Download or read book Biostatistical Applications in Cancer Research written by Craig Beam and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biostatistics is defined as much by its application as it is by theory. This book provides an introduction to biostatistical applications in modern cancer research that is both accessible and valuable to the cancer biostatistician or to the cancer researcher, learning biostatistics. The topical areas include active areas of the application of biostatistics to modern cancer research: survival analysis, screening, diagnostics, spatial analysis and the analysis of microarray data. Biostatistics is an essential component of basic and clinical cancer research. The text, authored by distinguished figures in the field, addresses clinical issues in statistical analysis. The spectrum of topics discussed ranges from fundamental methodology to clinical and translational applications.
Download or read book Frontiers of Biostatistical Methods and Applications in Clinical Oncology written by Shigeyuki Matsui and published by Springer. This book was released on 2017-10-03 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state of the art of biostatistical methods and their applications in clinical oncology. Many methodologies established today in biostatistics have been brought about through its applications to the design and analysis of oncology clinical studies. This field of oncology, now in the midst of evolution owing to rapid advances in biotechnologies and cancer genomics, is becoming one of the most promising disease fields in the shift toward personalized medicine. Modern developments of diagnosis and therapeutics of cancer have also been continuously fueled by recent progress in establishing the infrastructure for conducting more complex, large-scale clinical trials and observational studies. The field of cancer clinical studies therefore will continue to provide many new statistical challenges that warrant further progress in the methodology and practice of biostatistics. This book provides a systematic coverage of various stages of cancer clinical studies. Topics from modern cancer clinical trials include phase I clinical trials for combination therapies, exploratory phase II trials with multiple endpoints/treatments, and confirmative biomarker-based phase III trials with interim monitoring and adaptation. It also covers important areas of cancer screening, prognostic analysis, and the analysis of large-scale molecular data in the era of big data.
Download or read book Methods and Biostatistics in Oncology written by Raphael. L.C Araújo and published by Springer. This book was released on 2018-04-16 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces and discusses the most important aspects of clinical research methods and biostatistics for oncologists, pursuing a tailor-made and practical approach. Evidence-based medicine (EBM) has been in vogue in the last few decades, particularly in rapidly advancing fields such as oncology. This approach has been used to support decision-making processes worldwide, sparking new clinical research and guidelines on clinical and surgical oncology. Clinical oncology research has many peculiarities, including specific study endpoints, a special focus on survival analyses, and a unique perspective on EBM. However, during medical studies and in general practice, these topics are barely taught. Moreover, even when EBM and clinical cancer research are discussed, they are presented in a theoretical fashion, mostly focused on formulas and numbers, rather than on clinical application for a proper literature appraisal. Addressing that gap, this book discusses more practical aspects of clinical research and biostatistics in oncology, instead of relying only on mathematical formulas and theoretical considerations. Methods and Biostatistics in Oncology will help readers develop the skills they need to understand the use of research on everyday oncology clinical practice for study design and interpretation, as well to demystify the use of EBM in oncology.
Download or read book Stochastic Models Of Tumor Latency And Their Biostatistical Applications written by Alexander D Tsodikov and published by World Scientific. This book was released on 1996-03-20 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research monograph discusses newly developed mathematical models and methods that provide biologically meaningful inferences from data on cancer latency produced by follow-up and discrete surveillance studies. Methods for designing optimal strategies of cancer surveillance are systematically presented for the first time in this book. It offers new approaches to the stochastic description of tumor latency, employs biologically-based models for making statistical inference from data on tumor recurrence and also discusses methods of statistical analysis of data resulting from discrete surveillance strategies. It also offers insight into the role of prognostic factors based on the interpretation of their effects in terms of parameters endowed with biological meaning, as well as methods for designing optimal schedules of cancer screening and surveillance. Last but not least, it discusses survival models allowing for cure rates and the choice of optimal treatment based on covariate information, and presents numerous examples of real data analysis.
Download or read book High Dimensional Data Analysis in Cancer Research written by Xiaochun Li and published by Springer Science & Business Media. This book was released on 2008-12-19 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate analysis is a mainstay of statistical tools in the analysis of biomedical data. It concerns with associating data matrices of n rows by p columns, with rows representing samples (or patients) and columns attributes of samples, to some response variables, e.g., patients outcome. Classically, the sample size n is much larger than p, the number of variables. The properties of statistical models have been mostly discussed under the assumption of fixed p and infinite n. The advance of biological sciences and technologies has revolutionized the process of investigations of cancer. The biomedical data collection has become more automatic and more extensive. We are in the era of p as a large fraction of n, and even much larger than n. Take proteomics as an example. Although proteomic techniques have been researched and developed for many decades to identify proteins or peptides uniquely associated with a given disease state, until recently this has been mostly a laborious process, carried out one protein at a time. The advent of high throughput proteome-wide technologies such as liquid chromatography-tandem mass spectroscopy make it possible to generate proteomic signatures that facilitate rapid development of new strategies for proteomics-based detection of disease. This poses new challenges and calls for scalable solutions to the analysis of such high dimensional data. In this volume, we will present the systematic and analytical approaches and strategies from both biostatistics and bioinformatics to the analysis of correlated and high-dimensional data.
Download or read book Computational Biology written by Tuan Pham and published by Springer Science & Business Media. This book was released on 2009-09-23 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume covers techniques in computational biology and their applications in oncology. It details advanced statistical methods, heuristic algorithms, cluster analysis, data modeling, and image and pattