data.

    Science.gov (United States)

    Furey, T S; Cristianini, N; Duffy, N; Bednarski, D W; Schummer, M; Haussler, D

    2000-10-01

    DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data using support vector machines (SVMs). This analysis consists of both classification of the tissue samples, and an exploration of the data for mis-labeled or questionable tissue results. We demonstrate the method in detail on samples consisting of ovarian cancer tissues, normal ovarian tissues, and other normal tissues. The dataset consists of expression experiment results for 97,802 cDNAs for each tissue. As a result of computational analysis, a tissue sample is discovered and confirmed to be wrongly labeled. Upon correction of this mistake and the removal of an outlier, perfect classification of tissues is achieved, but not with high confidence. We identify and analyse a subset of genes from the ovarian dataset whose expression is highly differentiated between the types of tissues. To show robustness of the SVM method, two previously published datasets from other types of tissues or cells are analysed. The results are comparable to those previously obtained. We show that other machine learning methods also perform comparably to the SVM on many of those datasets. The SVM software is available at http://www.cs. columbia.edu/ approximately bgrundy/svm.

  18. A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

    Directory of Open Access Journals (Sweden)

    Wang Lily

    2008-07-01

    Full Text Available Abstract Background Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate classification algorithms available for microarray gene expression data is a critical ingredient in order to develop the best possible molecular signatures for patient care. As suggested by a large body of literature to date, support vector machines can be considered "best of class" algorithms for classification of such data. Recent work, however, suggests that random forest classifiers may outperform support vector machines in this domain. Results In the present paper we identify methodological biases of prior work comparing random forests and support vector machines and conduct a new rigorous evaluation of the two algorithms that corrects these limitations. Our experiments use 22 diagnostic and prognostic datasets and show that support vector machines outperform random forests, often by a large margin. Our data also underlines the importance of sound research design in benchmarking and comparison of bioinformatics algorithms. Conclusion We found that both on average and in the majority of microarray datasets, random forests are outperformed by support vector machines both in the settings when no gene selection is performed and when several popular gene selection methods are used.

  19. An Entropy-based gene selection method for cancer classification using microarray data

    Directory of Open Access Journals (Sweden)

    Krishnan Arun

    2005-03-01

    Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

  20. Locating relationship and communication issues among stressors associated with breast cancer.

    Science.gov (United States)

    Weber, Kirsten M; Solomon, Denise Haunani

    2008-11-01

    This article clarifies how the social contexts in which breast cancer survivors live can contribute to the stress they experience because of the disease. Guided by Solomon and Knobloch's (2004) relational turbulence model and Petronio's (2002) communication privacy management theory, this study explores personal relationship and communication boundary issues within stressors that are associated with the diagnosis, treatment, and early survivorship of breast cancer. A qualitative analysis of discourse posted on breast cancer discussion boards and weblogs using the constant comparative method and open-coding techniques revealed 12 sources of stress. Using axial coding methods and probing these topics for underlying relationship and communication issues yielded 5 themes. The discussion highlights the implications of the findings for the theories that guided this investigation and for breast cancer survivorship more generally.

  1. Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

    Science.gov (United States)

    Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

    2018-01-01

    )-based classification including feature ranking was performed. The accuracy attained exceeded the 92% in overall recognition of the 7 different cancer-related skin states. The proposed integration scheme is expected to allow the co-integration with other state-of-the-art technologies such as RNA-seq.

  2. Psychosocial and Quality of Life Issues in Prostate and Ovarian Cancer

    OpenAIRE

    Madalinska, J.B.

    2007-01-01

    textabstractProstate and ovarian cancers are among the leading causes of death in Western countries. Applied preventive health strategies, including screening and early medical treatments either with prophylactic or curative intention, may substantially affect patients’ quality of life (QOL). This thesis focuses on the psychosocial and QOL issues involved in the evaluation of early-detected and treated prostate cancer among men in the general population, and in the evaluation of preventive he...

  3. 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

  4. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features

    Directory of Open Access Journals (Sweden)

    Eman Magdy

    2015-01-01

    Full Text Available Computer-aided diagnostic (CAD systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients’ lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR for classification step. Finally, K-nearest neighbour (KNN, support vector machine (SVM, naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier.

  5. 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.

  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. Quantum Dots for Cancer Research: Current Status, Remaining Issues, and Future Perspectives

    International Nuclear Information System (INIS)

    Fang, Min; Peng, Chun-wei; Pang, Dai-Wen; Li, Yan

    2012-01-01

    Cancer is a major threat to public health in the 21st century because it is one of the leading causes of death worldwide. The mechanisms of carcinogenesis, cancer invasion, and metastasis remain unclear. Thus, the development of a novel approach for cancer detection is urgent, and real-time monitoring is crucial in revealing its underlying biological mechanisms. With the optical and chemical advantages of quantum dots (QDs), QD-based nanotechnology is helpful in constructing a biomedical imaging platform for cancer behavior study. This review mainly focuses on the application of QD-based nanotechnology in cancer cell imaging and tumor microenvironment studies both in vivo and in vitro, as well as the remaining issues and future perspectives

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

    International Nuclear Information System (INIS)

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

    2013-01-01

    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. (letter)

  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. Stratification and Prognostic Relevance of Jass’s Molecular Classification of Colorectal Cancer

    International Nuclear Information System (INIS)

    Zlobec, Inti; Bihl, Michel P.; Foerster, Anja; Rufle, Alex; Terracciano, Luigi; Lugli, Alessandro

    2012-01-01

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into five subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: Three hundred two patients were included in this study. Molecular analysis was performed for five CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1), MGMT, MSI, KRAS, and BRAF. Methylation in at least 4 promoters or in one to three promoters was considered CIMP-high and CIMP-low (CIMP-H/L), respectively. Results: CIMP-H, CIMP-L, and CIMP-negative were found in 7.1, 43, and 49.9% cases, respectively. One hundred twenty-three tumors (41%) could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-L, 14 CIMP-H, and two CIMP-negative cases. The 10 year survival rate for CIMP-high patients [22.6% (95%CI: 7–43)] was significantly lower than for CIMP-L or CIMP-negative (p = 0.0295). Only the combined analysis of BRAF and CIMP (negative versus L/H) led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  11. Stratification and Prognostic Relevance of Jass’s Molecular Classification of Colorectal Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Zlobec, Inti [Institute of Pathology, University of Bern, Bern (Switzerland); Institute for Pathology, University Hospital Basel, Basel (Switzerland); Bihl, Michel P.; Foerster, Anja; Rufle, Alex; Terracciano, Luigi [Institute for Pathology, University Hospital Basel, Basel (Switzerland); Lugli, Alessandro, E-mail: inti.zlobec@pathology.unibe.ch [Institute of Pathology, University of Bern, Bern (Switzerland); Institute for Pathology, University Hospital Basel, Basel (Switzerland)

    2012-02-27

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into five subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: Three hundred two patients were included in this study. Molecular analysis was performed for five CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1), MGMT, MSI, KRAS, and BRAF. Methylation in at least 4 promoters or in one to three promoters was considered CIMP-high and CIMP-low (CIMP-H/L), respectively. Results: CIMP-H, CIMP-L, and CIMP-negative were found in 7.1, 43, and 49.9% cases, respectively. One hundred twenty-three tumors (41%) could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-L, 14 CIMP-H, and two CIMP-negative cases. The 10 year survival rate for CIMP-high patients [22.6% (95%CI: 7–43)] was significantly lower than for CIMP-L or CIMP-negative (p = 0.0295). Only the combined analysis of BRAF and CIMP (negative versus L/H) led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  12. Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

    Directory of Open Access Journals (Sweden)

    Inti eZlobec

    2012-02-01

    Full Text Available Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP, microsatellite instability (MSI, KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1, MGMT, MSI, KRAS and BRAF. Tumors were CIMP-high or CIMP-low if ≥4 and 1-3 promoters were methylated, respectively. Results: CIMP-high, CIMP-low and CIMP–negative were found in 7.1%, 43% and 49.9% cases, respectively. 123 tumors (41% could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-low, 14 CIMP-high and 2 CIMP-negative cases. The 10-year survival rate for CIMP-high patients (22.6% (95%CI: 7-43 was significantly lower than for CIMP-low or CIMP-negative (p=0.0295. Only the combined analysis of BRAF and CIMP (negative versus low/high led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  13. Men's sexual issues after breast cancer in their wives: a qualitative study.

    Science.gov (United States)

    Nasiri, Ahmad; Taleghani, Fariba; Irajpour, Alireza

    2012-01-01

    Husbands of women with breast cancer may experience problems in their sexual relationships with their wives. Adjustment to sexual issues can be affected by cultural norms and beliefs. Understanding men's perceptions and responses to their new sexual status after diagnosis of their wife's disease and during its treatment may help clinicians to better support the couple. The objective of this study was to explore the sexual issues of Iranian men after breast cancer in their wives. A qualitative research method based on the grounded theory approach was used. In-depth interviews were conducted with a purposive sampling of Iranian men experiencing breast cancer in their wives. Data analysis was based on the constant comparative method. Eighteen men were interviewed. Five main themes emerged: sexual relationship changes, sexual avoidance, sexual abstinence, sexual restraint, and efforts to normalize the relationship. The participants experienced problems in their sex lives. Because cultural and religious beliefs were important factors affecting the men's sexual adjustment, health system providers should encourage husbands to tolerate and adjust to their sexual issues in the context of their culture and religion. The findings of this study could help nurses and other healthcare professionals recognize sexual issues in the husbands of women with breast cancer and promote the couples' healthy sexual life.

  14. Contemporary management of locally advanced rectal cancer: Resolving issues, controversies and shifting paradigms.

    Science.gov (United States)

    Nacion, Aeris Jane D; Park, Youn Young; Kim, Nam Kyu

    2018-02-01

    Advancements in rectal cancer treatment have resulted in improvement only in locoregional control and have failed to address distant relapse, which is the predominant mode of treatment failure in rectal cancer. As the efficacy of conventional chemoradiotherapy (CRT) followed by total mesorectal excision (TME) reaches a plateau, the need for alternative strategies in locally advanced rectal cancer (LARC) has grown in relevance. Several novel strategies have been conceptualized to address this issue, including: 1) neoadjuvant induction and consolidation chemotherapy before CRT; 2) neoadjuvant chemotherapy alone to avoid the sequelae of radiation; and 3) nonoperative management for patients who achieved pathological or clinical complete response after CRT. This article explores the issues, recent advances and paradigm shifts in the management of LARC and emphasizes the need for a personalized treatment plan for each patient based on tumor stage, location, gene expression and quality of life.

  15. 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

  16. 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

  17. 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.

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

    Science.gov (United States)

    Barao, Katia; Forones, Nora Manoukian

    2012-01-01

    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. To compare the BMI differences according to the WHO, OPAS and Lipschitz classification. 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. 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 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.

  19. Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections.

    Science.gov (United States)

    Kuepper, Claus; Kallenbach-Thieltges, Angela; Juette, Hendrik; Tannapfel, Andrea; Großerueschkamp, Frederik; Gerwert, Klaus

    2018-05-16

    A feasibility study using a quantum cascade laser-based infrared microscope for the rapid and label-free classification of colorectal cancer tissues is presented. Infrared imaging is a reliable, robust, automated, and operator-independent tissue classification method that has been used for differential classification of tissue thin sections identifying tumorous regions. However, long acquisition time by the so far used FT-IR-based microscopes hampered the clinical translation of this technique. Here, the used quantum cascade laser-based microscope provides now infrared images for precise tissue classification within few minutes. We analyzed 110 patients with UICC-Stage II and III colorectal cancer, showing 96% sensitivity and 100% specificity of this label-free method as compared to histopathology, the gold standard in routine clinical diagnostics. The main hurdle for the clinical translation of IR-Imaging is overcome now by the short acquisition time for high quality diagnostic images, which is in the same time range as frozen sections by pathologists.

  20. Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis

    Directory of Open Access Journals (Sweden)

    Amal Saki Malehi

    2016-01-01

    Full Text Available Aims: The aim of this study was to determine the prognostic index for separating homogenous subgroups in colorectal cancer (CRC patients based on clinicopathological characteristics using survival tree analysis. Methods: The current study was conducted at the Research Center of Gastroenterology and Liver Disease, Shahid Beheshti Medical University in Tehran, between January 2004 and January 2009. A total of 739 patients who already have been diagnosed with CRC based on pathologic report were enrolled. The data included demographic and clinical-pathological characteristic of patients. Tree-structured survival analysis based on a recursive partitioning algorithm was implemented to evaluate prognostic factors. The probability curves were calculated according to the Kaplan-Meier method, and the hazard ratio was estimated as an interest effect size. Result: There were 526 males (71.2% of these patients. The mean survival time (from diagnosis time was 42.46± (3.4. Survival tree identified three variables as main prognostic factors and based on their four prognostic subgroups was constructed. The log-rank test showed good separation of survival curves. Patients with Stage I-IIIA and treated with surgery as the first treatment showed low risk (median = 34 months whereas patients with stage IIIB, IV, and more than 68 years have the worse survival outcome (median = 9.5 months. Conclusion: Constructing the prognostic classification index via survival tree can aid the researchers to assess interaction between clinical variables and determining the cumulative effect of these variables on survival outcome.

  1. A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection.

    Science.gov (United States)

    Ceccarelli, Michele; d'Acierno, Antonio; Facchiano, Angelo

    2009-10-15

    Mass spectrometry spectra, widely used in proteomics studies as a screening tool for protein profiling and to detect discriminatory signals, are high dimensional data. A large number of local maxima (a.k.a. peaks) have to be analyzed as part of computational pipelines aimed at the realization of efficient predictive and screening protocols. With this kind of data dimensions and samples size the risk of over-fitting and selection bias is pervasive. Therefore the development of bio-informatics methods based on unsupervised feature extraction can lead to general tools which can be applied to several fields of predictive proteomics. We propose a method for feature selection and extraction grounded on the theory of multi-scale spaces for high resolution spectra derived from analysis of serum. Then we use support vector machines for classification. In particular we use a database containing 216 samples spectra divided in 115 cancer and 91 control samples. The overall accuracy averaged over a large cross validation study is 98.18. The area under the ROC curve of the best selected model is 0.9962. We improved previous known results on the problem on the same data, with the advantage that the proposed method has an unsupervised feature selection phase. All the developed code, as MATLAB scripts, can be downloaded from http://medeaserver.isa.cnr.it/dacierno/spectracode.htm.

  2. Subtype classification for prediction of prognosis of breast cancer from a biomarker panel: correlations and indications

    Directory of Open Access Journals (Sweden)

    Chen C

    2014-02-01

    positive correlation (P<0.001 between the estrogen receptor and the progesterone receptor (r=0.588, but a significant negative correlation (P<0.001, r=-0.618 with the HHR subtype. There were significant differences between the estrogen receptor, progesterone receptor, and HER2 subtypes with regard to total HER2 load and hormone receptor subtypes. The rates of androgen receptor and p53 positivity were 46.3% and 57.0%, respectively. Other than the androgen receptor, differences in expression of Ki67, EGFR, and p53 did not achieve statistical significance (P>0.05 between the five subtypes. EGFR and Ki67 had prognostic significance for 5-year disease-free survival in univariate analysis, but the androgen receptor and p53 did not. Multivariate analysis identified that EGFR expression had predictive significance for 5-year disease-free survival in hormone-receptor positive patients and in those with the lymph node-positive breast cancer subtype. Conclusion: Hormone receptor expression was indeed one of the molecular profiles in the subtypes identified by quantitative HER2 and vice versa. EGFR status may provide discriminative prognostic information in addition to HER2 and hormone receptor status, and should be integrated into routine practice to help formulate more specific prediction of the prognosis and appropriate individualized treatment. Keywords: quantum dots, breast cancer, molecular classification, prognosis, prediction

  3. 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.

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

    Science.gov (United States)

    Moore, Annamarie; Higgins, Agnes; Sharek, Danika

    2013-08-01

    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. This study employed a self-completion, anonymous survey design with a sample of registered nurses working in five, randomly chosen, oncology centres in Ireland. 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. 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. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. 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.

  6. 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

  7. Methodological issues in systematic reviews of headache trials: adapting historical diagnostic classifications and outcome measures to present-day standards.

    Science.gov (United States)

    McCrory, Douglas C; Gray, Rebecca N; Tfelt-Hansen, Peer; Steiner, Timothy J; Taylor, Frederick R

    2005-05-01

    Recent efforts to make headache diagnostic classification and clinical trial methodology more consistent provide valuable advice to trialists generating new evidence on effectiveness of treatments for headache; however, interpreting older trials that do not conform to new standards remains problematic. Systematic reviewers seeking to utilize historical data can adapt currently recommended diagnostic classification and clinical trial methodological approaches to interpret all available data relative to current standards. In evaluating study populations, systematic reviewers can: (i) use available data to attempt to map study populations to diagnoses in the new International Classification of Headache Disorders; and (ii) stratify analyses based on the extent to which study populations are precisely specified. In evaluating outcome measures, systematic reviewers can: (i) summarize prevention studies using headache frequency, incorporating headache index in a stratified analysis if headache frequency is not available; (ii) summarize acute treatment studies using pain-free response as reported in directly measured headache improvement or headache severity outcomes; and (iii) avoid analysis of recurrence or relapse data not conforming to the sustained pain-free response definition.

  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....... 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. 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

  10. 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 skin cancer risk factors, other UV behaviors, or early detection information over time. The classification of indoor tanning beds as carcinogenic had no significant impact on the volume or nature of skin cancer and recreational tanning coverage in magazines.

  11. Cancerous patients and outbreak of Escherichia coli: an important issue in oncology

    OpenAIRE

    Joob, Beuy; Wiwanitkit, Viroj

    2014-01-01

    The widespread of the Escherichia coli outbreak in Europe becomes an important public concern at global level. The infection can be serious and might result in death. The retrospective literature review on this specific topic is performed. In this specific brief article, the author presented and discussed on the problem of Escherichia coli infection in the cancerous patients. This is an actual important issue in medical oncology for the scenario of Escherichia coli epidemic.

  12. Fertility preservation: A key survivorship issue for young women with cancer

    Directory of Open Access Journals (Sweden)

    Ana M Angarita

    2016-04-01

    Full Text Available 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, presence of male partner, time available and preferences regarding use of donor sperm influence the selection of the appropriate fertility preservation option. Embryo and oocyte cryopreservation are the standard techniques used while ovarian tissue cryopreservation is new, yet promising. Despite the importance of fertility preservation for cancer survivors’ quality of life, there are still communication and financial barriers faced by women who wish to pursue fertility preservation.

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

    Science.gov (United States)

    Angarita, Ana Milena; Johnson, Cynae A.; Fader, Amanda Nickles; 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, presence of male partner, time available, and preferences regarding use of donor sperm influence the selection of the appropriate fertility preservation option. Embryo and oocyte cryopreservation are the standard techniques used while ovarian tissue cryopreservation is new, yet promising. Despite the importance of fertility preservation for cancer survivors’ quality of life, there are still communication and financial barriers faced by women who wish to pursue fertility preservation. PMID:27200291

  14. Maintaining normality and support are central issues when receiving chemotherapy for ovarian cancer.

    Science.gov (United States)

    Ekman, Inger; Bergbom, Ingegerd; Ekman, Tor; Berthold, Harrieth; Mahsneh, Sawsan Majali

    2004-01-01

    The aim of this study was to enrich the understanding of patients' perspective of being diagnosed and treated for ovarian cancer. A qualitative approach was used to obtain knowledge and insight into patients' experiences and thoughts. Ten Swedish women, diagnosed with ovarian cancer, participated in a total of 23 interviews on 3 occasions: at the time of diagnosis, during chemotherapy, and after completion of chemotherapy. The results of the interpretation of the interviews were formulated in the form of 3 themes: (1) feeling the same despite radical castrating surgery, (2) accepting chemotherapy, and (3) maintaining normality and support. Suggestions of caring implications from our interpretation of the interview data underscore the need to support these women in learning to cope with their feelings of weakness and anxiety. The findings further indicate the potential in narrative methods to identify important issues in comprehensive cancer care.

  15. Electromagnetic fields and cancer: how ICNIRP has dealt with the issue

    International Nuclear Information System (INIS)

    Repacholi, M.H.

    1996-01-01

    Whether exposure to electromagnetic fields (EMFs) cause cancer has been vigorously debated for many years and has been the most vexing issue with which ICNIRP has had to deal during its short existence. There have been three parts of the electromagnetic spectrum that the issue of cancer has raised: static (0 Hz) magnetic fields, extremely low frequency (ELF) fields (defined as > 0-300 Hz, but concerns have been raised almost exclusively at the power frequencies of 50/60 Hz), and radiofrequency (RF) fields (300 Hz -300 GHz). By far the major problems have arisen during the construction of new high voltage transmission lines and mobile telephone systems. Actions by protest groups concerned with possible health effects, especially with cancer in children, has now reached such a scale that it is costing electrical utilities and communications companies billions of dollars annually world-wide. With such high stakes, ICNIRP has had to be extremely careful in its evaluation of the scientific literature, use valid and defensible methods of literature review, and be completely independent of any special interest groups. This paper summarises what criteria ICNIRP uses to review the literature, its response to EMF exposure and cancer, and its current position on static, ELF and RF fields. (author)

  16. 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.

  17. The correlation study of radiological findings with pathological classification of superficial depressed (IIc type) early gastric cancer

    International Nuclear Information System (INIS)

    Liu Linxiang; Deng Bingxing; Liu Yujin; Iinuma, G.; Moriyama, N.

    2007-01-01

    Objective: To investigate the relations between radiological findings and pathological classification of superficial depressed (II c type) early gastric cancer. Methods: Radiological features in subtonic double contrast barium examination and the endoscopic pictures of early gastric cancer compared with the global pathological specimens and micro-pathological features were prospectively studied. Combined with the gastric endoscopic pictures, the sharpness of margin of the lesions, the changes of converging mucosal folds and the changes of the depressed surface on the film of double contrast barium examination were analyzed. The correlation between the radiological features and histological classification of gastric cancer including well differentiated tubular adenocarcinoma (tub1), moderately differentiated tubular adenocarcinoma (tub2), poorly differentiated adenocarcinoma (por) and signet-ring cell carcinoma (sig) were studied. Results: In 102 cases of II c type early gastric cancer, there were tub1 27 cases, tub2 11, por 26 and sig 38 cases histologically. The margin of the depressed lesions of tubl (24 cases) and tub2 (9 cases) cancers were mostly unsharply demarcated or with fine spicular border, while the margin of lesions of por(15 cases) and sig(31 cases) were mostly clearly and sharply demarcated, with statistical significance (P<0.01). The depressed surface of tub1 and tub2 lesions (17 cases) revealed little unevenness, sometimes with evenly granulations, single nodule and scar-like depression, while that of por and sig lesions (41 cases) manifested as nodules of varying sizes, with statistical significance (P<0.01). Conclusion: The radiological findings of superficial depressed early gastric cancer in different histological types were different, the possible histological type could be speculated according to the radiological findings of the lesions. (authors)

  18. Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

    International Nuclear Information System (INIS)

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

    2013-01-01

    The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory. (paper)

  19. Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

    Science.gov (United States)

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

    2013-03-01

    The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.

  20. hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine.

    Science.gov (United States)

    Falgreen, Steffen; Ellern Bilgrau, Anders; Brøndum, Rasmus Froberg; Hjort Jakobsen, Lasse; Have, Jonas; Lindblad Nielsen, Kasper; El-Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; H Young, Ken; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

    2016-01-01

    Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays.

  1. Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

    Science.gov (United States)

    Saini, Harsh; Lal, Sunil Pranit; Naidu, Vimal Vikash; Pickering, Vincel Wince; Singh, Gurmeet; Tsunoda, Tatsuhiko; Sharma, Alok

    2016-12-05

    High dimensional feature space generally degrades classification in several applications. In this paper, we propose a strategy called gene masking, in which non-contributing dimensions are heuristically removed from the data to improve classification accuracy. Gene masking is implemented via a binary encoded genetic algorithm that can be integrated seamlessly with classifiers during the training phase of classification to perform feature selection. It can also be used to discriminate between features that contribute most to the classification, thereby, allowing researchers to isolate features that may have special significance. This technique was applied on publicly available datasets whereby it substantially reduced the number of features used for classification while maintaining high accuracies. The proposed technique can be extremely useful in feature selection as it heuristically removes non-contributing features to improve the performance of classifiers.

  2. 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.

  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. The efficacy of issuing a free coupon for breast cancer screening

    International Nuclear Information System (INIS)

    Ban, Kanako; Watanabe, Satoko; Ono, Yoshiki

    2011-01-01

    In 2009, the Japanese government introduced a new project in which a free coupon for breast cancer screening was issued. Our institution provided two mammography buses and visited 11 suburbs of Tokyo places a total of 233 times for screening with the free coupon. We classified the areas visited into two groups: those where we had sent the bus every year (usual areas), and other areas to which we had never sent the bus previously (new area). We also issued questionnaires to the coupon examinees. The number of mammography screenings conducted was 15,257 (a 71% increase). The recall rate was 6.3%, and the rate of responders for detailed examination was 60.3% in the new areas, being lower than in the other areas. The most serious problem in the new areas was that the rate of early cancer detection was 44.4%, being much lower than in the other areas. In response to the questionnaire items inquiring about womens' motivation for screening, 'individual notice' accounted for the majority of responses, followed by 'free screening'. In response to the question of how much women were prepared to pay for breast cancer screening, the majority of women stated that they would be willing to pay between 1,000 and 2,000 yen. In conclusion, the scheme for providing free coupons for breast cancer screening would appear to motivate women who have never undergone screening before. On the other hand, some problems have been exposed. In areas new to screening, a high proportion of advanced cancers were found, and there was a lower rate of response for more detailed examination. The answers received appear to indicate that women prefer to receive individual notice, rather than free screening. (author)

  6. 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 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.

  7. Breast cancer surgery and diagnosis-related groups (DRGs): patient classification and hospital reimbursement in 11 European countries.

    Science.gov (United States)

    Scheller-Kreinsen, David; Quentin, Wilm; Geissler, Alexander; Busse, Reinhard

    2013-10-01

    Researchers from eleven countries (i.e. Austria, England, Estonia, Finland, France, Germany, Ireland, Netherlands, Poland, Spain, and Sweden) compared how their DRG systems deal with breast cancer surgery patients. DRG algorithms and indicators of resource consumption were assessed for those DRGs that individually contain at least 1% of all breast cancer surgery patients. Six standardised case vignettes were defined and quasi prices according to national DRG-based hospital payment systems were ascertained. European DRG systems classify breast cancer surgery patients according to different sets of classification variables into three to seven DRGs. Quasi prices for an index case treated with partial mastectomy range from €577 in Poland to €5780 in the Netherlands. Countries award their highest payments for very different kinds of patients. Breast cancer specialists and national DRG authorities should consider how other countries' DRG systems classify breast cancer patients in order to identify potential scope for improvement and to ensure fair and appropriate reimbursement. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. 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.J.F.J.; 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.

  9. 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...

  10. Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

    Science.gov (United States)

    Ma, Ling; Lu, Guolan; Wang, Dongsheng; Wang, Xu; Chen, Zhuo Georgia; Muller, Susan; Chen, Amy; Fei, Baowei

    2017-03-01

    Hyperspectral imaging (HSI) is an emerging imaging modality that can provide a noninvasive tool for cancer detection and image-guided surgery. HSI acquires high-resolution images at hundreds of spectral bands, providing big data to differentiating different types of tissue. We proposed a deep learning based method for the detection of head and neck cancer with hyperspectral images. Since the deep learning algorithm can learn the feature hierarchically, the learned features are more discriminative and concise than the handcrafted features. In this study, we adopt convolutional neural networks (CNN) to learn the deep feature of pixels for classifying each pixel into tumor or normal tissue. We evaluated our proposed classification method on the dataset containing hyperspectral images from 12 tumor-bearing mice. Experimental results show that our method achieved an average accuracy of 91.36%. The preliminary study demonstrated that our deep learning method can be applied to hyperspectral images for detecting head and neck tumors in animal models.

  11. Breast cancer: a study of the psychosocial issues faced by women undergoing radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Burnie, C. [Hamilton Regional Cancer Centre, Hamilton, Ontario (Canada)

    2000-09-30

    The purpose of this study was to determine the psychosocial issues faced by post lumpectomy women with early stage breast cancer undergoing radical radiation to the affected breast. Twenty-five women in their second to fifth week of treatment were given the survey to determine these issues. Responses were then grouped by age category and results compiled. Regardless of age, a majority of women felt that they and their spouses had become closer since their diagnosis and described their spouses as being supportive. Scheduling appointment times around childcare was important for some women. Almost half of the women experienced a change in employment status as a result of their diagnosis. Appointment times and work schedules were important for some women still working. In all age groups, women experienced fatigue at least sometimes. (author)

  12. Breast cancer: a study of the psychosocial issues faced by women undergoing radiation therapy

    International Nuclear Information System (INIS)

    Burnie, C.

    2000-01-01

    The purpose of this study was to determine the psychosocial issues faced by post lumpectomy women with early stage breast cancer undergoing radical radiation to the affected breast. Twenty-five women in their second to fifth week of treatment were given the survey to determine these issues. Responses were then grouped by age category and results compiled. Regardless of age, a majority of women felt that they and their spouses had become closer since their diagnosis and described their spouses as being supportive. Scheduling appointment times around childcare was important for some women. Almost half of the women experienced a change in employment status as a result of their diagnosis. Appointment times and work schedules were important for some women still working. In all age groups, women experienced fatigue at least sometimes. (author)

  13. 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.

  14. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

    Directory of Open Access Journals (Sweden)

    Hala Alshamlan

    2015-01-01

    Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  15. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

    Science.gov (United States)

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

    An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  16. Future trends and emerging issues for nanodelivery systems in oral and oropharyngeal cancer

    Directory of Open Access Journals (Sweden)

    Irimie AI

    2017-06-01

    Full Text Available Alexandra Iulia Irimie,1 Laura Sonea,2 Ancuta Jurj,3 Nikolay Mehterov,4,5 Alina Andreea Zimta,2,3 Liviuta Budisan,3 Cornelia Braicu,3 Ioana Berindan-Neagoe2,3,6 1Department of Prosthodontics and Dental Materials, Faculty of Dental Medicine, 2MedFuture Research Center for Advanced Medicine, 3Research Center for Functional Genomics and Translational Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania; 4Department of Medical Biology, Medical University of Plovdiv, 5Technological Center for Emergency Medicine, Plovdiv, Bulgaria; 6Department of Functional Genomics and Experimental Pathology, Ion Chiricuta Oncology Institute, Cluj-Napoca, Romania Abstract: Oral cancer is a prevalent cancer type on a global scale, whose traditional treatment strategies have several drawbacks that could in the near future be overcome through the development of novel therapeutic and prognostic strategies. Nanotechnology provides an alternative to traditional therapy that leads to enhanced efficiency and less toxicity. Various nanosystems have been developed for the treatment of oral cancer, including polymeric, metallic, and lipid-based formulations that incorporate chemotherapeutics, natural compounds, siRNA, or other molecules. This review summarizes the main benefits of using these nanosystems, in parallel with a particular focus on the issues encountered in medical practice. These novel strategies have provided encouraging results in both in vitro and in vivo studies, but few have entered clinical trials. The use of nanosystems in oral cancer has the potential of becoming a valid therapeutic option for patients suffering from this malignancy, considering that clinical trials have already been completed and others are currently being developed. Keywords: oral cancer, nanoparticle, lipidic nanosystems, polymeric micelles, dendrimers

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

    Energy Technology Data Exchange (ETDEWEB)

    Bhooshan, Neha; Giger, Maryellen; Edwards, Darrin; Yuan Yading; Jansen, Sanaz; Li Hui; Lan Li; Newstead, Gillian [Department of Radiology, University of Chicago, Chicago, IL 60637 (United States); Sattar, Husain, E-mail: bhooshan@uchicago.edu [Department of Pathology, University of Chicago, Chicago, IL 60637 (United States)

    2011-09-21

    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.

  18. CDX2 prognostic value in stage II/III resected colon cancer is related to CMS classification.

    Science.gov (United States)

    Pilati, C; Taieb, J; Balogoun, R; Marisa, L; de Reyniès, A; Laurent-Puig, P

    2017-05-01

    Caudal-type homeobox transcription factor 2 (CDX2) is involved in colon cancer (CC) oncogenesis and has been proposed as a prognostic biomarker in patients with stage II or III CC. We analyzed CDX2 expression in a series of 469 CC typed for the new international consensus molecular subtype (CMS) classification, and we confirmed results in a series of 90 CC. Here, we show that lack of CDX2 expression is only present in the mesenchymal subgroup (CMS4) and in MSI-immune tumors (CMS1) and not in CMS2 and CMS3 colon cancer. Although CDX2 expression was a globally independent prognostic factor, loss of CDX2 expression is not associated with a worse prognosis in the CMS1 group, but is highly prognostic in CMS4 patients for both relapse free and overall survival. Similarly, lack of CDX2 expression was a bad prognostic factor in MSS patients, but not in MSI. Our work suggests that combination of the consensual CMS classification and lack of CDX2 expression could be a useful marker to identify CMS4/CDX2-negative patients with a very poor prognosis. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  19. [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.

  20. A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Jessica Roelands

    2018-02-01

    Full Text Available The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB. In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list.

  1. 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.

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

    Science.gov (United States)

    Glaab, Enrico; Bacardit, Jaume; Garibaldi, Jonathan M; Krasnogor, Natalio

    2012-01-01

    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.

  3. 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

  4. 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.

  5. 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.

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

    International Nuclear Information System (INIS)

    Parise, C. A.; Caggiano, V.

    2014-01-01

    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.

  7. 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.

  8. 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...... on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10...

  9. 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......Clinical trials are crucial to improve cancer treatment but recruitment is difficult. Optimised patient information has been recognised as a key issue. In line with the increasing focus on patients' perspectives in health care, we aimed to study patients' opinions about the written information used...... the possibility to discontinue treatment were perceived as the most important issues. Patients' views of the information in clinical trials provide new insights and identify key issues to consider in optimising future written information and may improve recruitment to clinical cancer trials....

  10. Male coping with cancer-fertility issues: putting the 'social' into biopsychosocial approaches.

    Science.gov (United States)

    Crawshaw, Marilyn

    2013-09-01

    Biopsychosocial approaches in infertility and cancer services and research pay limited attention to 'social dimensions'. Additionally, existing cancer-related male infertility research is dominated by sperm banking studies even though fertility-related social concerns in the long term are reported to have an adverse effect on wellbeing. This paper considers whether social influences affected the fertility-related experiences of 28 men interviewed as part of a mixed-gender qualitative study of 'South Asian' and 'White' cancer survivors and their professional carers. Findings are reported under: managing stigma; sexuality and virility; ambiguity in fertile status; relationship to sperm; and meaning of fatherhood. Gender and other social influences were ambiguous, fluid and subtle--yet powerful. Combinations were neither standard nor static, indicating the dangers of practitioners stereotyping, and/or assuming homogeneity of, (in)fertile men and being unaware of their own socialized expectations. Social structures and attitudes towards valued male social roles as well as the men's psychological capacity and bodily state appear to affect experience. Men may more readily be engaged if practitioners proactively attend to the impact of social concerns, including employment and financial matters, on their perceived capacity to be fathers as a route into raising issues of sexuality and fertility. Copyright © 2013 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

  11. Latency issues in epidemiologic studies of lung cancer in uranium miners

    International Nuclear Information System (INIS)

    Sever, L.E.; Petersen, G.R.

    1982-12-01

    Considerable evidence suggests that the risk of lung cancer is elevated in uranium miners exposed to radon daughter products. Important in understanding the risk of lung cancer in this population is evaluation of the time relationship of exposure to disease occurrence, that is, consideration of data relevant to the latent period. In this presentation we address theoretical considerations relating to the latent period in cohort studies and review methodological issues in research on uranium miners. We examine the problems associated with determining latent periods in censored cohort studies and suggest means of overcoming them. We discuss extant studies of lung cancer among uranium miners from the perspective of the impact of censored data on published conclusions regarding latency. In addition, we consider evidence regarding the length of the latent period in these studies and present data to support conclusions that the latent period may be: (1) more than 40 years; (2) dependent on age at which exposure begins; (3) dependent on exposure rate; and (4) related to smoking habits

  12. Assessing Unmet Information Needs of Breast Cancer Survivors: Exploratory Study of Online Health Forums Using Text Classification and Retrieval.

    Science.gov (United States)

    McRoy, Susan; Rastegar-Mojarad, Majid; Wang, Yanshan; Ruddy, Kathryn J; Haddad, Tufia C; Liu, Hongfang

    2018-05-15

    Patient education materials given to breast cancer survivors may not be a good fit for their information needs. Needs may change over time, be forgotten, or be misreported, for a variety of reasons. An automated content analysis of survivors' postings to online health forums can identify expressed information needs over a span of time and be repeated regularly at low cost. Identifying these unmet needs can guide improvements to existing education materials and the creation of new resources. The primary goals of this project are to assess the unmet information needs of breast cancer survivors from their own perspectives and to identify gaps between information needs and current education materials. This approach employs computational methods for content modeling and supervised text classification to data from online health forums to identify explicit and implicit requests for health-related information. Potential gaps between needs and education materials are identified using techniques from information retrieval. We provide a new taxonomy for the classification of sentences in online health forum data. 260 postings from two online health forums were selected, yielding 4179 sentences for coding. After annotation of data and training alternative one-versus-others classifiers, a random forest-based approach achieved F1 scores from 66% (Other, dataset2) to 90% (Medical, dataset1) on the primary information types. 136 expressions of need were used to generate queries to indexed education materials. Upon examination of the best two pages retrieved for each query, 12% (17/136) of queries were found to have relevant content by all coders, and 33% (45/136) were judged to have relevant content by at least one. Text from online health forums can be analyzed effectively using automated methods. Our analysis confirms that breast cancer survivors have many information needs that are not covered by the written documents they typically receive, as our results suggest that at most

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

    International Nuclear Information System (INIS)

    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)

  14. Clinical significance of combined detection of CYFRA21-1, NSE and CEA in classification and staging of patients with lung cancer

    International Nuclear Information System (INIS)

    Hu He; Li Yanhua; Liang Weida; Zhang Qin

    2011-01-01

    To explore clinical value of combined detection of CYFRA21-1, NSE and CEA in classification and staging of patients with lung cancer, the CYFRA21-1, NSE and CEA levels in pleural effusion in 330 patients with lung cancer and in 43 patients with benign were detected by the electrochemiluminescence. The results showed that CYFRA21-1, NSE and CEA levels in pleural effusion in patients with lung cancer group were significantly higher than that of in benign group (P<0.01). The positive rate of tumor markers in different pathological type lung cancer were different,which CYFRA21-1 positive rate in squamous cell cancer group was highest with 65.5%; CEA positive rate in glands cancer group was supreme with 65.0%; the NSE positive rate in differentiation cancer group was highest with 79.5%. The positive rate in three markers combined detection was higher than that in one item detection. The tumor marker levels in lung cancer were positively related with clinical staging. The higher of tumor marker levels and the more late of clinical staging, and the clinical III∼IV period was obviously higher than that I∼II period (P<0.05). The combined detection of CYFRA21-1, NSE and CEA may enhance the positive rate in lung cancer detection, and may have significant clinical value in the classification and staging of patients with lung cancer. (authors)

  15. 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

  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. 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.

  18. 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.

  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 follicular cell-derived thyroid cancer by global RNA profiling

    DEFF Research Database (Denmark)

    Rossing, Maria

    2013-01-01

    The incidence of thyroid cancer is increasing worldwide and thyroid nodules are a frequent clinical finding. Diagnosing follicular cell-derived cancers is, however, challenging both histopathologically and especially cytopathologically. The advent of high-throughput molecular technologies has...... profiling of follicular cell-derived thyroid cancers....... prompted many researchers to explore the transcriptome and, in recent years, also the miRNome in order to generate new molecular classifiers capable of classifying thyroid tumours more accurately than by conventional cytopathological and histopathological methods. This has led to a number of molecular...

  2. Some Issues in the Automatic Classification of U.S. Patents Working Notes for the AAAI-98 Workshop on Learning for Text Categorization

    National Research Council Canada - National Science Library

    Larkey, Leah

    1998-01-01

    The classification of U.S. patents poses some special problems due to the enormous size of the corpus, the size and complex hierarchical structure of the classification system, and the size and structure of patent documents...

  3. Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

    OpenAIRE

    Inti eZlobec; Inti eZlobec; Michel P Bihl; Anja eFoerster; Alex eRufle; Luigi eTerracciano; Alessandro eLugli; Alessandro eLugli

    2012-01-01

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related pro...

  4. Towards precise classification of cancers based on robust gene functional expression profiles

    Directory of Open Access Journals (Sweden)

    Zhu Jing

    2005-03-01

    Full Text Available Abstract Background Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level. Results Inspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles. Conclusion This modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge

  5. Policy issues in setting de minimis standards for latent cancer risks of radiation and chemical carcinogens

    International Nuclear Information System (INIS)

    Spangler, M.

    1984-01-01

    In the fuel cycles for the development and utilization of alternative energy resources, the risk of latent cancer arises from a number of sources. Included are ionizing radiation and the carcinogenic potential of polluting chemicals present in certain fuels or in materials associated with the construction, operation, maintenance or waste treatment processes of nuclear power, fossil fuels, synfuels, biomass, and other sources of energy. One aspect of developing a carcinogen guideline policy for a consistent and effective regulatory regime to use in dealing with these assorted carcinogenic risks is the setting of de minimis quantitative standards. In this report, 11 policy issues related to the setting of such regulatory standards are identified and a brief commentary is provided. 15 references, 1 table

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

    DEFF Research Database (Denmark)

    Benthien, K.S; Nordly, M.; Videbæk, K.

    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...

  7. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, H.M.J.; Moerland, P.D.; Van den Ham, R.; Reinders, M.J.T.; Verhaegh, W.F.J.

    2009-01-01

    Background: Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for

  8. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, Herman M. J.; Moerland, Perry D.; van den Ham, René; Reinders, Marcel J. T.; Verhaegh, Wim F. J.

    2009-01-01

    Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the

  9. 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.

  10. Ethical issues in autologous stem cell transplantation (ASCT in advanced breast cancer: A systematic literature review

    Directory of Open Access Journals (Sweden)

    Scheibler Fueloep

    2011-04-01

    Full Text Available Abstract Background An effectiveness assessment on ASCT in locally advanced and metastatic breast cancer identified serious ethical issues associated with this intervention. Our objective was to systematically review these aspects by means of a literature analysis. Methods We chose the reflexive Socratic approach as the review method using Hofmann's question list, conducted a comprehensive literature search in biomedical, psychological and ethics bibliographic databases and screened the resulting hits in a 2-step selection process. Relevant arguments were assembled from the included articles, and were assessed and assigned to the question list. Hofmann's questions were addressed by synthesizing these arguments. Results Of the identified 879 documents 102 included arguments related to one or more questions from Hofmann's question list. The most important ethical issues were the implementation of ASCT in clinical practice on the basis of phase-II trials in the 1990s and the publication of falsified data in the first randomized controlled trials (Bezwoda fraud, which caused significant negative effects on recruiting patients for further clinical trials and the doctor-patient relationship. Recent meta-analyses report a marginal effect in prolonging disease-free survival, accompanied by severe harms, including death. ASCT in breast cancer remains a stigmatized technology. Reported health-related-quality-of-life data are often at high risk of bias in favor of the survivors. Furthermore little attention has been paid to those patients who were dying. Conclusions The questions were addressed in different degrees of completeness. All arguments were assignable to the questions. The central ethical dimensions of ASCT could be discussed by reviewing the published literature.

  11. Ethical issues in autologous stem cell transplantation (ASCT) in advanced breast cancer: a systematic literature review.

    Science.gov (United States)

    Droste, Sigrid; Herrmann-Frank, Annegret; Scheibler, Fueloep; Krones, Tanja

    2011-04-15

    An effectiveness assessment on ASCT in locally advanced and metastatic breast cancer identified serious ethical issues associated with this intervention. Our objective was to systematically review these aspects by means of a literature analysis. We chose the reflexive Socratic approach as the review method using Hofmann's question list, conducted a comprehensive literature search in biomedical, psychological and ethics bibliographic databases and screened the resulting hits in a 2-step selection process. Relevant arguments were assembled from the included articles, and were assessed and assigned to the question list. Hofmann's questions were addressed by synthesizing these arguments. Of the identified 879 documents 102 included arguments related to one or more questions from Hofmann's question list. The most important ethical issues were the implementation of ASCT in clinical practice on the basis of phase-II trials in the 1990s and the publication of falsified data in the first randomized controlled trials (Bezwoda fraud), which caused significant negative effects on recruiting patients for further clinical trials and the doctor-patient relationship. Recent meta-analyses report a marginal effect in prolonging disease-free survival, accompanied by severe harms, including death. ASCT in breast cancer remains a stigmatized technology. Reported health-related-quality-of-life data are often at high risk of bias in favor of the survivors. Furthermore little attention has been paid to those patients who were dying. The questions were addressed in different degrees of completeness. All arguments were assignable to the questions. The central ethical dimensions of ASCT could be discussed by reviewing the published literature.

  12. Development of a computer aided diagnosis model for prostate cancer classification on multi-parametric MRI

    Science.gov (United States)

    Alfano, R.; Soetemans, D.; Bauman, G. S.; Gibson, E.; Gaed, M.; Moussa, M.; Gomez, J. A.; Chin, J. L.; Pautler, S.; Ward, A. D.

    2018-02-01

    Multi-parametric MRI (mp-MRI) is becoming a standard in contemporary prostate cancer screening and diagnosis, and has shown to aid physicians in cancer detection. It offers many advantages over traditional systematic biopsy, which has shown to have very high clinical false-negative rates of up to 23% at all stages of the disease. However beneficial, mp-MRI is relatively complex to interpret and suffers from inter-observer variability in lesion localization and grading. Computer-aided diagnosis (CAD) systems have been developed as a solution as they have the power to perform deterministic quantitative image analysis. We measured the accuracy of such a system validated using accurately co-registered whole-mount digitized histology. We trained a logistic linear classifier (LOGLC), support vector machine (SVC), k-nearest neighbour (KNN) and random forest classifier (RFC) in a four part ROI based experiment against: 1) cancer vs. non-cancer, 2) high-grade (Gleason score ≥4+3) vs. low-grade cancer (Gleason score work will form the basis for a tool that enhances the radiologist's ability to detect malignancies, potentially improving biopsy guidance, treatment selection, and focal therapy for prostate cancer patients, maximizing the potential for cure and increasing quality of life.

  13. 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.

  14. Classification of bladder cancer cell lines using Raman spectroscopy: a comparison of excitation wavelength, sample substrate and statistical algorithms

    Science.gov (United States)

    Kerr, Laura T.; Adams, Aine; O'Dea, Shirley; Domijan, Katarina; Cullen, Ivor; Hennelly, Bryan M.

    2014-05-01

    Raman microspectroscopy can be applied to the urinary bladder for highly accurate classification and diagnosis of bladder cancer. This technique can be applied in vitro to bladder epithelial cells obtained from urine cytology or in vivo as an optical biopsy" to provide results in real-time with higher sensitivity and specificity than current clinical methods. However, there exists a high degree of variability across experimental parameters which need to be standardised before this technique can be utilized in an everyday clinical environment. In this study, we investigate different laser wavelengths (473 nm and 532 nm), sample substrates (glass, fused silica and calcium fluoride) and multivariate statistical methods in order to gain insight into how these various experimental parameters impact on the sensitivity and specificity of Raman cytology.

  15. 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.

  16. 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.

  17. 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

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

    Science.gov (United States)

    Dellson, P; Nilbert, M; Bendahl, P-O; Malmström, P; Carlsson, C

    2011-07-01

    Clinical trials are crucial to improve cancer treatment but recruitment is difficult. Optimised patient information has been recognised as a key issue. In line with the increasing focus on patients' perspectives in health care, we aimed to study patients' opinions about the written information used 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 the possibility to discontinue treatment were perceived as the most important issues. Patients' views of the information in clinical trials provide new insights and identify key issues to consider in optimising future written information and may improve recruitment to clinical cancer trials. © 2010 Blackwell Publishing Ltd.

  19. Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules

    Science.gov (United States)

    Gong, Jing; Liu, Ji-Yu; Sun, Xi-Wen; Zheng, Bin; Nie, Sheng-Dong

    2018-02-01

    This study aims to develop a computer-aided diagnosis (CADx) scheme for classification between malignant and benign lung nodules, and also assess whether CADx performance changes in detecting nodules associated with early and advanced stage lung cancer. The study involves 243 biopsy-confirmed pulmonary nodules. Among them, 76 are benign, 81 are stage I and 86 are stage III malignant nodules. The cases are separated into three data sets involving: (1) all nodules, (2) benign and stage I malignant nodules, and (3) benign and stage III malignant nodules. A CADx scheme is applied to segment lung nodules depicted on computed tomography images and we initially computed 66 3D image features. Then, three machine learning models namely, a support vector machine, naïve Bayes classifier and linear discriminant analysis, are separately trained and tested by using three data sets and a leave-one-case-out cross-validation method embedded with a Relief-F feature selection algorithm. When separately using three data sets to train and test three classifiers, the average areas under receiver operating characteristic curves (AUC) are 0.94, 0.90 and 0.99, respectively. When using the classifiers trained using data sets with all nodules, average AUC values are 0.88 and 0.99 for detecting early and advanced stage nodules, respectively. AUC values computed from three classifiers trained using the same data set are consistent without statistically significant difference (p  >  0.05). This study demonstrates (1) the feasibility of applying a CADx scheme to accurately distinguish between benign and malignant lung nodules, and (2) a positive trend between CADx performance and cancer progression stage. Thus, in order to increase CADx performance in detecting subtle and early cancer, training data sets should include more diverse early stage cancer cases.

  20. 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.

  1. Study on Biopharmaceutics Classification and Oral Bioavailability of a Novel Multikinase Inhibitor NCE for Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Yang Yang

    2014-04-01

    Full Text Available Specific biopharmaceutics classification investigation and study on phamacokinetic profile of a novel drug candidate (2-methylcarbamoyl-4-{4-[3- (trifluoromethyl benzamido] phenoxy} pyridinium 4-methylbenzenesulfonate monohydrate, NCE were carried out. Equilibrium solubility and intrinsic dissolution rate (IDR of NCE were estimated in different phosphate buffers. Effective intestinal permeability (Peff of NCE was determined using single-pass intestinal perfusion technique in rat duodenum, jejunum and ileum at three concentrations. Theophylline (high permeability and ranitidine (low permeability were also applied to access the permeability of NCE as reference compounds. The bioavailability after intragastrical and intravenous administration was measured in beagle dogs. The solubility of NCE in tested phosphate buffers was quite low with the maximum solubility of 81.73 μg/mL at pH 1.0. The intrinsic dissolution ratio of NCE was 1 × 10−4 mg·min−1·cm−2. The Peff value of NCE in all intestinal segments was more proximate to the high-permeability reference theophylline. Therefore, NCE was classified as class II drug according to Biopharmaceutics Classification System due to its low solubility and high intestinal permeability. In addition, concentration-dependent permeability was not observed in all the segments, indicating that there might be passive transportation for NCE. The absolute oral bioavailability of NCE in beagle dogs was 26.75%. Therefore, dissolution promotion will be crucial for oral formulation development and intravenous administration route will also be suggested for further NCE formulation development. All the data would provide a reference for biopharmaceutics classification research of other novel drug candidates.

  2. Study on biopharmaceutics classification and oral bioavailability of a novel multikinase inhibitor NCE for cancer therapy.

    Science.gov (United States)

    Yang, Yang; Fan, Chun-Mei; He, Xuan; Ren, Ke; Zhang, Jin-Kun; He, Ying-Ju; Yu, Luo-Ting; Zhao, Ying-Lan; Gong, Chang-Yang; Zheng, Yu; Song, Xiang-Rong; Zeng, Jun

    2014-04-25

    Specific biopharmaceutics classification investigation and study on phamacokinetic profile of a novel drug candidate (2-methylcarbamoyl-4-{4-[3- (trifluoromethyl) benzamido] phenoxy} pyridinium 4-methylbenzenesulfonate monohydrate, NCE) were carried out. Equilibrium solubility and intrinsic dissolution rate (IDR) of NCE were estimated in different phosphate buffers. Effective intestinal permeability (P(eff)) of NCE was determined using single-pass intestinal perfusion technique in rat duodenum, jejunum and ileum at three concentrations. Theophylline (high permeability) and ranitidine (low permeability) were also applied to access the permeability of NCE as reference compounds. The bioavailability after intragastrical and intravenous administration was measured in beagle dogs. The solubility of NCE in tested phosphate buffers was quite low with the maximum solubility of 81.73 μg/mL at pH 1.0. The intrinsic dissolution ratio of NCE was 1 × 10⁻⁴ mg·min⁻¹·cm⁻². The P(eff) value of NCE in all intestinal segments was more proximate to the high-permeability reference theophylline. Therefore, NCE was classified as class II drug according to Biopharmaceutics Classification System due to its low solubility and high intestinal permeability. In addition, concentration-dependent permeability was not observed in all the segments, indicating that there might be passive transportation for NCE. The absolute oral bioavailability of NCE in beagle dogs was 26.75%. Therefore, dissolution promotion will be crucial for oral formulation development and intravenous administration route will also be suggested for further NCE formulation development. All the data would provide a reference for biopharmaceutics classification research of other novel drug candidates.

  3. 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.

  4. 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.

  5. Application of SVM classifier in thermographic image classification for early detection of breast cancer

    Science.gov (United States)

    Oleszkiewicz, Witold; Cichosz, Paweł; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał

    2016-09-01

    This article presents the application of machine learning algorithms for early detection of breast cancer on the basis of thermographic images. Supervised learning model: Support vector machine (SVM) and Sequential Minimal Optimization algorithm (SMO) for the training of SVM classifier were implemented. The SVM classifier was included in a client-server application which enables to create a training set of examinations and to apply classifiers (including SVM) for the diagnosis and early detection of the breast cancer. The sensitivity and specificity of SVM classifier were calculated based on the thermographic images from studies. Furthermore, the heuristic method for SVM's parameters tuning was proposed.

  6. Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations

    Science.gov (United States)

    2014-01-01

    Introduction Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. Methods An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). Results The original training cohort reached a statistically significant difference (p risk groups. Conclusions Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments. PMID:24996446

  7. 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 ( ...

  8. 6 Common Cancers - Skin Cancer

    Science.gov (United States)

    ... Bar Home Current Issue Past Issues 6 Common Cancers - Skin Cancer Past Issues / Spring 2007 Table of Contents ... AP Photo/Herald-Mail, Kevin G. Gilbert Skin Cancer Skin cancer is the most common form of cancer ...

  9. 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 ...

  10. 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...

  11. Prognostic classification with laboratory parameters or imaging techniques in small-cell lung cancer

    NARCIS (Netherlands)

    de Jong, Wouter K.; Fidler, Vaclav; Groen, Harry J. M.

    PURPOSE: Our aim in this study was to compare prognostic models based on laboratory tests with a model including imaging information in small-cell lung cancer. PATIENTS AND METHODS: A retrospective analysis was performed on 156 consecutive patients. Three existing models based on laboratory tests

  12. Towards a molecular classification of colorectal cancer: The role of BRAF

    Directory of Open Access Journals (Sweden)

    Alexandra eThiel

    2013-11-01

    Full Text Available Different genetic aberrations of BRAF have been reported in various malignancies. BRAF is member of the RAS/RAF/MEK/ERK pathway and constitutive activity of this pathway can lead to increased cellular growth, invasion, and metastasis. The most common activating BRAF mutation in colorectal cancer is the V600E mutation, which is present in 5-15% of all tumors, and up to 80% of tumors with high microsatellite instability harbor this mutation. BRAF mutation is associated with proximal location, higher age, female gender, MSI-H, high grade, and mucinous histology, and is a marker of poor prognosis in colorectal cancer. The role of BRAF mutation as a predictive marker in respect of EGFR targeted treatments is controversial. BRAF V600 selective inhibitors have been approved for the treatment of V600 mutation positive metastatic melanoma, but the response rates in colorectal cancer are poor. This might be due to innate resistance mechanisms of colorectal cancers against the treatment solely targeting BRAF. To overcome resistance the combination of treatments, simultaneous inhibition of BRAF and MEK or PI3K/mTOR, might emerge as a successful therapeutic concept.

  13. Israeli and Chinese partners of women with breast cancer: a cross-cultural view of marital issues.

    Science.gov (United States)

    Woloski-Wruble, Anna C; Dekeyzer Ganz, Freda; Jiang, Yongqin; Qiang, Wan-Min; Kadmon, Ilana

    2012-03-01

    Cultural nuances may influence the interface between the cancer experience and marital issues, specifically for the partner. Most of the literature has focused on the woman's narrative or couple's adjustment to cancer in general. The purpose of this study was to describe and compare the marital relationship, sexuality, and marital adjustment of Israeli and Chinese husbands of women with breast cancer and the discussion of the health-care team concerning these issues. A convenience sample of 50 Chinese and 50 Israeli men, ages of 28-79 years, completed components of the Psychological Adjustment to Illness Scale, the Locke Wallace Adjustment Scale, and a background questionnaire. The majority of husbands were in their first marriage. The average time since diagnosis was 16.7 months. No significant difference was found between the two groups on issues of marital relationship. Significant differences were found between Israeli and Chinese husbands on sexual interest, pleasure, and performance (pcultural differences were found in sexuality variables with no differences discerned on marital relationship variables. Couple-based interventions for marital issues are a critical component of support for both partners. Culturally sensitive assessment and care of the spouse as well as the woman with breast cancer should be part of a holistic, comprehensive family care plan. Copyright © 2011 John Wiley & Sons, Ltd.

  14. Topics in this issue: cancer testes antigens, immune checkpoints, inflammation associated with ischemia-reperfusion and integrin targeting.

    Science.gov (United States)

    Bot, Adrian; Chiriva-Internati, Maurizio

    2012-10-01

    This issue of the International Reviews of Immunology is dedicated to several topics: cancer immunotherapy, and basic and translational aspects of immunity. Two reviews, one focused on breast and the other on lung cancer, highlight the need to redefine the cancer testes antigens (CTAs) as novel information regarding their expression profile and biological role emerges. Two other reviews showcase pivotal molecules that keep in check immunity at two different levels: the transcription factor autoimmune regulator (AIRE) important to negative selection of the T-cell repertoire, and CD22 that limits the antigen-initiated B-cell response. Two other articles focus on the debated role of Toll-like receptors (TLRs) and inflammation in general, in ischemia-reperfusion lesions that follow cardiovascular disorders and stroke. Last but not the least, this issue hosts a review that discusses the role and translational potential of the α4 integrin for the treatment of inflammatory bowel disease (IBD).

  15. A multigene mutation classification of 468 colorectal cancers reveals a prognostic role for APC

    Science.gov (United States)

    Schell, Michael J.; Yang, Mingli; Teer, Jamie K.; Lo, Fang Yin; Madan, Anup; Coppola, Domenico; Monteiro, Alvaro N. A.; Nebozhyn, Michael V.; Yue, Binglin; Loboda, Andrey; Bien-Willner, Gabriel A.; Greenawalt, Danielle M.; Yeatman, Timothy J.

    2016-01-01

    Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinicopathologic staging for decades. There is a need to stratify subpopulations of CRC on a molecular basis to better predict outcome and assign therapies. Here we report targeted exome-sequencing of 1,321 cancer-related genes on 468 tumour specimens, which identified a subset of 17 genes that best classify CRC, with APC playing a central role in predicting overall survival. APC may assume 0, 1 or 2 truncating mutations, each with a striking differential impact on survival. Tumours lacking any APC mutation carry a worse prognosis than single APC mutation tumours; however, two APC mutation tumours with mutant KRAS and TP53 confer the poorest survival among all the subgroups examined. Our study demonstrates a prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC. PMID:27302369

  16. 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.

  17. Validation of the RTOG recursive partitioning analysis (RPA) classification for small-cell lung cancer-only brain metastases

    International Nuclear Information System (INIS)

    Videtic, Gregory M.M.; Adelstein, David J.; Mekhail, Tarek M.; Rice, Thomas W.; Stevens, Glen H.J.; Lee, S.-Y.; Suh, John H.

    2007-01-01

    Purpose: Radiation Therapy Oncology Group (RTOG) developed a prognostic classification based on a recursive partitioning analysis (RPA) of patient pretreatment characteristics from three completed brain metastases randomized trials. Clinical trials for patients with brain metastases generally exclude small-cell lung cancer (SCLC) cases. We hypothesize that the RPA classes are valid in the setting of SCLC brain metastases. Methods and Materials: A retrospective review of 154 SCLC patients with brain metastases treated between April 1983 and May 2005 was performed. RPA criteria used for class assignment were Karnofsky performance status (KPS), primary tumor status (PT), presence of extracranial metastases (ED), and age. Results: Median survival was 4.9 months, with 4 patients (2.6%) alive at analysis. Median follow-up was 4.7 months (range, 0.3-40.3 months). Median age was 65 (range, 42-85 years). Median KPS was 70 (range, 40-100). Number of patients with controlled PT and no ED was 20 (13%) and with ED, 27 (18%); without controlled PT and ED, 34 (22%) and with ED, 73 (47%). RPA class distribution was: Class I: 8 (5%); Class II: 96 (62%); Class III: 51 (33%). Median survivals (in months) by RPA class were: Class I: 8.6; Class II: 4.2; Class III: 2.3 (p = 0.0023). Conclusions: Survivals for SCLC-only brain metastases replicate the results from the RTOG RPA classification. These classes are therefore valid for brain metastases from SCLC, support the inclusion of SCLC patients in future brain metastases trials, and may also serve as a basis for historical comparisons

  18. Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations.

    Science.gov (United States)

    Wang, Dong-Yu; Done, Susan J; Mc Cready, David R; Leong, Wey L

    2014-07-04

    Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). The original training cohort reached a statistically significant difference (p value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups. Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments.

  19. 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…

  20. Cancer classification through filtering progressive transductive support vector machine based on gene expression data

    Science.gov (United States)

    Lu, Xinguo; Chen, Dan

    2017-08-01

    Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

  1. Inflammation, Adenoma and Cancer: Objective Classification of Colon Biopsy Specimens with Gene Expression Signature

    Directory of Open Access Journals (Sweden)

    Orsolya Galamb

    2008-01-01

    Full Text Available Gene expression analysis of colon biopsies using high-density oligonucleotide microarrays can contribute to the understanding of local pathophysiological alterations and to functional classification of adenoma (15 samples, colorectal carcinomas (CRC (15 and inflammatory bowel diseases (IBD (14. Total RNA was extracted, amplified and biotinylated from frozen colonic biopsies. Genome-wide gene expression profile was evaluated by HGU133plus2 microarrays and verified by RT-PCR. We applied two independent methods for data normalization and used PAM for feature selection. Leave one-out stepwise discriminant analysis was performed. Top validated genes included collagenIVα1, lipocalin-2, calumenin, aquaporin-8 genes in CRC; CD44, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; and lipocalin-2, ubiquitin D and IFITM2 genes in IBD. Best differentiating markers between Ulcerative colitis and Crohn's disease were cyclin-G2; tripartite motif-containing-31; TNFR shedding aminopeptidase regulator-1 and AMICA. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes (indoleamine-pyrrole-2,3-dioxygenase, ectodermal-neural cortex, TIMP3, fucosyltransferase-8, collectin sub-family member 12, carboxypeptidase D, and transglutaminase-2. Using routine biopsy samples we successfully performed whole genomic microarray analysis to identify discriminative signatures. Our results provide further insight into the pathophysiological background of colonic diseases. The results set up data warehouse which can be mined further.

  2. Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

    Science.gov (United States)

    Fusco, Roberta; Sansone, Mario; Filice, Salvatore; Carone, Guglielmo; Amato, Daniela Maria; Sansone, Carlo; Petrillo, Antonella

    2016-01-01

    We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented. The sensitivity and specificity are respectively 91 and 83 % for ANN, 85 and 82 % for SVM, 96 and 85 % for LDA, 92 and 87 % for TC, and 82 and 85 % for BC. The sensitivity and specificity are respectively 82 and 74 % for dynamic features, 93 and 60 % for morphological features, 88 and 81 % for textural features, 95 and 86 % for a combination of dynamic and morphological features, and 88 and 84 % for a combination of dynamic, morphological, and other features. LDA and TC have the best performance. A combination of dynamic and morphological features gives the best performance.

  3. Classification of Breast Cancer Resistant Protein (BCRP) Inhibitors and Non-Inhibitors Using Machine Learning Approaches.

    Science.gov (United States)

    Belekar, Vilas; Lingineni, Karthik; Garg, Prabha

    2015-01-01

    The breast cancer resistant protein (BCRP) is an important transporter and its inhibitors play an important role in cancer treatment by improving the oral bioavailability as well as blood brain barrier (BBB) permeability of anticancer drugs. In this work, a computational model was developed to predict the compounds as BCRP inhibitors or non-inhibitors. Various machine learning approaches like, support vector machine (SVM), k-nearest neighbor (k-NN) and artificial neural network (ANN) were used to develop the models. The Matthews correlation coefficients (MCC) of developed models using ANN, k-NN and SVM are 0.67, 0.71 and 0.77, and prediction accuracies are 85.2%, 88.3% and 90.8% respectively. The developed models were tested with a test set of 99 compounds and further validated with external set of 98 compounds. Distribution plot analysis and various machine learning models were also developed based on druglikeness descriptors. Applicability domain is used to check the prediction reliability of the new molecules.

  4. Classification of hospital pathways in the management of cancer: application to lung cancer in the region of burgundy.

    Science.gov (United States)

    Nuemi, G; Afonso, F; Roussot, A; Billard, L; Cottenet, J; Combier, E; Diday, E; Quantin, C

    2013-10-01

    The evaluation of national cancer plans is an important aspect of their implementation. For this evaluation, the principal actors in the field (doctors, nurses, etc.) as well as decision-makers must have access to information that is reliable, synthetic and easy to interpret, and which reflects the implementation process in the field. We propose here a methodology to make this type of information available in the context of reducing inequalities with regard to access to healthcare for patients with lung cancer in the region of Burgundy. We used the national medico-administrative DRG-type database, which gathers together all hospital stays. By using this database, it was possible to identify and reconstruct the care management history of these patients. That is, by linking together all attended hospitals, sorted chronologically. Eligible patients were at least 18 years old, whatever the gender and had undergone surgery for their lung cancer. They had to be residents of Burgundy at the time of the first operation between 2006 and 2008. Patient's pathway was defined as the sequence of all attended hospitals (hospital stays) during the year of follow up linked together using an anonymised patient identifier. We then constructed a pathway typology of pathway using an unsupervised clustering method, and conducted a spatial analysis of this typology. Between 2006 and 2008, we selected 495 patients in the 4 administrative departments of the Burgundy region. They accounted for a total of 3821 stays during the year of follow-up. There were 393 men (79%) and the mean age was 64 (95% confidence interval: 63-65) years. We reconstructed 94 pathways (about five per patient). Here, neighbourhood's cares accounted for 41% of them, while 44% included a surgical intervention outside the region of Burgundy. We constructed a pathway typology with five classes. Spatial analysis showed that the vast majority of initial surgeries took place in the major regional centres. The construction

  5. Clinical and Pathological Staging Validation in the Eighth Edition of the TNM Classification for Lung Cancer: Correlation between Solid Size on Thin-Section Computed Tomography and Invasive Size in Pathological Findings in the New T Classification.

    Science.gov (United States)

    Aokage, Keiju; Miyoshi, Tomohiro; Ishii, Genichiro; Kusumoto, Masahiro; Nomura, Shogo; Katsumata, Shinya; Sekihara, Keigo; Hishida, Tomoyuki; Tsuboi, Masahiro

    2017-09-01

    The aim of this study was to validate the new eighth edition of the TNM classification and to elucidate whether radiological solid size corresponds to pathological invasive size incorporated in this T factor. We analyzed the data on 1792 patients who underwent complete resection from 2003 to 2011 at the National Cancer Center Hospital East, Japan. We reevaluated preoperative thin-section computed tomography (TSCT) to determine solid size and pathological invasive size using the fourth edition of the WHO classification and reclassified them according to the new TNM classification. The discriminative power of survival curves by the seventh edition was compared with that by the eighth edition by using concordance probability estimates and Akaike's information criteria calculated using a univariable Cox regression model. Pearson's correlation coefficient was calculated to elucidate the correlation between radiological solid size using TSCT and pathological invasive size. The overall survival curves in the eighth edition were well distinct at each clinical and pathological stage. The 5-year survival rates of patients with clinical and pathological stage 0 newly defined were both 100%. The concordance probability estimate and Akaike's information criterion values of the eighth edition were higher than those of the seventh edition in discriminatory power for overall survival. Solid size on TSCT scan and pathological invasive size showed a positive linear relationship, and Pearson's correlation coefficient was calculated as 0.83, which indicated strong correlation. This TNM classification will be feasible regarding patient survival, and radiological solid size correlates significantly with pathological invasive size as a new T factor. Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  6. 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

  7. Prognostic significance of visceral pleural invasion in the forthcoming (seventh) edition of TNM classification for lung cancer.

    Science.gov (United States)

    Shim, Hyo Sup; Park, In Kyu; Lee, Chang Young; Chung, Kyung Young

    2009-08-01

    The next revision to the TNM classification for lung cancer (the seventh edition) is scheduled to be released in 2009. However, the definition of visceral pleural invasion (VPI), which is a non-size-based T2 descriptor, still lacks in detail, and its validation is not included. We analyzed 1046 cases of non-small cell lung cancer (NSCLC) with T1, T2, or T3 diseases from 1990 to 2005, and subclassified into p0-p3 according to the degrees of pleural invasion. Survival analyses were performed using Kaplan-Meier method. Then, all patients were subdivided into nine groups according to tumor size and pleural invasion, and we compared survival differences, primarily focusing on T2a and T2b diseases according to the seventh edition. There was no survival difference between patients with p1 and p2, thus we regarded p1 or p2 as VPI. There was survival difference between two groups, which are expected to be classified as T2b. The behavior of tumors larger than 5cm but 7cm or less with VPI was similar to T3 tumors. VPI is a poor prognostic factor of NSCLC, and the penetration through the elastic layer of the visceral pleura regardless of its exposure on the pleural surface (pl and p2) should be defined as VPI. This study also indicates that VPI influences T stage dependent on tumor size, and it can be suggested that tumors of larger than 5cm but 7cm or less with VPI should be upgraded to T3 stage.

  8. Improving supervised classification accuracy using non-rigid multimodal image registration: detecting prostate cancer

    Science.gov (United States)

    Chappelow, Jonathan; Viswanath, Satish; Monaco, James; Rosen, Mark; Tomaszewski, John; Feldman, Michael; Madabhushi, Anant

    2008-03-01

    Computer-aided diagnosis (CAD) systems for the detection of cancer in medical images require precise labeling of training data. For magnetic resonance (MR) imaging (MRI) of the prostate, training labels define the spatial extent of prostate cancer (CaP); the most common source for these labels is expert segmentations. When ancillary data such as whole mount histology (WMH) sections, which provide the gold standard for cancer ground truth, are available, the manual labeling of CaP can be improved by referencing WMH. However, manual segmentation is error prone, time consuming and not reproducible. Therefore, we present the use of multimodal image registration to automatically and accurately transcribe CaP from histology onto MRI following alignment of the two modalities, in order to improve the quality of training data and hence classifier performance. We quantitatively demonstrate the superiority of this registration-based methodology by comparing its results to the manual CaP annotation of expert radiologists. Five supervised CAD classifiers were trained using the labels for CaP extent on MRI obtained by the expert and 4 different registration techniques. Two of the registration methods were affi;ne schemes; one based on maximization of mutual information (MI) and the other method that we previously developed, Combined Feature Ensemble Mutual Information (COFEMI), which incorporates high-order statistical features for robust multimodal registration. Two non-rigid schemes were obtained by succeeding the two affine registration methods with an elastic deformation step using thin-plate splines (TPS). In the absence of definitive ground truth for CaP extent on MRI, classifier accuracy was evaluated against 7 ground truth surrogates obtained by different combinations of the expert and registration segmentations. For 26 multimodal MRI-WMH image pairs, all four registration methods produced a higher area under the receiver operating characteristic curve compared to that

  9. Can-CSC-GBE: Developing Cost-sensitive Classifier with Gentleboost Ensemble for breast cancer classification using protein amino acids and imbalanced data.

    Science.gov (United States)

    Ali, Safdar; Majid, Abdul; Javed, Syed Gibran; Sattar, Mohsin

    2016-06-01

    Early prediction of breast cancer is important for effective treatment and survival. We developed an effective Cost-Sensitive Classifier with GentleBoost Ensemble (Can-CSC-GBE) for the classification of breast cancer using protein amino acid features. In this work, first, discriminant information of the protein sequences related to breast tissue is extracted. Then, the physicochemical properties hydrophobicity and hydrophilicity of amino acids are employed to generate molecule descriptors in different feature spaces. For comparison, we obtained results by combining Cost-Sensitive learning with conventional ensemble of AdaBoostM1 and Bagging. The proposed Can-CSC-GBE system has effectively reduced the misclassification costs and thereby improved the overall classification performance. Our novel approach has highlighted promising results as compared to the state-of-the-art ensemble approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Regularization strategies for hyperplane classifiers: application to cancer classification with gene expression data.

    Science.gov (United States)

    Andries, Erik; Hagstrom, Thomas; Atlas, Susan R; Willman, Cheryl

    2007-02-01

    Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.

  11. Detection of Gastric Cancer with Fourier Transform Infrared Spectroscopy and Support Vector Machine Classification

    Directory of Open Access Journals (Sweden)

    Qingbo Li

    2013-01-01

    Full Text Available Early diagnosis and early medical treatments are the keys to save the patients' lives and improve the living quality. Fourier transform infrared (FT-IR spectroscopy can distinguish malignant from normal tissues at the molecular level. In this paper, programs were made with pattern recognition method to classify unknown samples. Spectral data were pretreated by using smoothing and standard normal variate (SNV methods. Leave-one-out cross validation was used to evaluate the discrimination result of support vector machine (SVM method. A total of 54 gastric tissue samples were employed in this study, including 24 cases of normal tissue samples and 30 cases of cancerous tissue samples. The discrimination results of SVM method showed the sensitivity with 100%, specificity with 83.3%, and total discrimination accuracy with 92.2%.

  12. Constructing Support Vector Machine Ensembles for Cancer Classification Based on Proteomic Profiling

    Institute of Scientific and Technical Information of China (English)

    Yong Mao; Xiao-Bo Zhou; Dao-Ying Pi; You-Xian Sun

    2005-01-01

    In this study, we present a constructive algorithm for training cooperative support vector machine ensembles (CSVMEs). CSVME combines ensemble architecture design with cooperative training for individual SVMs in ensembles. Unlike most previous studies on training ensembles, CSVME puts emphasis on both accuracy and collaboration among individual SVMs in an ensemble. A group of SVMs selected on the basis of recursive classifier elimination is used in CSVME, and the number of the individual SVMs selected to construct CSVME is determined by 10-fold cross-validation. This kind of SVME has been tested on two ovarian cancer datasets previously obtained by proteomic mass spectrometry. By combining several individual SVMs, the proposed method achieves better performance than the SVME of all base SVMs.

  13. 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.

  14. 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.

  15. [Evaluation and classification of drug therapy for breast cancer with bone-only metastasis].

    Science.gov (United States)

    Meng, X Y; Song, S T

    2017-03-23

    Skeleton is one of the most common metastatic organs for breast cancer, which has a better prognosis than visceral metastases. Bone-only metastasis was defined"non-measurable" in the RECIST (Response Evaluation Criteria in Solid Tumors) criteria, and was excluded by clinical trials. However, patients with bone-only metastasis are also in need of effective treatment to prolong survival. Endocrine therapy is the most important treatment for bone metastatic patients. Tumor response of bone metastases can be determined objectively by bone-window CT. Effective treatment should be continued if the symptoms are relieved or osteogenesis is observed. Osteoblastic change in bone-window CT is a sign of improvement after treatment. Endocrine therapy is proper for ER-positive patients. The patients with initial osteoblastic metastasis should not be treated with salvage chemotherapy or anti-HER2 treatment, only if osteolytic metastasis or visceral metastasis is observed. Bishosphonates are just auxiliary drugs in bone metastasis, which should not be abused.

  16. 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 ...

  17. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

    This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

  18. 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.

  19. Functional challenges among late effects cancer survivors: a preliminary report on work engagement issues.

    Science.gov (United States)

    Crist, Patricia

    2013-01-01

    While the cancer survivor rate is nearly 68% now, intervention regimens may leave residual conditions that impact engagement in work and various life tasks. Survivors are underemployed and report stigmatizing attitudes among co-workers. When late effects from cancer arise over 10 years later, the impact on individuals in the prime of their productive employment life is evident. Assisting these individuals begins with awareness of late effects in order to create work-related, adaptive strategies. Sixteen adult cancer survivors experiencing late effects completed the Occupational Self Assessment (Version 2.2) and the Quality of Life-Cancer Survivors (QOL-CS). Knowledge of functional problems secondary to recognized late effects medical conditions reported in the literature was utilized to sort items according to professional definitions of work, performance skills and performance patterns. Late effects survivors reported that cancer illness and treatment has negatively impacted their employment. Individual response to the impact of late effects is highly variant. "Getting things done" and physical energy limitations are most pronounced. Cancer survivors report lower competence in significant work-related skills and patterns. Quality of life associated with the aftereffects of fatigue, aches and pain, and sleep changes are the lowest. Responses range across the 16 survivors to both performance skills and performance patterns. Cancer survivorship has clearly interfered with employment. An interdisciplinary focus on meaningful engagement in life activities, particularly work is crucial to support survivors through advocacy, adaptation and positive change to focus on engaging the work talents and gifts for all cancer survivors.

  20. Localized Prostate Cancer and Quality of Life: Screening, treatment and methodological issues

    NARCIS (Netherlands)

    I.J. Korfage (Ida)

    2005-01-01

    textabstractIn Western countries prostate cancer is the most prevalent malignancy in males. In its early stage prostate cancer usually does not cause any pain or other symptoms. It can be detected early by testing for prostate-specific antigen (PSA). Since the 1980s the PSA-test has been applied

  1. Advice about Work-Related Issues to Peers and Employers from Head and Neck Cancer Survivors

    NARCIS (Netherlands)

    Dewa, Carolyn S.; Trojanowski, Lucy; Tamminga, Sietske J.; Ringash, Jolie; McQuestion, Maurene; Hoch, Jeffrey S.

    2016-01-01

    The purpose of this exploratory and descriptive study is to contribute to the sparse return-to-work literature on head and neck cancer (HNC) survivors. Interview participants were asked to reflect upon their work-related experience with cancer by answering two specific questions: (1) What advice

  2. 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

  3. 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.

  4. 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....

  5. Integrated genomic and immunophenotypic classification of pancreatic cancer reveals three distinct subtypes with prognostic/predictive significance.

    Science.gov (United States)

    Wartenberg, Martin; Cibin, Silvia; Zlobec, Inti; Vassella, Erik; Eppenberger-Castori, Serenella M M; Terracciano, Luigi; Eichmann, Micha; Worni, Mathias; Gloor, Beat; Perren, Aurel; Karamitopoulou, Eva

    2018-04-16

    Current clinical classification of pancreatic ductal adenocarcinoma (PDAC) is unable to predict prognosis or response to chemo- or immunotherapy and does not take into account the host reaction to PDAC-cells. Our aim is to classify PDAC according to host- and tumor-related factors into clinically/biologically relevant subtypes by integrating molecular and microenvironmental findings. A well-characterized PDAC-cohort (n=110) underwent next-generation sequencing with a hotspot cancer panel, while Next-generation Tissue-Microarrays were immunostained for CD3, CD4, CD8, CD20, PD-L1, p63, hyaluronan-mediated motility receptor (RHAMM) and DNA mismatch-repair proteins. Previous data on FOXP3 were integrated. Immune-cell counts and protein expression were correlated with tumor-derived driver mutations, clinicopathologic features (TNM 8. 2017), survival and epithelial-mesenchymal-transition (EMT)-like tumor budding.  Results: Three PDAC-subtypes were identified: the "immune-escape" (54%), poor in T- and B-cells and enriched in FOXP3+Tregs, with high-grade budding, frequent CDKN2A- , SMAD4- and PIK3CA-mutations and poor outcome; the "immune-rich" (35%), rich in T- and B-cells and poorer in FOXP3+Tregs, with infrequent budding, lower CDKN2A- and PIK3CA-mutation rate and better outcome and a subpopulation with tertiary lymphoid tissue (TLT), mutations in DNA damage response genes (STK11, ATM) and the best outcome; and the "immune-exhausted" (11%) with immunogenic microenvironment and two subpopulations: one with PD-L1-expression and high PIK3CA-mutation rate and a microsatellite-unstable subpopulation with high prevalence of JAK3-mutations. The combination of low budding, low stromal FOXP3-counts, presence of TLTs and absence of CDKN2A-mutations confers significant survival advantage in PDAC-patients. Immune host responses correlate with tumor characteristics leading to morphologically recognizable PDAC-subtypes with prognostic/predictive significance. Copyright ©2018

  6. Distinct clinical outcomes of two CIMP-positive colorectal cancer subtypes based on a revised CIMP classification system.

    Science.gov (United States)

    Bae, Jeong Mo; Kim, Jung Ho; Kwak, Yoonjin; Lee, Dae-Won; Cha, Yongjun; Wen, Xianyu; Lee, Tae Hun; Cho, Nam-Yun; Jeong, Seung-Yong; Park, Kyu Joo; Han, Sae Won; Lee, Hye Seung; Kim, Tae-You; Kang, Gyeong Hoon

    2017-04-11

    Colorectal cancer (CRC) is a heterogeneous disease in terms of molecular carcinogenic pathways. Based on recent findings regarding the multiple serrated neoplasia pathway, we revised an eight-marker panel for a new CIMP classification system. 1370 patients who received surgical resection for CRCs were classified into three CIMP subtypes (CIMP-N: 0-4 methylated markers, CIMP-P1: 5-6 methylated markers and CIMP-P2: 7-8 methylated markers). Our findings were validated in a separate set of high-risk stage II or stage III CRCs receiving adjuvant fluoropyrimidine plus oxaliplatin (n=950). A total of 1287/62/21 CRCs cases were classified as CIMP-N/CIMP-P1/CIMP-P2, respectively. CIMP-N showed male predominance, distal location, lower T, N category and devoid of BRAF mutation, microsatellite instability (MSI) and MLH1 methylation. CIMP-P1 showed female predominance, proximal location, advanced TNM stage, mild decrease of CK20 and CDX2 expression, mild increase of CK7 expression, BRAF mutation, MSI and MLH1 methylation. CIMP-P2 showed older age, female predominance, proximal location, advanced T category, markedly reduced CK20 and CDX2 expression, rare KRAS mutation, high frequency of CK7 expression, BRAF mutation, MSI and MLH1 methylation. CIMP-N showed better 5-year cancer-specific survival (CSS; HR=0.47; 95% CI: 0.28-0.78) in discovery set and better 5-year relapse-free survival (RFS; HR=0.50; 95% CI: 0.29-0.88) in validation set compared with CIMP-P1. CIMP-P2 showed marginally better 5-year CSS (HR=0.28, 95% CI: 0.07-1.22) in discovery set and marginally better 5-year RFS (HR=0.21, 95% CI: 0.05-0.92) in validation set compared with CIMP-P1. CIMP subtypes classified using our revised system showed different clinical outcomes, demonstrating the heterogeneity of multiple serrated precursors of CIMP-positive CRCs.

  7. A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

    Directory of Open Access Journals (Sweden)

    Abdullah M. Iliyasu

    2017-12-01

    Full Text Available 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.

  8. 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.

  9. Bladder Cancer in HIV-infected Adults: An Emerging Issue? Case-Reports and Systematic Review.

    Directory of Open Access Journals (Sweden)

    Sylvain Chawki

    Full Text Available Non-AIDS-related malignancies now represent a frequent cause of death among HIV-infected patients. Albeit bladder cancer is one of the most common malignancies worldwide, it has been rarely reported among HIV-infected patients. We wished to assess the prevalence and characteristics of bladder cancer in HIV-infected patients.We conducted a single center retrospective study from 1998 to 2013 in a university hospital in Paris. Cases of bladder cancer among HIV-infected patients were identified using the electronic records of the hospital database and of the HIV-infected cohort. Patient characteristics and outcomes were retrieved from patients charts. A systematic review of published cases of bladder cancers in patients with HIV-infection was also performed.During the study period we identified 15 HIV-infected patients (0.2% of the cohort with a bladder cancer. Patients were mostly men (73% and smokers (67%, with a median age of 56 years at cancer diagnosis. Bladder cancer was diagnosed a median of 14 years after HIV-infection. Most patients were on ART (86% with median current and nadir CD4 cell counts of 506 and 195 cells/mm3, respectively. Haematuria (73% was the most frequent presenting symptom and HPV-associated lesions were seen in 6/10 (60% patients. Histopathology showed transitional cell carcinoma in 80% and a high proportion of tumors with muscle invasion (47% and high histologic grade (73%. One-year survival rate was 74.6%. The systematic review identified 13 additional cases of urothelial bladder cancers which shared similar features.Bladder cancers in HIV-infected patients remain rare but may occur in relatively young patients with a low nadir CD4 cell count, have aggressive pathological features and can be fatal.

  10. The classification of lung cancers and their degree of malignancy by FTIR, PCA-LDA analysis, and a physics-based computational model.

    Science.gov (United States)

    Kaznowska, E; Depciuch, J; Łach, K; Kołodziej, M; Koziorowska, A; Vongsvivut, J; Zawlik, I; Cholewa, M; Cebulski, J

    2018-08-15

    Lung cancer has the highest mortality rate of all malignant tumours. The current effects of cancer treatment, as well as its diagnostics, are unsatisfactory. Therefore it is very important to introduce modern diagnostic tools, which will allow for rapid classification of lung cancers and their degree of malignancy. For this purpose, the authors propose the use of Fourier Transform InfraRed (FTIR) spectroscopy combined with Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) and a physics-based computational model. The results obtained for lung cancer tissues, adenocarcinoma and squamous cell carcinoma FTIR spectra, show a shift in wavenumbers compared to control tissue FTIR spectra. Furthermore, in the FTIR spectra of adenocarcinoma there are no peaks corresponding to glutamate or phospholipid functional groups. Moreover, in the case of G2 and G3 malignancy of adenocarcinoma lung cancer, the absence of an OH groups peak was noticed. Thus, it seems that FTIR spectroscopy is a valuable tool to classify lung cancer and to determine the degree of its malignancy. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. 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.

  12. Objective burden, resources, and other stressors among informal cancer caregivers: a hidden quality issue?†

    Science.gov (United States)

    van Ryn, Michelle; Sanders, Sara; Kahn, Katherine; van Houtven, Courtney; Griffin, Joan M.; Martin, Michelle; Atienza, Audie A.; Phelan, Sean; Finstad, Deborah; Rowland, Julia

    2015-01-01

    A great deal of clinical cancer care is delivered in the home by informal caregivers (e.g. family, friends), who are often untrained. Caregivers' context varies widely, with many providing care despite low levels of resources and high levels of additional demands. Background Changes in health care have shifted much cancer care to the home, with limited data to inform this transition. We studied the characteristics, care tasks, and needs of informal caregivers of cancer patients. Methods Caregivers of seven geographically and institutionally defined cohorts of newly diagnosed colorectal and lung cancer patients completed self-administered questionnaires (n = 677). We combined this information with patient survey and chart abstraction data and focused on caregivers who reported providing, unpaid, at least 50% of the patient's informal cancer care. Results Over half of caregivers (55%) cared for a patient with metastatic disease, severe comorbidity, or undergoing current treatment. Besides assisting with activities of daily living, caregivers provided cancer-specific care such as watching for treatment side effects (68%), helping manage pain, nausea or fatigue (47%), administering medicine (34%), deciding whether to call a doctor (30%), deciding whether medicine was needed (29%), and changing bandages (19%). However, half of caregivers reported not getting training perceived as necessary. In addition, 49% of caregivers worked for pay, 21% reported poor or fair health, and 21% provided unpaid care for other individuals. One in four reported low confidence in the quality of the care they provided. Conclusions Much assistance for cancer patients is delivered in the home by informal caregivers, often without desired training, with a significant minority having limited resources and high additional demands. Future research should explore the potentially high yield of addressing caregiver needs in improving quality of cancer care and both survivors' and caregivers' outcomes

  13. 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.

  14. [Issues involving breast cancer management in Senegal: a cross-sectional study].

    Science.gov (United States)

    Gueye, Serigne Modou Kane; Gueye, Mamour; Coulbary, Sophie Aminata; Diouf, Alassane; Moreau, Jean Charles

    2016-01-01

    At a time when innovative therapies in breast cancer multiply, poorer countries such as Senegal are still lag far behind in the overall management of this type of cancer. In Senegal, although the treatment of advanced breast cancer is now well codified, survival and morbidity outcomes are still mediocre in view of diagnostic delays and of sometimes expensive and poorly tolerated mutilating treatments become necessary. With respect to advanced cancers, the challenges will lie in building of palliative care centres and in developing multidisciplinary approaches to improve quality of life and to support patients. On the other hand, with respect to preclinical or potentially curable cancers, the challenges are immense given the importance of early detection, localisation and diagnosis (stereotactic or ultrasound guided biopsy) but also of precision surgery and of complete resection (indexing - excision ensuring a margin of healthy tissue and specimen radiograph) while minimizing complications such as those of classic dissection (sentinel lymph node biopsy). Our health structures are not always prepared to achieve these goals. This is a situational analysis of the contextual obstacles that still exist and add a burden on the overall management of breast cancer in Senegal.

  15. 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.

  16. Implementing risk-stratified screening for common cancers: a review of potential ethical, legal and social issues.

    Science.gov (United States)

    Hall, A E; Chowdhury, S; Hallowell, N; Pashayan, N; Dent, T; Pharoah, P; Burton, H

    2014-06-01

    The identification of common genetic variants associated with common cancers including breast, prostate and ovarian cancers would allow population stratification by genotype to effectively target screening and treatment. As scientific, clinical and economic evidence mounts there will be increasing pressure for risk-stratified screening programmes to be implemented. This paper reviews some of the main ethical, legal and social issues (ELSI) raised by the introduction of genotyping into risk-stratified screening programmes, in terms of Beauchamp and Childress's four principles of biomedical ethics--respect for autonomy, non-maleficence, beneficence and justice. Two alternative approaches to data collection, storage, communication and consent are used to exemplify the ELSI issues that are likely to be raised. Ultimately, the provision of risk-stratified screening using genotyping raises fundamental questions about respective roles of individuals, healthcare providers and the state in organizing or mandating such programmes, and the principles, which underpin their provision, particularly the requirement for distributive justice. The scope and breadth of these issues suggest that ELSI relating to risk-stratified screening will become increasingly important for policy-makers, healthcare professionals and a wide diversity of stakeholders. © The Author 2013. Published by Oxford University Press on behalf of Faculty of Public Health.

  17. 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.

  18. Revision, uptake and coding issues related to the open access Orchard Sports Injury Classification System (OSICS) versions 8, 9 and 10.1

    OpenAIRE

    Orchard, John; Rae, Katherine; Brooks, John; H?gglund, Martin; Til, Lluis; Wales, David; Wood, Tim

    2010-01-01

    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 Sys...

  19. 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...

  20. 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; Eckhardt, S Gail; 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

    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

  1. 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; Eckhardt, S. Gail; 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

  2. Psychosocial and Quality of Life Issues in Prostate and Ovarian Cancer

    NARCIS (Netherlands)

    J.B. Madalinska

    2007-01-01

    textabstractProstate and ovarian cancers are among the leading causes of death in Western countries. Applied preventive health strategies, including screening and early medical treatments either with prophylactic or curative intention, may substantially affect patients’ quality of life (QOL). This

  3. Health issues in the Arab American community. Commentary on tobacco: the world's leading cause of cancer.

    Science.gov (United States)

    Seffrin, John R

    2007-01-01

    Cancer incidence is on the rise in many regions of the world, including the Middle East, where incidence rates for both men and women are increasing. Like many regions of the world, increased tobacco use, combined with other factors, is driving cancer incidence in the Middle East. Tobacco, the only consumer product proven to kill more than half of its regular users, will be responsible for 4.9 million deaths worldwide this year alone. That burden is fairly evenly shared by industrialized and developing nations today but, if current trends continue, the cancer burden in the developing world will more than triple in the next 25 years, resulting in a global total of 10 million deaths worldwide each year. Seven million of these deaths will occur in the developing world, in nations least prepared to deal with the financial, social, and political consequences of this global public health tragedy. In the Arab world, lung cancer is already occurring with increasing frequency, particularly among men.

  4. Advice about Work-Related Issues to Peers and Employers from Head and Neck Cancer Survivors.

    Science.gov (United States)

    Dewa, Carolyn S; Trojanowski, Lucy; Tamminga, Sietske J; Ringash, Jolie; McQuestion, Maurene; Hoch, Jeffrey S

    2016-01-01

    The purpose of this exploratory and descriptive study is to contribute to the sparse return-to-work literature on head and neck cancer (HNC) survivors. Interview participants were asked to reflect upon their work-related experience with cancer by answering two specific questions: (1) What advice would you give someone who has been newly diagnosed with head and neck cancer? (2) What advice would you give to employers of these people? Data were gathered through 10 individual semi-structured in-depth interviews with HNC clinic patients at a regional cancer center's head and neck clinic in Ontario, Canada. A constant comparative method of theme development was used. Codes identified in and derived from the data were discussed by research team members until consensus was reached. Codes with similar characteristics were grouped together and used to develop overarching themes. Work-related advice for peers focused on personal self-care and interactions within workplaces. Work-related advice to employers focused on demonstrating basic human values as well as the importance of communication. The study results suggest HNC clinic patients should be proactive with employers and help to set reasonable expectations and provide a realistic plan for work to be successfully completed. HNC clinic patients should develop communication skills to effectively disclose their cancer and treatment to employers. In this exploratory study, HNC clinic patients' advice was solution-focused underscoring the importance of self-care and pro-active communication and planning with employers. Employers were advised to demonstrate core human values throughout all phases of the work disability episode beginning at diagnosis.

  5. 32 CFR 2400.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... REGULATIONS TO IMPLEMENT E.O. 12356; OFFICE OF SCIENCE AND TECHNOLOGY POLICY INFORMATION SECURITY PROGRAM 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...

  6. Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification

    Science.gov (United States)

    2018-01-01

    One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes. PMID:29470520

  7. Comparison of the 6th and 7th editions of the UICC-AJCC TNM classification for esophageal cancer

    NARCIS (Netherlands)

    K. Talsma (Koen); P. van Hagen (Pieter); B.A. Grotenhuis (Brechtje); E.W. Steyerberg (Ewout); H.W. Tilanus (Hugo); J.J.B. van Lanschot (Jan); B.P.L. Wijnhoven (Bas)

    2012-01-01

    textabstractBackground. The new 7th edition of the Union for International Cancer Control-American Joint Committee on Cancer (UICC-AJCC) tumor, node, metastasis (TNM) staging system is the ratification of data-driven recommendations from the Worldwide Esophageal Cancer Collaboration database.

  8. The eighth TNM classification system for lung cancer: A consideration based on the degree of pleural invasion and involved neighboring structures.

    Science.gov (United States)

    Sakakura, Noriaki; Mizuno, Tetsuya; Kuroda, Hiroaki; Arimura, Takaaki; Yatabe, Yasushi; Yoshimura, Kenichi; Sakao, Yukinori

    2018-04-01

    The eighth tumor-node-metastasis (TNM) classification system for lung cancer has been used since January 2017 and must be applied to an individual institution's database. We analyzed pathological stage data of 2756 patients who underwent resection of non-small-cell lung cancer, particularly in terms of the degree of visceral pleural invasion and involved neighboring structures. Few patients had stage IIA disease (103, 4%); stratification between stages IB and IIA was insufficient (p = 0.129). When T2a tumors were divided into PL1 and PL2 subgroups based on the degree of pleural invasion, there was a significant prognostic difference between the subgroups (p consideration. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. [Assessment of functioning in patients with head and neck cancer based on the international classification of functioning, disability and health (ICF)].

    Science.gov (United States)

    Tschiesner, U

    2011-09-01

    The article approaches with the question how preservation of function after treatment of head and neck cancer (HNC) can be defined and measured across treatment approaches. On the basis of the "International Classification of Functioning, Disability and Health (ICF)" a series of efforts are summarized how all relevant aspects of the interdisciplinary team can be integrated into a common concept.Different efforts on the development, validation and implementation of ICF Core Sets for head and neck cancer (ICF-HNC) are discussed. The ICF-HNC covers organ-based problems with food ingestion, breathing, and speech, as well as psychosocial difficulties.Relationships between the ICF-HNC and well-established outcome measures are illustrated. This enables the user to integrate different aspects of functional outcome into a consolidated approach towards preservation/rehabilitation of functioning after HNC - applicable for a variety of treatment-approaches and health-professions. George Thieme Verlag KG Stuttgart · New York.

  10. Evaluation of a 5-year cervical cancer prevention project in Indonesia: opportunities, issues, and challenges.

    Science.gov (United States)

    Kim, Young-Mi; Lambe, Fransisca Maria; Soetikno, Djoko; Wysong, Megan; Tergas, Ana Isabel; Rajbhandari, Presha; Ati, Abigael; Lu, Enriquito

    2013-06-01

    The Cervical and Breast Cancer Prevention (CECAP) Project sought to develop a national model for cervical cancer prevention in Indonesia based on visual inspection with acetic acid (VIA) to detect abnormal changes in the cervix. The purpose of this study was to evaluate a pilot project introducing VIA and cryotherapy in Indonesia and to identify lessons learned that could be applied to the national scale-up of cervical cancer prevention services. Fifty-four months (July 2007 to December 2011) of service records at 17 health centers were abstracted and analyzed. The data were used to calculate the proportion of all women aged 30-50 who received VIA screening, the VIA-positive rate, the treatment rate, and the interval between screening and treatment. The 45 050 women screened during the project included 24.4% of the total female population in the target age group in the catchment area. Throughout the 5-year project, 83.1% of VIA-positive women sought cryotherapy. During the last 18 months of the project, after data collection tools were revised to more accurately reflect when cryotherapy was received, 13% of women were treated on the same day that they were screened. Among the 74% of women treated within 1 month of screening, the mean interval between screening and treatment was 7.2 days. As cervical cancer prevention services are scaled up throughout Indonesia, changes in the service delivery model and program management are needed to increase screening coverage, promote a single-visit approach, and ensure the quality of services. © 2013 The Authors. Journal of Obstetrics and Gynaecology Research © 2013 Japan Society of Obstetrics and Gynecology.

  11. Lifestyle issues for colorectal cancer survivors--perceived needs, beliefs and opportunities.

    Science.gov (United States)

    Anderson, Annie S; Steele, Robert; Coyle, Joanne

    2013-01-01

    As survival rates for patients treated with colorectal cancer (CRC) increase, it is important to consider the short- and long-term self-management needs. The current work aimed to explore perceived patient needs for advice on diet, activity and beliefs about the role of lifestyle for reducing disease recurrence. Forty colorectal cancer survivors, aged between 27 and 84, participated in six focus groups in community locations in the UK. The findings suggest that CRC survivors would welcome guidance on diet in the immediate posttreatment period to alleviate symptoms and fears about food choices. Many participants actively sought lifestyle advice but experienced confusion, mixed messages, culturally inappropriate guidance and uncertainty about evidence of benefit. There was scepticism over the role of diet and physical activity as causes of cancer, in part because people believed their lifestyles had been healthy and could not see how reinstating healthy behaviours would reduce future disease risk. The sense of changing lifestyle to 'stack the odds in their favour' (against recurrence) appeared a more meaningful concept than prevention per se. Those people who had made or maintained dietary changes highlighted the importance of these to contributing to wellbeing and a sense of control in their life. A dogmatic approach to lifestyle change may lead to perceptions of victim blaming and stigmatisation. Personalised, evidence informed, guidance on lifestyle choices does appear to be a much needed part of care planning and should be built in to survivorship programmes.

  12. 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

  13. Design issues in epidemiologic studies of indoor exposure to Rn and risk of lung cancer

    International Nuclear Information System (INIS)

    Lubin, J.H.; Samet, J.M.; Weinberg, C.

    1990-01-01

    Recent data on indoor air quality have indicated that Rn (222Rn) and its decay products are frequently present in domestic environments. Their presence in indoor air raises concerns about an increase in lung cancer risk for the general population. To directly evaluate lung cancer risk from domestic exposure to Rn and its decay products, as well as to evaluate risk assessments derived from studies of Rn-exposed underground miners, several epidemiologic studies of indoor Rn exposure have been initiated or are planned. This paper calculates sample sizes required for a hypothetical case-control study to address several important hypotheses and shows the impact of difficult problems associated with estimating a subject's Rn exposure. We consider the effects of subject mobility, choice of the exposure response trend which is used to characterize an alternative hypothesis, and errors in the estimation of exposure. Imprecise estimation of Rn exposure arises from errors in the measurement device, exposure to Rn decay products from sources outside the home, inability to measure exposures over time in current as well as previous residences, and the unknown relationship between measured concentration and lung dose of alpha energy from the decay of Rn and its progeny. These methodological problems can result in large discrepancies between computed and actual study power. Failure to anticipate these problems in the design of a study can result in inaccurate estimates of power. We conclude that case-control studies of indoor Rn and lung cancer may require substantial numbers of subjects in order to address the many questions of importance that burden current risk assessments with uncertainty. We suggest pooling data from studies with the largest numbers of cases and with the most precise estimates of Rn exposure as the best approach for meeting present research needs

  14. 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 %.

  15. 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.

  16. 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

  17. A multicenter validation of an endoscopic classification with narrow band imaging for gastric precancerous and cancerous lesions

    NARCIS (Netherlands)

    Pimentel-Nunes, P.; Dinis-Ribeiro, M.; Soares, J. B.; Marcos-Pinto, R.; Santos, C.; Rolanda, C.; Bastos, R. P.; Areia, M.; Afonso, L.; Bergman, J.; Sharma, P.; Gotoda, T.; Henrique, R.; Moreira-Dias, L.

    2012-01-01

    Background and study aim: The reliability and external validity of narrow band imaging (NBI) in the stomach have not been described consistently. The aim of the current study was to describe and estimate the accuracy and reliability of a simplified classification system for NBI in the diagnosis of

  18. Tumor Size Evaluation according to the T Component of the Seventh Edition of the International Association for the Study of Lung Cancer's TNM Classification: Interobserver Agreement between Radiologists and Computer-Aided Diagnosis System in Patients with Lung Cancer

    International Nuclear Information System (INIS)

    Kim, Jin Kyoung; Chong, Se Min; Seo, Jae Seung; Lee, Sun Jin; Han, Heon

    2011-01-01

    To assess the interobserver agreement for tumor size evaluation between radiologists and the computer-aided diagnosis (CAD) system based on the 7th edition of the TNM classification by the International Association for the Study of Lung Cancer in patients with lung cancer. We evaluated 20 patients who underwent a lobectomy or pneumonectomy for primary lung cancer. The maximum diameter of each primary tumor was measured by two radiologists and a CAD system on CT, and was staged based on the 7th edition of the TNM classification. The CT size and T-staging of the primary tumors was compared with the pathologic size and staging and the variability in the sizes and T stages of primary tumors was statistically analyzed between each radiologist's measurement or CAD estimation and the pathologic results. There was no statistically significant interobserver difference for the CT size among the two radiologists, between pathologic and CT size estimated by the radiologists, and between pathologic and CT staging by the radiologists and CAD system. However, there was a statistically significant interobserver difference between pathologic size and the CT size estimated by the CAD system (p = 0.003). No significant differences were found in the measurement of tumor size among radiologists or in the assessment of T-staging by radiologists and the CAD system.

  19. Sentinel lymph node mapping in breast cancer: a critical reappraisal of the internal mammary chain issue.

    Science.gov (United States)

    Manca, G; Volterrani, D; Mazzarri, S; Duce, V; Svirydenka, A; Giuliano, A; Mariani, G

    2014-06-01

    Although, like the axilla, the internal mammary nodes (IMNs) are a first-echelon nodal drainage site in breast cancer, the importance of their treatment has long been debated. Seminal randomized trials have failed to demonstrate a survival benefit from surgical IMN dissection, and several retrospective studies have shown that IMNs are rarely the first site of recurrence. However, the recent widespread adoption of sentinel lymph node (SLN) biopsy has stimulated a critical reappraisal of such early results. Furthermore, the higher proportion of screening-detected cancers, improved imaging and techniques (i.e., lymphoscintigraphy for radioguided SLN biopsy) make it possible to visualize lymphatic drainage to the IMNs. The virtually systematic application of adjuvant systemic and/or loco-regional radiotherapy encourages re-examination of the significance of IMN metastases. Moreover, randomized trials testing the value of postmastectomy irradiation and a meta-analysis of 78 randomized trials have provided high levels of evidence that local-regional tumor control is associated with long-term survival improvements. This benefit was limited to trials that used systemic chemotherapy, which was not routinely administered in the earlier studies. However, the contribution from IMN treatment is unclear. Lymphoscintigraphic studies have shown that a significant proportion of breast cancers have primary drainage to the IMNs, including approximately 30% of medial tumors and 15% of lateral tumors. In the few studies where IMN biopsy was performed, 20% of sentinel IMNs were metastatic. The risk of IMN involvement is higher in patients with medial tumors and positive axillary nodes. IMN metastasis has prognostic significance, as recognized by its inclusion in the American Joint Committee on Cancer staging criteria, and seems to have similar prognostic importance as axillary nodal involvement. Although routine IMN evaluation might be indicated, it has not been routinely performed

  20. Locus-Specific Databases and Recommendations to Strengthen Their Contribution to the Classification of Variants in Cancer Susceptibility Genes

    NARCIS (Netherlands)

    Greenblatt, Marc S.; Brody, Lawrence C.; Foulkes, William D.; Genuardi, Maurizio; Hofstra, Robert M. W.; Olivier, Magali; Plon, Sharon E.; Sijmons, Rolf H.; Sinilnikova, Olga; Spurdle, Amanda B.

    2008-01-01

    Locus-specific databases (LSDBs) are curated collections of sequence variants in genes associated with disease. LSDBs of cancer-related genes often serve as a critical resource to researchers, diagnostic laboratories, clinicians, and others in the cancer genetics community. LSDBs are poised to play

  1. Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer

    NARCIS (Netherlands)

    Hoadley, Katherine A.; Yau, Christina; Hinoue, Toshinori; Wolf, Denise M.; Lazar, Alexander J.; Drill, Esther; Shen, Ronglai; Taylor, Alison M.; Cherniack, Andrew D.; Thorsson, Vésteinn; Akbani, Rehan; Bowlby, Reanne; Wong, Christopher K.; Wiznerowicz, Maciej; Sanchez-Vega, Francisco; Robertson, A. Gordon; Schneider, Barbara G.; Lawrence, Michael S.; Noushmehr, Houtan; Malta, Tathiane M.; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher C.; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Gonzalez, Ana Maria Angulo; Behrens, Carmen; Bondaruk, olanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Pinero, Edna M.Mora; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz; Stuart, Joshua M.; Benz, Christopher C.; Laird, Peter W.

    2018-01-01

    We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA

  2. 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.

  3. Revision, uptake and coding issues related to the open access Orchard Sports Injury Classification System (OSICS) versions 8, 9 and 10.1

    Science.gov (United States)

    Orchard, John; Rae, Katherine; Brooks, John; Hägglund, Martin; Til, Lluis; Wales, David; Wood, Tim

    2010-01-01

    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. PMID:24198559

  4. 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.

  5. Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

    Science.gov (United States)

    Adi Putra, Januar

    2018-04-01

    In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.

  6. 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.

  7. Evaluating sequelae after head and neck cancer from the patient perspective with the help of the International Classification of Functioning, Disability and Health.

    Science.gov (United States)

    Tschiesner, Uta; Linseisen, Elisabeth; Coenen, Michaela; Rogers, Simon; Harreus, Ulrich; Berghaus, Alexander; Cieza, Alarcos

    2009-03-01

    Functioning is recognized increasingly as an important study outcome with head and neck cancer (HNC). The International Classification of Functioning, Disability and Health, as adopted by the World Health Organization in 2001, is based on a comprehensive bio-psycho-social view. The objective of this study was to evaluate functioning from the patient perspective and to classify the results using the comprehensive view of the ICF. Patients with HNC were interviewed on their problems in daily life using qualitative methodology. Sampling of patients followed the maximum variation strategy. Sample size was determined by saturation. All individual interviews were digitally recorded and transcribed verbatim. Interview texts were divided into meaning units and the concepts contained in the meaning units were linked to the ICF according to established linking rules. The transcribed data were analyzed and linked by a second health professional and the degree of consensus was calculated using kappa statistics. Concordance of identified ICF categories among different tumor locations was also measured with kappa statistics. Until saturation was reached, 18 patients were interviewed: seven patients with oral cancer, five with hypopharyngeal cancer and six with laryngeal cancer. Thousand four hundred and sixty-two (1,462) different concepts were translated into the ICF using 104 different, second-level ICF categories. These ICF categories are presented in detail. From the patient perspective, the ICF components (a) Body functions, (b) Activities and participation and (c) contextual Environmental factors are equally represented, while (d) Body structures show by far the least number of categories. The concordance between different tumor locations rages between 0.53 and 0.58 (confidence interval 0.42-0.70). The degree of consensus in the linking process was 0.58 (confidence interval 0.45-0.73). The ICF classification can display problems with functioning following HNC sufficiently

  8. Rural-Urban Differences in Late-Stage Breast Cancer: Do Associations Differ by Rural-Urban Classification System?

    Science.gov (United States)

    Pruitt, Sandi L; Eberth, Jan M; Morris, E Scott; Grinsfelder, David B; Cuate, Erica L

    2016-01-01

    Introduction Rural residence is associated with later stage of breast cancer diagnosis in some but not all prior studies. The lack of a standardized definition of rural residence may contribute to these mixed findings. We characterize and compare multiple definitions of rural vs. non-rural residence to provide guidance regarding choice of measures and to further elucidate rural disparities in breast cancer stage at diagnosis. Methods We used Texas Cancer Registry data of 120,738 female breast cancer patients ≥50 years old diagnosed between 1995–2009. We defined rural vs. non-rural residence using 7 different measures and examined their agreement using Kappa statistics. Measures were defined at various geographic levels: county, ZIP code, census tract, and census block group. Late-stage was defined as regional or distant disease. For each measure, we tested the association of rural residence and late-stage cancer with unadjusted and adjusted logistic regression. Covariates included: age; patient race/ethnicity; diagnosis year; census block group-level mammography capacity; and census tract-level percent poverty, percent Hispanic, and percent Black. Results We found moderate to high levels of agreement between measures of rural vs. non-rural residence. For 72.9% of all patients, all 7 definitions agreed as to rural vs. non-rural residence. Overall, 6 of 7 definitions demonstrated an adverse association between rural residence and late-stage disease in unadjusted and adjusted models (Adjusted OR Range = 1.09–1.14). Discussion Our results document a clear rural disadvantage in late-stage breast cancer. We contribute to the heterogeneous literature by comparing varied measures of rural residence. We recommend use of the census tract-level Rural Urban Commuting Area Codes in future cancer outcomes research where small area data are available. PMID:27158685

  9. Reporting combined outcomes with Trifecta and survival, continence, and potency (SCP) classification in 337 patients with prostate cancer treated with image-guided hypofractionated radiotherapy.

    Science.gov (United States)

    Jereczek-Fossa, Barbara A; Zerini, Dario; Fodor, Cristiana; Santoro, Luigi; Maucieri, Andrea; Gerardi, Marianna A; Vischioni, Barbara; Cambria, Raffaella; Garibaldi, Cristina; Cattani, Federica; Vavassori, Andrea; Matei, Deliu V; Musi, Gennaro; De Cobelli, Ottavio; Orecchia, Roberto

    2014-12-01

    To report the image-guided hypofractionated radiotherapy (hypo-IGRT) outcome for patients with localised prostate cancer according to the new outcome models Trifecta (cancer control, urinary continence, and sexual potency) and SCP (failure-free survival, continence and potency). Between August 2006 and January 2011, 337 patients with cT1-T2N0M0 prostate cancer (median age 73 years) were eligible for a prospective longitudinal study on hypo-IGRT (70.2 Gy/26 fractions) in our Department. Patients completed four questionnaires before treatment, and during follow-up: the International Index of Erectile Function-5 (IIEF-5), the International Prostate Symptom Score (IPSS), and the European Organization for Research and Treatment of Cancer prostate-cancer-specific Quality of Life Questionnaires (QLQ) QLQ-PR25 and QLQ-C30. Baseline and follow-up patient data were analysed according to the Trifecta and SCP outcome models. Cancer control, continence and potency were defined respectively as no evidence of disease, score 1 or 2 for item 36 of the QLQ-PR25 questionnaire, and total score of >16 on the IIEF-5 questionnaire. Patients receiving androgen-deprivation therapy (ADT) at any time were excluded. Trifecta criteria at baseline were met in 72 patients (42% of all ADT-free patients with completed questionnaires). Both at 12 and 24 months after hypo-IGRT, 57% of the Trifecta patients at baseline were still meeting the Trifecta criteria (both oncological and functional success according to the SCP model). The main reason for failing the Trifecta criteria during follow-up was erectile dysfunction: in 18 patients after 6 months follow-up, in 12 patients after 12 months follow-up, and in eight patients after 24 months. Actuarial 2-year Trifecta failure-free survival rate was 44% (95% confidence interval 27-60%). In multivariate analysis no predictors of Trifecta failure were identified. Missing questionnaires was the main limitation of the study. The Trifecta and SCP

  10. Tolerance to missing data using a likelihood ratio based classifier for computer-aided classification of breast cancer

    International Nuclear Information System (INIS)

    Bilska-Wolak, Anna O; Floyd, Carey E Jr

    2004-01-01

    While mammography is a highly sensitive method for detecting breast tumours, its ability to differentiate between malignant and benign lesions is low, which may result in as many as 70% of unnecessary biopsies. The purpose of this study was to develop a highly specific computer-aided diagnosis algorithm to improve classification of mammographic masses. A classifier based on the likelihood ratio was developed to accommodate cases with missing data. Data for development included 671 biopsy cases (245 malignant), with biopsy-proved outcome. Sixteen features based on the BI-RADS TM lexicon and patient history had been recorded for the cases, with 1.3 ± 1.1 missing feature values per case. Classifier evaluation methods included receiver operating characteristic and leave-one-out bootstrap sampling. The classifier achieved 32% specificity at 100% sensitivity on the 671 cases with 16 features that had missing values. Utilizing just the seven features present for all cases resulted in decreased performance at 100% sensitivity with average 19% specificity. No cases and no feature data were omitted during classifier development, showing that it is more beneficial to utilize cases with missing values than to discard incomplete cases that cannot be handled by many algorithms. Classification of mammographic masses was commendable at high sensitivity levels, indicating that benign cases could be potentially spared from biopsy

  11. Diagnosis of breast cancer using diffuse optical spectroscopy from 500 to 1600 nm: comparison of classification methods

    Science.gov (United States)

    Nachabé, Rami; Evers, Daniel J.; Hendriks, Benno H. W.; Lucassen, Gerald W.; van der Voort, Marjolein; Rutgers, Emiel J.; Peeters, Marie-Jeanne Vrancken; van der Hage, Jos A.; Oldenburg, Hester S.; Wesseling, Jelle; Ruers, Theo J. M.

    2011-08-01

    We report on the use of diffuse optical spectroscopy analysis of breast spectra acquired in the wavelength range from 500 to 1600 nm with a fiber optic probe. A total of 102 ex vivo samples of five different breast tissue types, namely adipose, glandular, fibroadenoma, invasive carcinoma, and ductal carcinoma in situ from 52 patients were measured. A model deriving from the diffusion theory was applied to the measured spectra in order to extract clinically relevant parameters such as blood, water, lipid, and collagen volume fractions, β-carotene concentration, average vessels radius, reduced scattering amplitude, Mie slope, and Mie-to-total scattering fraction. Based on a classification and regression tree algorithm applied to the derived parameters, a sensitivity-specificity of 98%-99%, 84%-95%, 81%-98%, 91%-95%, and 83%-99% were obtained for discrimination of adipose, glandular, fibroadenoma, invasive carcinoma, and ductal carcinoma in situ, respectively; and a multiple classes overall diagnostic performance of 94%. Sensitivity-specificity values obtained for discriminating malignant from nonmalignant tissue were compared to existing reported studies by applying the different classification methods that were used in each of these studies. Furthermore, in these reported studies, either lipid or β-carotene was considered as adipose tissue precursors. We estimate both chromophore concentrations and demonstrate that lipid is a better discriminator for adipose tissue than β-carotene.

  12. The classification of secondary colorectal liver cancer in human biopsy samples using angular dispersive x-ray diffraction and multivariate analysis

    International Nuclear Information System (INIS)

    Theodorakou, Chrysoula; Farquharson, Michael J

    2009-01-01

    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.

  13. A multifactorial likelihood model for MMR gene variant classification incorporating probabilities based on sequence bioinformatics and tumor characteristics: a report from the Colon Cancer Family Registry.

    Science.gov (United States)

    Thompson, Bryony A; Goldgar, David E; Paterson, Carol; Clendenning, Mark; Walters, Rhiannon; Arnold, Sven; Parsons, Michael T; Michael D, Walsh; Gallinger, Steven; Haile, Robert W; Hopper, John L; Jenkins, Mark A; Lemarchand, Loic; Lindor, Noralane M; Newcomb, Polly A; Thibodeau, Stephen N; Young, Joanne P; Buchanan, Daniel D; Tavtigian, Sean V; Spurdle, Amanda B

    2013-01-01

    Mismatch repair (MMR) gene sequence variants of uncertain clinical significance are often identified in suspected Lynch syndrome families, and this constitutes a challenge for both researchers and clinicians. Multifactorial likelihood model approaches provide a quantitative measure of MMR variant pathogenicity, but first require input of likelihood ratios (LRs) for different MMR variation-associated characteristics from appropriate, well-characterized reference datasets. Microsatellite instability (MSI) and somatic BRAF tumor data for unselected colorectal cancer probands of known pathogenic variant status were used to derive LRs for tumor characteristics using the Colon Cancer Family Registry (CFR) resource. These tumor LRs were combined with variant segregation within families, and estimates of prior probability of pathogenicity based on sequence conservation and position, to analyze 44 unclassified variants identified initially in Australasian Colon CFR families. In addition, in vitro splicing analyses were conducted on the subset of variants based on bioinformatic splicing predictions. The LR in favor of pathogenicity was estimated to be ~12-fold for a colorectal tumor with a BRAF mutation-negative MSI-H phenotype. For 31 of the 44 variants, the posterior probabilities of pathogenicity were such that altered clinical management would be indicated. Our findings provide a working multifactorial likelihood model for classification that carefully considers mode of ascertainment for gene testing. © 2012 Wiley Periodicals, Inc.

  14. Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

    Science.gov (United States)

    Aytaç Korkmaz, Sevcan; Binol, Hamidullah

    2018-03-01

    Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

  15. 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

    International Nuclear Information System (INIS)

    Yoon, Jeong Hee; Lee, Jeong Min; 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

  16. 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.

  17. The Classification of Romanian High-Schools

    Science.gov (United States)

    Ivan, Ion; Milodin, Daniel; Naie, Lucian

    2006-01-01

    The article tries to tackle the issue of high-schools classification from one city, district or from Romania. The classification criteria are presented. The National Database of Education is also presented and the application of criteria is illustrated. An algorithm for high-school multi-rang classification is proposed in order to build classes of…

  18. 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.

  19. Classification of 27 Tumor-Associated Antigens by Histochemical Analysis of 36 Freshly Resected Lung Cancer Tissues

    Directory of Open Access Journals (Sweden)

    Gene Kurosawa

    2016-11-01

    Full Text Available In previous studies, we identified 29 tumor-associated antigens (TAAs and isolated 488 human monoclonal antibodies (mAbs that specifically bind to one of the 29 TAAs. In the present study, we performed histochemical analysis of 36 freshly resected lung cancer tissues by using 60 mAbs against 27 TAAs. Comparison of the staining patterns of tumor cells, bronchial epithelial cells, and normal pulmonary alveolus cells and interalveolar septum allowed us to determine the type and location of cells that express target molecules, as well as the degree of expression. The patterns were classified into 7 categories. While multiple Abs were used against certain TAAs, the differences observed among them should be derived from differences in the binding activity and/or the epitope. Thus, such data indicate the versatility of respective clones as anti-cancer drugs. Although the information obtained was limited to the lung and bronchial tube, bronchial epithelial cells represent normal growing cells, and therefore, the data are informative. The results indicate that 9 of the 27 TAAs are suitable targets for therapeutic Abs. These 9 Ags include EGFR, HER2, TfR, and integrin α6β4. Based on our findings, a pharmaceutical company has started to develop anti-cancer drugs by using Abs to TfR and integrin α6β4. HGFR, PTP-LAR, CD147, CDCP1, and integrin αvβ3 are also appropriate targets for therapeutic purposes.

  20. 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...

  1. Gender, Race, and Survival: A Study in Non-Small-Cell Lung Cancer Brain Metastases Patients Utilizing the Radiation Therapy Oncology Group Recursive Partitioning Analysis Classification

    International Nuclear Information System (INIS)

    Videtic, Gregory M.M.; Reddy, Chandana A.; Chao, Samuel T.; Rice, Thomas W.; Adelstein, David J.; Barnett, Gene H.; Mekhail, Tarek M.; Vogelbaum, Michael A.; Suh, John H.

    2009-01-01

    Purpose: To explore whether gender and race influence survival in non-small-cell lung cancer (NSCLC) in patients with brain metastases, using our large single-institution brain tumor database and the Radiation Therapy Oncology Group recursive partitioning analysis (RPA) brain metastases classification. Methods and materials: A retrospective review of a single-institution brain metastasis database for the interval January 1982 to September 2004 yielded 835 NSCLC patients with brain metastases for analysis. Patient subsets based on combinations of gender, race, and RPA class were then analyzed for survival differences. Results: Median follow-up was 5.4 months (range, 0-122.9 months). There were 485 male patients (M) (58.4%) and 346 female patients (F) (41.6%). Of the 828 evaluable patients (99%), 143 (17%) were black/African American (B) and 685 (83%) were white/Caucasian (W). Median survival time (MST) from time of brain metastasis diagnosis for all patients was 5.8 months. Median survival time by gender (F vs. M) and race (W vs. B) was 6.3 months vs. 5.5 months (p = 0.013) and 6.0 months vs. 5.2 months (p = 0.08), respectively. For patients stratified by RPA class, gender, and race, MST significantly favored BFs over BMs in Class II: 11.2 months vs. 4.6 months (p = 0.021). On multivariable analysis, significant variables were gender (p = 0.041, relative risk [RR] 0.83) and RPA class (p < 0.0001, RR 0.28 for I vs. III; p < 0.0001, RR 0.51 for II vs. III) but not race. Conclusions: Gender significantly influences NSCLC brain metastasis survival. Race trended to significance in overall survival but was not significant on multivariable analysis. Multivariable analysis identified gender and RPA classification as significant variables with respect to survival.

  2. 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.

  3. Detection and classification of focal liver lesions in patients with colorectal cancer: Retrospective comparison of diffusion-weighted MR imaging and multi-slice CT

    International Nuclear Information System (INIS)

    Eiber, Matthias; Fingerle, Alexander A.; Brügel, Melanie; Gaa, Jochen; Rummeny, Ernst J.; Holzapfel, Konstantin

    2012-01-01

    Objectives: To compare the diagnostic performance of diffusion-weighted MR imaging (DWI) with multi-slice CT (MS-CT) in the detection and classification of focal liver lesions in patients with colorectal cancer. Methods: In a retrospective study 68 patients who underwent DWI at 1.5 T (b-values of 50, 300 and 600 s/mm 2 ) and contrast-enhanced MS-CT were analysed by two radiologists blinded to the clinical results. Imaging results were correlated with intraoperative surgical and ultrasound findings (n = 24), imaging follow-up or PET (n = 44). Sensitivity of DWI and MS-CT in detection of focal liver lesions was compared on a per-lesion and a per-segment basis. Receiver operator-characteristic (ROC) curves to determine the diagnostic performance and the sensitivities of correctly identifying liver metastases on a segmental base were calculated. Results: For lesion detection, DWI was significantly superior to MS-CT both on a per-lesion (difference in sensitivities for reader 1 and 2 22.65% and 19.06%, p < 0.0001) and a per-segment basis (16.86% and 11.76%, p < 0.0001). Especially lesions smaller than 10 mm were better detected with DWI compared to MS-CT (difference 41.10% and 29.45%, p < 0.0001). ROC-analysis showed superiority for lesions classification (p < 0.0001) of DWI (AUC: 0.949 and 0.951) as compared to MS-CT (AUC: 0.879 and 0.892, p < 0.0001 and p = 0.005). DWI was able to filter out metastatic segments with a higher sensitivity (88.2 and 86.5%) compared to MS-CT (68.0 and 67.4%, p < 0.0001 and p = 0.005, respectively). Conclusion: Compared to MS-CT DWI is both more sensitive in the detection of liver lesions and more accurate in determining the extent of metastatic disease in patients with colorectal cancer and therefore might help to optimize therapeutic management in those patients.

  4. 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

  5. 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.

  6. 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.

  7. 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....

  8. [Guideline development for rehabilitation of breast cancer patients - phase 2: findings from the classification of therapeutic procedures, KTL-data-analysis].

    Science.gov (United States)

    Domann, U; Brüggemann, S; Klosterhuis, H; Weis, J

    2007-08-01

    Aim of this project is the development of an evidence based guideline for the rehabilitation of breast cancer patients, funded by the German Pension Insurance scheme. The project consists of four phases. This paper is focused on the 2nd phase, i.e., analysis of procedures in rehabilitation based on evidence based therapeutic modules. As a result of a systematic literature review 14 therapeutic modules were defined. From a total of 840 possible KTL Codes (Klassifikation Therapeutischer Leistungen, Classification of therapeutic procedures), 229 could be assigned to these modules. These analyses are based on 24685 patients in 57 rehabilitation clinics, who had been treated in 2003. For these modules the number of patients having received those interventions as well as the duration of the modules were calculated. The data were analysed with respect to the influence of age and comorbidity. Moreover, differences between rehabilitation clinics were investigated according to the category of interventions. Our findings show great variability in the use of the therapeutic modules. Therapeutic modules like Physiotherapy (91.6%), Training Therapy (85.2%) and Information (97.8%) are provided to most of the patients. Younger patients receive more treatments than older patients, and patients with higher comorbidity receive more Physiotherapie, Lymphoedema Therapy and Psychological Interventions than patients without comorbidities. Data analysis shows wide interindividual variability with regard to the therapeutic modules. This variability is related to age and comorbidity of the patients. Furthermore, great differences were found between the rehabilitation clinics concerning the use of the various interventions. This variability supports the necessity of developing and implementing an evidence based guideline for the rehabilitation of breast cancer patients. The next step will be discussing these findings with experts from science and clinical practice.

  9. Unsupervised Analysis of Array Comparative Genomic Hybridization Data from Early-Onset Colorectal Cancer Reveals Equivalence with Molecular Classification and Phenotypes

    Directory of Open Access Journals (Sweden)

    María Arriba

    2017-01-01

    Full Text Available AIM: To investigate whether chromosomal instability (CIN is associated with tumor phenotypes and/or with global genomic status based on MSI (microsatellite instability and CIMP (CpG island methylator phenotype in early-onset colorectal cancer (EOCRC. METHODS: Taking as a starting point our previous work in which tumors from 60 EOCRC cases (≤45 years at the time of diagnosis were analyzed by array comparative genomic hybridization (aCGH, in the present study we performed an unsupervised hierarchical clustering analysis of those aCGH data in order to unveil possible associations between the CIN profile and the clinical features of the tumors. In addition, we evaluated the MSI and the CIMP statuses of the samples with the aim of investigating a possible relationship between copy number alterations (CNAs and the MSI/CIMP condition in EOCRC. RESULTS: Based on the similarity of the CNAs detected, the unsupervised analysis stratified samples into two main clusters (A, B and four secondary clusters (A1, A2, B3, B4. The different subgroups showed a certain correspondence with the molecular classification of colorectal cancer (CRC, which enabled us to outline an algorithm to categorize tumors according to their CIMP status. Interestingly, each subcluster showed some distinctive clinicopathological features. But more interestingly, the CIN of each subcluster mainly affected particular chromosomes, allowing us to define chromosomal regions more specifically affected depending on the CIMP/MSI status of the samples. CONCLUSIONS: Our findings may provide a basis for a new form of classifying EOCRC according to the genomic status of the tumors.

  10. Economic issues involved in integrating genomic testing into clinical care: the case of genomic testing to guide decision-making about chemotherapy for breast cancer patients

    OpenAIRE

    2010-01-01

    Abstract The use of taxanes to treat node-positive (N+) breast cancer patients is associated with heterogeneous benefits as well as with morbidity and financial costs. This study aimed to assess the economic impact of using gene expression profiling to guide decision-making about chemotherapy, and to discuss the coverage/reimbursement issues involved. Retrospective data on 246 patients included in a randomised trial (PACS01) were analyzed. Tumours were genotyped using DNA microarra...

  11. Communication in cancer care: psycho-social, interactional, and cultural issues. A general overview and the example of India.

    Science.gov (United States)

    Chaturvedi, Santosh K; Strohschein, Fay J; Saraf, Gayatri; Loiselle, Carmen G

    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 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.

  12. 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.

  13. 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.

  14. Network-Based Logistic Classification with an Enhanced L1/2 Solver Reveals Biomarker and Subnetwork Signatures for Diagnosing Lung Cancer

    Directory of Open Access Journals (Sweden)

    Hai-Hui Huang

    2015-01-01

    Full Text Available Identifying biomarker and signaling pathway is a critical step in genomic studies, in which the regularization method is a widely used feature extraction approach. However, most of the regularizers are based on L1-norm and their results are not good enough for sparsity and interpretation and are asymptotically biased, especially in genomic research. Recently, we gained a large amount of molecular interaction information about the disease-related biological processes and gathered them through various databases, which focused on many aspects of biological systems. In this paper, we use an enhanced L1/2 penalized solver to penalize network-constrained logistic regression model called an enhanced L1/2 net, where the predictors are based on gene-expression data with biologic network knowledge. Extensive simulation studies showed that our proposed approach outperforms L1 regularization, the old L1/2 penalized solver, and the Elastic net approaches in terms of classification accuracy and stability. Furthermore, we applied our method for lung cancer data analysis and found that our method achieves higher predictive accuracy than L1 regularization, the old L1/2 penalized solver, and the Elastic net approaches, while fewer but informative biomarkers and pathways are selected.

  15. Communication in cancer care: psycho-social, interactional, and cultural issues. A general overview and the example of India

    OpenAIRE

    Chaturvedi, Santosh K.; Strohschein, Fay J.; Saraf, Gayatri; Loiselle, Carmen G.

    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 i...

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. Summary and recommendations of a National Cancer Institute workshop on issues limiting the clinical use of Monte Carlo dose calculation algorithms for megavoltage external beam radiation therapy

    International Nuclear Information System (INIS)

    Fraass, Benedick A.; Smathers, James; Deye, James

    2003-01-01

    Due to the significant interest in Monte Carlo dose calculations for external beam megavoltage radiation therapy from both the research and commercial communities, a workshop was held in October 2001 to assess the status of this computational method with regard to use for clinical treatment planning. The Radiation Research Program of the National Cancer Institute, in conjunction with the Nuclear Data and Analysis Group at the Oak Ridge National Laboratory, gathered a group of experts in clinical radiation therapy treatment planning and Monte Carlo dose calculations, and examined issues involved in clinical implementation of Monte Carlo dose calculation methods in clinical radiotherapy. The workshop examined the current status of Monte Carlo algorithms, the rationale for using Monte Carlo, algorithmic concerns, clinical issues, and verification methodologies. Based on these discussions, the workshop developed recommendations for future NCI-funded research and development efforts. This paper briefly summarizes the issues presented at the workshop and the recommendations developed by the group

  2. Classification of early-stage non-small cell lung cancer by weighing gene expression profiles with connectivity information.

    Science.gov (United States)

    Zhang, Ao; Tian, Suyan

    2018-05-01

    Pathway-based feature selection algorithms, which utilize biological information contained in pathways to guide which features/genes should be selected, have evolved quickly and become widespread in the field of bioinformatics. Based on how the pathway information is incorporated, we classify pathway-based feature selection algorithms into three major categories-penalty, stepwise forward, and weighting. Compared to the first two categories, the weighting methods have been underutilized even though they are usually the simplest ones. In this article, we constructed three different genes' connectivity information-based weights for each gene and then conducted feature selection upon the resulting weighted gene expression profiles. Using both simulations and a real-world application, we have demonstrated that when the data-driven connectivity information constructed from the data of specific disease under study is considered, the resulting weighted gene expression profiles slightly outperform the original expression profiles. In summary, a big challenge faced by the weighting method is how to estimate pathway knowledge-based weights more accurately and precisely. Only until the issue is conquered successfully will wide utilization of the weighting methods be impossible. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. 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)...

  4. Esophagus cancer

    International Nuclear Information System (INIS)

    Anon.

    1989-01-01

    Ways of metastatic spreading of esophagus cancer, depending on segmental division of esophagus are considered. Classification of esophagus cancer according to morphological structure, domestic clinical classification according to stages and international classification according to TNM system are presented. Diagnosis of esophagus cancer should be complex and based on results of clinical examination of patients, radiological, endoscopic and morphological investigations. Radiological, surgical and combined (preoperative radiotherapy with successive operation) methods of treatment are used in the case of esophagus cancer. Versions of preoperative radiotherapy are given. Favourable results of applying combined surgical treatment with preoperative radiotherapy are shown

  5. 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.

  6. Issues in Developing a Surveillance Case Definition for Nonfatal Suicide Attempt and Intentional Self-harm Using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) Coded Data.

    Science.gov (United States)

    Hedegaard, Holly; Schoenbaum, Michael; Claassen, Cynthia; Crosby, Alex; Holland, Kristin; Proescholdbell, Scott

    2018-02-01

    Suicide and intentional self-harm are among the leading causes of death in the United States. To study this public health issue, epidemiologists and researchers often analyze data coded using the International Classification of Diseases (ICD). Prior to October 1, 2015, health care organizations and providers used the clinical modification of the Ninth Revision of ICD (ICD-9-CM) to report medical information in electronic claims data. The transition in October 2015 to use of the clinical modification of the Tenth Revision of ICD (ICD-10-CM) resulted in the need to update methods and selection criteria previously developed for ICD-9-CM coded data. This report provides guidance on the use of ICD-10-CM codes to identify cases of nonfatal suicide attempts and intentional self-harm in ICD-10-CM coded data sets. ICD-10-CM codes for nonfatal suicide attempts and intentional self-harm include: X71-X83, intentional self-harm due to drowning and submersion, firearms, explosive or thermal material, sharp or blunt objects, jumping from a high place, jumping or lying in front of a moving object, crashing of motor vehicle, and other specified means; T36-T50 with a 6th character of 2 (except for T36.9, T37.9, T39.9, T41.4, T42.7, T43.9, T45.9, T47.9, and T49.9, which are included if the 5th character is 2), intentional self-harm due to drug poisoning (overdose); T51-T65 with a 6th character of 2 (except for T51.9, T52.9, T53.9, T54.9, T56.9, T57.9, T58.0, T58.1, T58.9, T59.9, T60.9, T61.0, T61.1, T61.9, T62.9, T63.9, T64.0, T64.8, and T65.9, which are included if the 5th character is 2), intentional self-harm due to toxic effects of nonmedicinal substances; T71 with a 6th character of 2, intentional self-harm due to asphyxiation, suffocation, strangulation; and T14.91, Suicide attempt. Issues to consider when selecting records for nonfatal suicide attempts and intentional self-harm from ICD-10-CM coded administrative data sets are also discussed. All material appearing in this

  7. 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

  8. 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.

  9. Grading Dysphagia as a Toxicity of Head and Neck Cancer: Differences in Severity Classification Based on MBS DIGEST and Clinical CTCAE Grades.

    Science.gov (United States)

    Goepfert, Ryan P; Lewin, Jan S; Barrow, Martha P; Warneke, Carla L; Fuller, Clifton D; Lai, Stephen Y; Weber, Randal S; Hutcheson, Katherine A

    2018-04-01

    Clinician-reported toxicity grading through common terminology criteria for adverse events (CTCAE) stages dysphagia based on symptoms, diet, and tube dependence. The new dynamic imaging grade of swallowing toxicity (DIGEST) tool offers a similarly scaled five-point ordinal summary grade of pharyngeal swallowing as determined through results of a modified barium swallow (MBS) study. This study aims to inform clinicians on the similarities and differences between dysphagia severity according to clinical CTCAE and MBS-derived DIGEST grading. A cross-sectional sample of 95 MBS studies was randomly selected from a prospectively-acquired MBS database among patients treated with organ preservation strategies for head and neck cancer. MBS DIGEST and clinical CTCAE dysphagia grades were compared. DIGEST and CTCAE dysphagia grades had "fair" agreement per weighted κ of 0.358 (95% CI .231-.485). Using a threshold of DIGEST ≥ 3 as reference, CTCAE had an overall sensitivity of 0.50, specificity of 0.84, and area under the curve (AUC) of 0.67 to identify severe MBS-detected dysphagia. At less than 6 months, sensitivity was 0.72, specificity was 0.76, and AUC was 0.75 while at greater than 6 months, sensitivity was 0.22, specificity was 0.90, and AUC was 0.56 for CTCAE to detect dysphagia as determined by DIGEST. Classification of pharyngeal dysphagia on MBS using DIGEST augments our understanding of dysphagia severity according to the clinically-derived CTCAE while maintaining the simplicity of an ordinal scale. DIGEST likely complements CTCAE toxicity grading through improved specificity for physiologic dysphagia in the acute phase and improved sensitivity for dysphagia in the late-phase.

  10. 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.

  11. Modern classification of neoplasms: reconciling differences between morphologic and molecular approaches

    International Nuclear Information System (INIS)

    Berman, Jules

    2005-01-01

    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. 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 value of a robust tumor classification. A

  12. 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/.

  13. 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.

  14. [Landscape classification: research progress and development trend].

    Science.gov (United States)

    Liang, Fa-Chao; Liu, Li-Ming

    2011-06-01

    Landscape classification is the basis of the researches on landscape structure, process, and function, and also, the prerequisite for landscape evaluation, planning, protection, and management, directly affecting the precision and practicability of landscape research. This paper reviewed the research progress on the landscape classification system, theory, and methodology, and summarized the key problems and deficiencies of current researches. Some major landscape classification systems, e. g. , LANMAP and MUFIC, were introduced and discussed. It was suggested that a qualitative and quantitative comprehensive classification based on the ideology of functional structure shape and on the integral consideration of landscape classification utility, landscape function, landscape structure, physiogeographical factors, and human disturbance intensity should be the major research directions in the future. The integration of mapping, 3S technology, quantitative mathematics modeling, computer artificial intelligence, and professional knowledge to enhance the precision of landscape classification would be the key issues and the development trend in the researches of landscape classification.

  15. 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

  16. Nutritional issues and self-care measures adopted by cancer patients attending a university hospital in Turkey

    Directory of Open Access Journals (Sweden)

    Sevgisun Kapucu

    2016-01-01

    Full Text Available Objective: This study aimed to assess the nutritional status of cancer patients and the self-care measures they adopted as a response to nutritional problems. Methods: This descriptive study included seventy cancer patients staying in the oncology and internal disease clinics of a university hospital in Turkey. Data were collected using a questionnaire with 29 questions. Results: The mean age of participants was 40.2 ΁ 1.82 years. Approximately, 62.9% of the patients ate only half of the meals offered to them, 65.7% experienced weight loss, and 45.7% had difficulty eating their meals on their own. Moreover, 47.1% of the patients received nutritional support and nutritional problems were observed in 71.4% of the patients; 80% were unable to eat hospital food, 54.3% had an eating disorder related to a special diet, 30% suffered from loss of appetite, 27% had nausea, and 14.3% had difficulty swallowing. Furthermore, 48.5% of patients responded that they ate home-cooked food or ordered food from outside when questioned about the self-care measures taken to avoid the aforementioned nutritional problems. Conclusions: Most of the cancer patients had serious nutritional problems and ate home-cooked food and used nutritional supplements to overcome these problems. Oncology nurses are responsible for evaluating the nutritional status of cancer patients and eliminating nutritional problems.

  17. Is classification necessary after Google?

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2012-01-01

    believe that the activity of “classification” is not worth the effort, as search engines can be improved without the heavy cost of providing metadata. Design/methodology/approach – The basic issue in classification is seen as providing criteria for deciding whether A should be classified as X...

  18. Classification and risk assessment of individuals with familial polyposis, Gardner's syndrome, and familial non-polyposis colon cancer from [3H]thymidine labeling patterns in colonic epithelial cells

    International Nuclear Information System (INIS)

    Lipkin, M.; Blattner, W.A.; Gardner, E.J.; Burt, R.W.; Lynch, H.; Deschner, E.; Winawer, S.; Fraumeni, J.F. Jr.

    1984-01-01

    A probabilistic analysis has been developed to assist the binary classification and risk assessment of members of familial colon cancer kindreds. The analysis is based on the microautoradiographic observation of [ 3 H]thymidine-labeled epithelial cells in colonic mucosa of the kindred members. From biopsies of colonic mucosa which are labeled with [ 3 H]thymidine in vitro, the degree of similarity of each subject's cell-labeling pattern measured over entire crypts was automatically compared to the labeling patterns of high-risk and low-risk reference populations. Each individual was then presumptively classified and assigned to one of the reference populations, and a degree of risk for the classification was provided. In carrying out the analysis, a linear score was calculated for each individual relative to each of the reference populations, and the classification was based on the polarity of the score difference; the degree of risk was then quantitated from the magnitude of the score difference. When the method was applied to kindreds having either familial polyposis or familial non-polyposis colon cancer, it effectively segregated individuals affected with disease from others at low risk, with sensitivity and specificity ranging from 71 to 92%. Further application of the method to asymptomatic family members believed to be at 50% risk on the basis of pedigree evaluation revealed a biomodal distribution to nearly zero or full risk. The accuracy and simplicity of this approach and its capability of revealing early stages of abnormal colonic epithelial cell development indicate potential for preclinical screening of subjects at risk in cancer-prone kindreds and for assisting the analysis of modes of inheritance

  19. Design issues in studies of radon and lung cancer: Implications of the joint effect of smoking and radon

    International Nuclear Information System (INIS)

    Upfal, M.; Divine, G.; Siemiatycki, J.

    1995-01-01

    Many case-control studies have been undertaken to assess whether and to what extent residential radon exposure is a risk factor for lung cancer. Nearly all these studies have been conducted in populations including smokers and nonsmokers. In this paper, we show that, depending on the nature of the joint effect of radon and tobacco on lung cancer risk, it may be very difficult to detect a main effect due to radon in mixed smoking and nonsmoking populations. If the joint effect is closer to additive than multiplicative, the most cost-effective way to achieve adequate statistical power may be to conduct a study among never-smokers. Because the underlying joint effect is unknown, and because many studies have been carried out among mixed smoker and nonsmoker populations, it would be desirable to conduct some studies with adequate power among never-smokers only. 30 refs., 4 figs., 2 tabs

  20. PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

    Science.gov (United States)

    Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

    2018-03-01

    Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

  1. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  2. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

  3. A Qualitative Investigation of Health Care Professionals', Patients' and Partners' Views on Psychosocial Issues and Related Interventions for Couples Coping with Cancer.

    Directory of Open Access Journals (Sweden)

    Tim Regan

    Full Text Available There is growing evidence that cancer affects couples as an interdependent system and that couple-based psychosocial interventions are efficacious in reducing distress and improving coping skills. However, adoption of a couples-focused approach into cancer care is limited. Previous research has shown that patients and partners hold differing views from health care professionals (HCPs regarding their psychosocial needs, and HCPs from different disciplines also hold divergent views regarding couples' psychosocial needs. This study aimed to explore the perspectives of HCPs and couples on the provision of couple-focused psychosocial care in routine cancer services.A qualitative study using semi-structured interviews was undertaken with 20 HCPs (medical oncologists, nurses, psycho-oncology professionals and 20 couples where one member had been diagnosed with cancer (breast, prostate, head/neck, bowel, multiple myeloma. Interviews were analysed using the framework approach.Three core themes were identified: "How Do Couples Cope with Cancer?" emphasised the positive and negative coping strategies used by couples, and highlighted that partners perceived a lack of engagement by HCPs. "What Is Couple-focused Psychosocial Care for People with Cancer?" described varying perspectives regarding the value of couple-focused psychosocial care and variation in the types of support couples need among HCPs and couples. Whereas most couples did not perceive a need for specialist couple-focused support and interventions, most HCPs felt couple-focused psychosocial care was necessary. "How Can Couple-Focused Psychosocial Care be Improved?" described couples' view of a need for better provision of information, and the importance of their relationship with oncology clinicians. HCPs identified a lack of confidence in responding to the emotional needs of couples, and barriers to providing psychosocial care, including challenges identifying distress (through screening and

  4. Pulmonary function following adjuvant chemotherapy and radiotherapy for breast cancer and the issue of three-dimensional treatment planning

    International Nuclear Information System (INIS)

    Lind, P.A.R.M.; Glas, U.; Fornander, T.; Rosfors, S.; Bevegard, S.; Wennberg, B.

    1998-01-01

    Background and purpose: The frequency and grade of pulmonary complications following adjuvant radiotherapy for breast cancer are still debated. This study focuses on loss of pulmonary function. Materials and methods: We have measured the reduction of pulmonary function 5 months following radiotherapy in 144 node-positive stage II breast cancer patients by using pulmonary function tests. Results: No deterioration of pulmonary function was detected among the patients who were treated with local radiotherapy. On the contrary, there was a mean increase in diffusion capacity by 7% (P=0.004) following radiotherapy, which most likely was explained by the adjuvant chemotherapy administered prior to the baseline pulmonary function tests. Patients undergoing loco-regional radiotherapy showed a mean reduction in diffusion capacity by 5% (P<0.001) and in vital capacity by 3% (P=0.001). The subset of patients (9%) who were diagnosed with severe pulmonary complications needing cortisone treatment had significantly larger mean paired differences in vital capacity (-0.446 L, -15% (equivalent to 15 years of normal ageing or the loss of 3/4 of a lung lobe)) compared to the patients who were asymptomatic (-0.084 L) (P<0.05). When the effects of potential confounding factors and different radiotherapy techniques were tested on the reduction of pulmonary function by stepwise multiple regression analysis, a significant correlation was found only to loco-regional radiotherapy including the lower internal mammary lymph nodes. Conclusions: We conclude that a clinically important reduction of pulmonary function is seen in the subset of patients who are diagnosed with severe pulmonary complication following loco-regional radiotherapy for breast cancer. The results of this study warrant further studies based on individual lung dose volume histograms. (Copyright (c) 1998 Elsevier Science B.V., Amsterdam. All rights reserved.)

  5. 3-Bromopyruvate (3BP) a fast acting, promising, powerful, specific, and effective "small molecule" anti-cancer agent taken from labside to bedside: introduction to a special issue.

    Science.gov (United States)

    Pedersen, Peter L

    2012-02-01

    . Significantly, in subsequent experiments with rodents (19 animals with advanced cancer) Ko led a project in which 3BP was shown in a short treatment period to eradicate all (100%). Ko's and co-author's findings once published attracted global attention leading world-wide to many other studies and publications related to 3BP and its potent anti-cancer effect. This Issue of the Journal of Bioenergetics and Biomembranes (JOBB 44-1) captures only a sampling of research conducted to date on 3BP as an anticancer agent, and includes also a Case Report on the first human patient known to the author to be treated with specially formulated 3BP. Suffice it to say in this bottom line, "3BP, a small molecule, results in a remarkable therapeutic effect when it comes to treating cancers exhibiting a "Warburg effect". This includes most cancer types.

  6. 5 CFR 511.607 - Nonappealable issues.

    Science.gov (United States)

    2010-01-01

    ... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Nonappealable issues. 511.607 Section 511... UNDER THE GENERAL SCHEDULE Classification Appeals § 511.607 Nonappealable issues. (a) The following issues are not appealable to the Office under this subpart. Such issues may be reviewed under...

  7. Hazard classification methodology

    International Nuclear Information System (INIS)

    Brereton, S.J.

    1996-01-01

    This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

  8. Quality and safety issues of web-based information about herbal medicines in the treatment of cancer.

    Science.gov (United States)

    Molassiotis, Alexander; Xu, Min

    2004-12-01

    A number of studies have been carried out to assess health information on the internet and they all have demonstrated that, whereas the internet can be the third opinion for many patients, often contains inaccurate and misleading information. Furthermore, as herbal medicines are increasingly used by patients, it is imperative to assess the quality of information presented on the internet. Hence, the aim of this study was to assess the quality and safety of the information presented on the internet about medicinal herbs specifically in the field of cancer. Two hundred relevant websites were initially selected from a process using 10 search engines and the keywords 'herbs' and 'cancer', and 43 sites actually met all inclusion criteria. Assessment of both quality and safety indicators was carried out using the DISCERN instrument, which has been developed to enable consumers and information providers to judge the quality of health information. Readability scores of the sites were also obtained (Flesch formula). It was shown that most sites had low quality in a number of indicators, including accuracy of information, revealing sources of information, biased presentation of information or regularity of updates. The mean score for quality was 22.12 (S.D.=4.18) out of a maximum score of 50. The mean safety score was 13.26 (S.D.=2.14) out of a maximum score of 30. Commercial sites had the most inaccurate or misleading information, emphasizing only the positive aspects of the use of herbs, with little or no evidence. The only biomedical sites assessed achieved the highest score in both quality and safety. Readability of the information was equal to the school level of college (mean=44.63). Seven percent of the sites discouraged the use of conventional medicine. Results suggest that health professionals should talk about use of alternative therapies with their patients and help them find the best available information when using the internet.

  9. The PiGeOn project: protocol for a longitudinal study examining psychosocial, behavioural and ethical issues and outcomes in cancer tumour genomic profiling.

    Science.gov (United States)

    Best, Megan; Newson, Ainsley J; Meiser, Bettina; Juraskova, Ilona; Goldstein, David; Tucker, Kathy; Ballinger, Mandy L; Hess, Dominique; Schlub, Timothy E; Biesecker, Barbara; Vines, Richard; Vines, Kate; Thomas, David; Young, Mary-Anne; Savard, Jacqueline; Jacobs, Chris; Butow, Phyllis

    2018-04-05

    Genomic sequencing in cancer (both tumour and germline), and development of therapies targeted to tumour genetic status, hold great promise for improvement of patient outcomes. However, the imminent introduction of genomics into clinical practice calls for better understanding of how patients value, experience, and cope with this novel technology and its often complex results. Here we describe a protocol for a novel mixed-methods, prospective study (PiGeOn) that aims to examine patients' psychosocial, cognitive, affective and behavioural responses to tumour genomic profiling and to integrate a parallel critical ethical analysis of returning results. This is a cohort sub-study of a parent tumour genomic profiling programme enrolling patients with advanced cancer. One thousand patients will be recruited for the parent study in Sydney, Australia from 2016 to 2019. They will be asked to complete surveys at baseline, three, and five months. Primary outcomes are: knowledge, preferences, attitudes and values. A purposively sampled subset of patients will be asked to participate in three semi-structured interviews (at each time point) to provide deeper data interpretation. Relevant ethical themes will be critically analysed to iteratively develop or refine normative ethical concepts or frameworks currently used in the return of genetic information. This will be the first Australian study to collect longitudinal data on cancer patients' experience of tumour genomic profiling. Findings will be used to inform ongoing ethical debates on issues such as how to effectively obtain informed consent for genomic profiling return results, distinguish between research and clinical practice and manage patient expectations. The combination of quantitative and qualitative methods will provide comprehensive and critical data on how patients cope with 'actionable' and 'non-actionable' results. This information is needed to ensure that when tumour genomic profiling becomes part of routine

  10. Classification of Laser Induced Fluorescence Spectra from Normal and Malignant bladder tissues using Learning Vector Quantization Neural Network in Bladder Cancer Diagnosis

    DEFF Research Database (Denmark)

    Karemore, Gopal Raghunath; Mascarenhas, Kim Komal; Patil, Choudhary

    2008-01-01

    In the present work we discuss the potential of recently developed classification algorithm, Learning Vector Quantization (LVQ), for the analysis of Laser Induced Fluorescence (LIF) Spectra, recorded from normal and malignant bladder tissue samples. The algorithm is prototype based and inherently...

  11. Attitudes toward Palliative Care and End of Life Issues: A Prospective Survey in Patients with Metastatic Cancer

    LENUS (Irish Health Repository)

    Docherty, C

    2016-05-01

    Palliative care (PC) positively impacts patient outcomes, decreases hospital admissions and improves quality of life. Despite evidence, PC resources are reported as under-utilised. Few studies have explored patient attitudes towards PC. This study evaluated patient attitudes towards PC. It was a prospective study conducted in oncology outpatient clinics. A 26-item questionnaire was distributed to those with metastatic cancer (N = 44). Sixty percent believed PC can make people ‘feel better’, 63.4% believed PC is offered when nothing more can be done. Most were unsure or disagreed that opioids are addictive. Eighty percent reported symptom control is more important than prolonging life. Sixty-one percent strongly agreed or agreed that ‘losing hope makes people die sooner’. Although PC was deemed beneficial, a significant relationship exists between familiarity with PC and thinking it’s offered when ‘nothing more can be done’. Lack of knowledge about opioids, preference for symptom control over life prolonging measures and the importance of hope were also emphasised.

  12. Professionals' views on the issues and challenges arising from providing a fertility preservation service through sperm banking to teenage males with cancer.

    Science.gov (United States)

    Crawshaw, Marilyn; Glaser, Adam; Hale, Juliet; Sloper, Patricia

    2004-03-01

    Interviews were undertaken with 22 health and social work professionals. Their analysis was completed using "selective transcription", noting understanding of process, issues and themes, and building a picture against which to consider the analysis of subsequent interviews with teenagers and parents. Professionals were also asked to identify areas for feedback from these participants. This work was part of a larger study of (i) the perceptions of adolescent males and their parents of fertility preservation services following a cancer diagnosis, and (ii) national postal surveys of common practices, areas of variance and issues experienced by professionals in UK regional paediatric oncology centres and licensed assisted conception centres. A large number of concerns were identified, which reflected professionals' difficulties in building and maintaining a relevant, adequate knowledge and skills base given the limited numbers of teenagers offered this service. The lack of appropriate training about the legal and consent frameworks, and the processes involved was also highlighted across all professional groups as was the confusion around professional and legal responsibilities for follow up. Thus, there was considerable professional uncertainty in a number of aspects of this sensitive area of service provision. Consideration needs to be given to the needs for national guidance, for training, support and updating, for liaison between the different health and social care sectors that may be involved, and for appropriate information systems. These need to be in place for each stage of the process, from diagnosis through to eventual discharge from the health system.

  13. Radioactive iodine (131I) therapy for differentiated thyroid cancer in Japan. Current issues with historical review and future perspective

    International Nuclear Information System (INIS)

    Higashi, Tatsuya; Kudo, Takashi; Kinuya, Seigo

    2012-01-01

    Radioactive iodine (RAI, 131 I) has been used as a therapeutic agent for differentiated thyroid cancer (DTC) with over 50 years of history. Recently, it is now attracting attention in medical fields as one of the molecular targeting therapies, which is known as targeted radionuclide therapy. Radioactive iodine therapy (RIT) for DTC, however, is now at stake in Japan, because Japan is confronting several problems, including the recent occurrence of the Great East Japan Disaster (GEJD) in March 2011. RIT for DTC is strictly limited in Japan and requires hospitalization. Because of strict regulations, severe lack of medical facilities for RIT has become one of the most important medical problems, which results in prolonged waiting time for Japanese patients with DTC, including those with distant metastasis, who wish to receive RIT immediately. This situation is also due to various other factors, such as prolonged economic recession, super-aging society, and subsequent rapidly changing medical environment. In addition, due to the experience of atomic bombings in Hiroshima and Nagasaki, Japanese people have strong feeling of ''radiophobia ''. There is fear that GEJD and related radiation contamination may worsen this feeling, which might be reflected in more severe regulation of RIT. To overcome these difficulties, it is essential to collect and disclose all information about the circumstances around this therapy in Japan. In this review, we would like to look at this therapy through several lenses, including historical, cultural, medical, and socio-economic points of view. We believe that clarifying the problems is sure to lead to the resolution of this complicated situation. We have also included several recommendations for future improvements. (author)

  14. Exposure to a patient-centered, Web-based intervention for managing cancer symptom and quality of life issues: impact on symptom distress.

    Science.gov (United States)

    Berry, Donna L; Blonquist, Traci M; Patel, Rupa A; Halpenny, Barbara; McReynolds, Justin

    2015-06-03

    Effective eHealth interventions can benefit a large number of patients with content intended to support self-care and management of both chronic and acute conditions. Even though usage statistics are easily logged in most eHealth interventions, usage or exposure has rarely been reported in trials, let alone studied in relationship to effectiveness. The intent of the study was to evaluate use of a fully automated, Web-based program, the Electronic Self Report Assessment-Cancer (ESRA-C), and how delivery and total use of the intervention may have affected cancer symptom distress. Patients at two cancer centers used ESRA-C to self-report symptom and quality of life (SxQOL) issues during therapy. Participants were randomized to ESRA-C assessment only (control) or the ESRA-C intervention delivered via the Internet to patients' homes or to a tablet at the clinic. The intervention enabled participants to self-monitor SxQOL and receive self-care education and customized coaching on how to report concerns to clinicians. Overall and voluntary intervention use were defined as having ≥2 exposures, and one non-prompted exposure to the intervention, respectively. Factors associated with intervention use were explored with Fisher's exact test. Propensity score matching was used to select a sample of control participants similar to intervention participants who used the intervention. Analysis of covariance (ANCOVA) was used to compare change in Symptom Distress Scale (SDS-15) scores from pre-treatment to end-of-study by groups in the matched sample. Radiation oncology participants used the intervention, overall and voluntarily, more than medical oncology and transplant participants. Participants who were working and had more than a high school education voluntarily used the intervention more. The SDS-15 score was reduced by an estimated 1.53 points (P=.01) in the intervention group users compared to the matched control group. The intended effects of a Web-based, patient

  15. Pediatric Thyroid Cancer

    Science.gov (United States)

    ... Marketplace Find an ENT Doctor Near You Pediatric Thyroid Cancer Pediatric Thyroid Cancer Patient Health Information News media ... and neck issues, should be consulted. Types of thyroid cancer in children: Papillary : This form of thyroid cancer ...

  16. SAW Classification Algorithm for Chinese Text Classification

    OpenAIRE

    Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

    2015-01-01

    Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

  17. Surgical nurses' work-related stress when caring for severely ill and dying patients in cancer after participating in an educational intervention on existential issues.

    Science.gov (United States)

    Udo, Camilla; Danielson, Ella; Henoch, Ingela; Melin-Johansson, Christina

    2013-10-01

    The aim of this study was to describe surgical nurses' perceived work-related stress in the care of severely ill and dying patients with cancer after participating in an educational intervention on existential issues. This article reports a mixed methods pilot study of an education programme consisting of lectures and supervised discussions conducted in 2009-2010 in three surgical wards in a county hospital in Sweden. The concurrent data collections consisted of repeated interviews with eleven nurses in an educational group, and questionnaires were distributed to 42 nurses on four occasions. Directly after the educational intervention, the nurses described working under high time pressure. They also described being hindered in caring because of discrepancies between their caring intentions and what was possible in the surgical care context. Six months later, the nurses described a change in decision making, and a shift in the caring to make it more in line with their own intentions and patients' needs rather than the organizational structure. They also reported decreased feelings of work-related stress, decreased stress associated with work-load and feeling less disappointed at work. Results indicate that it may be possible to influence nurses' work-related stress through an educational intervention. According to nurses' descriptions, reflecting on their ways of caring for severely ill and dying patients, many of whom had cancer, from an existential perspective, had contributed to enhanced independent decision making in caring. This in turn appears to have decreased their feelings of work-related stress and disappointment at work. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Classification of Radioactive Waste. General Safety Guide

    International Nuclear Information System (INIS)

    2009-01-01

    This publication is a revision of an earlier Safety Guide of the same title issued in 1994. It recommends revised waste management strategies that reflect changes in practices and approaches since then. It sets out a classification system for the management of waste prior to disposal and for disposal, driven by long term safety considerations. It includes a number of schemes for classifying radioactive waste that can be used to assist with planning overall national approaches to radioactive waste management and to assist with operational management at facilities. Contents: 1. Introduction; 2. The radioactive waste classification scheme; Appendix: The classification of radioactive waste; Annex I: Evolution of IAEA standards on radioactive waste classification; Annex II: Methods of classification; Annex III: Origin and types of radioactive waste

  19. Classification of Radioactive Waste. General Safety Guide

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2009-11-15

    This publication is a revision of an earlier Safety Guide of the same title issued in 1994. It recommends revised waste management strategies that reflect changes in practices and approaches since then. It sets out a classification system for the management of waste prior to disposal and for disposal, driven by long term safety considerations. It includes a number of schemes for classifying radioactive waste that can be used to assist with planning overall national approaches to radioactive waste management and to assist with operational management at facilities. Contents: 1. Introduction; 2. The radioactive waste classification scheme; Appendix: The classification of radioactive waste; Annex I: Evolution of IAEA standards on radioactive waste classification; Annex II: Methods of classification; Annex III: Origin and types of radioactive waste.

  20. Collateral in Loan Classification and Provisioning

    OpenAIRE

    In W Song

    2002-01-01

    Adequate loan classification practices are an essential part of a sound and effective credit risk-management process in a bank. Failure to identify deterioration in credit quality in a timely manner can aggravate and prolong the problem. Two key issues arise with regard to the use of collateral in the context of loan classification and provisioning. In particular, the questions arise whether collateral should be taken into account in classifying a collateralized loan, and whether it should be...

  1. Cancer

    Science.gov (United States)

    Cancer begins in your cells, which are the building blocks of your body. Normally, your body forms ... be benign or malignant. Benign tumors aren't cancer while malignant ones are. Cells from malignant tumors ...

  2. Classification of neuropathic pain in cancer patients: A Delphi expert survey report and EAPC/IASP proposal of an algorithm for diagnostic criteria.

    Science.gov (United States)

    Brunelli, Cinzia; Bennett, Michael I; Kaasa, Stein; Fainsinger, Robin; Sjøgren, Per; Mercadante, Sebastiano; Løhre, Erik T; Caraceni, Augusto

    2014-12-01

    Neuropathic pain (NP) in cancer patients lacks standards for diagnosis. This study is aimed at reaching consensus on the application of the International Association for the Study of Pain (IASP) special interest group for neuropathic pain (NeuPSIG) criteria to the diagnosis of NP in cancer patients 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 in patients with cancer, IASP NeuPSIG diagnostic criteria adaptation and assessment, and standardized PRO assessment for NP screening. Median consensus scores (MED) and interquartile ranges (IQR) were calculated to measure expert consensus after both rounds. Twenty-nine experts answered, and good agreement 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/imaging; MED=6, IQR=3). Agreement was also reached on clinical examination by soft brush or pin stimulation (MEDs⩾7 and IQRs⩽3) and on the use of PRO descriptors for NP screening (MED=8, IQR=3). Based on the study results, a clinical algorithm for NP diagnostic criteria in cancer patients with pain was proposed. Clinical research on PRO in the screening phase and on the application of the algorithm will be needed to examine their effectiveness in classifying NP in cancer patients. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  3. Characteristics of Differently Located Colorectal Cancers Support Proximal and Distal Classification: A Population-Based Study of 57,847 Patients.

    Directory of Open Access Journals (Sweden)

    Jiao Yang

    Full Text Available It has been suggested that colorectal cancer be regarded as several subgroups defined according to tumor location rather than as a single entity. The current study aimed to identify the most useful method for grouping colorectal cancer by tumor location according to both baseline and survival characteristics.Cases of pathologically confirmed colorectal adenocarcinoma diagnosed from 2000 to 2012 were identified from the Surveillance, Epidemiology, and End Results database and categorized into three groups: right colon cancer (RCC, left colon cancer (LCC, and rectal cancer (ReC. Adjusted hazard ratios for known predictors of disease-specific survival (DSS in colorectal cancer were obtained using a Cox proportional hazards regression model.The study included 57847 patients: 43.5% with RCC, 37.7% with LCC, and 18.8% with ReC. Compared with LCC and ReC, RCC was more likely to affect old patients and women, and to be at advanced stage, poorly differentiated or un-differentiated, and mucinous. Patients with LCC or ReC had better DSS than those with RCC in subgroups including stage III or IV disease, age ≤70 years and non-mucinous adenocarcinoma. Conversely, patients with LCC or ReC had worse DSS than those with RCC in subgroups including age ˃70 years and mucinous adenocarcinoma.RCC differed from both LCC and ReC in several clinicopathologic characteristics and in DSS. It seems reasonable to group colorectal cancer into right-sided (i.e., proximal and left-sided (i.e., distal ones.

  4. {sup 18}F-FDG PET/CT quantification in head and neck squamous cell cancer: principles, technical issues and clinical applications

    Energy Technology Data Exchange (ETDEWEB)

    Manca, Gianpiero; Volterrani, Duccio [University Hospital of Pisa, Regional Center of Nuclear Medicine, Pisa (Italy); Vanzi, Eleonora [University Hospital of Siena, Service of Medical Physics, Siena (Italy); Rubello, Domenico; Grassetto, Gaia [Santa Maria della Misericordia Rovigo Hospital, Department of Nuclear Medicine, Rovigo (Italy); Giammarile, Francesco [Faculte Charles Merieux, Medecine Nucleaire, Centre Hospitalier and Biophysique, Lyon (France); Wong, Ka Kit [University of Michigan Hospital, Nuclear Medicine/Radiology Department, Ann Arbor, MI (United States); Nuclear Medicine Service, Department of Veterans Affairs Health System, Ann Arbor, MI (United States); Perkins, Alan C. [University of Nottingham, Department of Radiological Sciences, School of Medicine, Nottingham (United Kingdom); Colletti, Patrick M. [Southern University of California, Department of Radiology, Los Angeles, CA (United States)

    2016-07-15

    {sup 18}F-FDG PET/CT plays a crucial role in the diagnosis and management of patients with head and neck squamous cell cancer (HNSCC). The major clinical applications of this method include diagnosing an unknown primary tumour, identifying regional lymph node involvement and distant metastases, and providing prognostic information. {sup 18}F-FDG PET/CT is also used for precise delineation of the tumour volume for radiation therapy planning and dose painting, and for treatment response monitoring, by detecting residual or recurrent disease. Most of these applications would benefit from a quantitative approach to the disease, but the quantitative capability of {sup 18}F-FDG PET/CT is still underused in HNSCC. Innovations in PET/CT technology promise to overcome the issues that until now have hindered the employment of dynamic procedures in clinical practice and have limited ''quantification'' to the evaluation of standardized uptake values (SUV), de facto a semiquantitative parameter, the limits of which are well known to the nuclear medicine community. In this paper the principles of quantitative imaging and the related technical issues are reviewed so that professionals involved in HNSCC management can reflect on the advantages of ''true'' quantification. A discussion is then presented on how semiquantitative information is currently used in clinical {sup 18}F-FDG PET/CT applications in HNSCC, by discussing the improvements that could be obtained with more advanced and ''personalized'' quantification techniques. (orig.)

  5. Profiling of microRNAs in tumor interstitial fluid of breast tumors – a novel resource to identify biomarkers for prognostic classification and detection of cancer

    DEFF Research Database (Denmark)

    Halvorsen, Ann Rita; Helland, Åslaug; Gromov, Pavel

    2017-01-01

    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...

  6. Asteroid taxonomic classifications

    International Nuclear Information System (INIS)

    Tholen, D.J.

    1989-01-01

    This paper reports on three taxonomic classification schemes developed and applied to the body of available color and albedo data. Asteroid taxonomic classifications according to two of these schemes are reproduced

  7. Residual tumor size and IGCCCG risk classification predict additional vascular procedures in patients with germ cell tumors and residual tumor resection: a multicenter analysis of the German Testicular Cancer Study Group.

    Science.gov (United States)

    Winter, Christian; Pfister, David; Busch, Jonas; Bingöl, Cigdem; Ranft, Ulrich; Schrader, Mark; Dieckmann, Klaus-Peter; Heidenreich, Axel; Albers, Peter

    2012-02-01

    Residual tumor resection (RTR) after chemotherapy in patients with advanced germ cell tumors (GCT) is an important part of the multimodal treatment. To provide a complete resection of residual tumor, additional surgical procedures are sometimes necessary. In particular, additional vascular interventions are high-risk procedures that require multidisciplinary planning and adequate resources to optimize outcome. The aim was to identify parameters that predict additional vascular procedures during RTR in GCT patients. A retrospective analysis was performed in 402 GCT patients who underwent 414 RTRs in 9 German Testicular Cancer Study Group (GTCSG) centers. Overall, 339 of 414 RTRs were evaluable with complete perioperative data sets. The RTR database was queried for additional vascular procedures (inferior vena cava [IVC] interventions, aortic prosthesis) and correlated to International Germ Cell Cancer Collaborative Group (IGCCCG) classification and residual tumor volume. In 40 RTRs, major vascular procedures (23 IVC resections with or without prosthesis, 11 partial IVC resections, and 6 aortic prostheses) were performed. In univariate analysis, the necessity of IVC intervention was significantly correlated with IGCCCG (14.1% intermediate/poor vs 4.8% good; p=0.0047) and residual tumor size (3.7% size risk features must initially be identified as high-risk patients for vascular procedures and therefore should be referred to specialized surgical centers with the ad hoc possibility of vascular interventions. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights rese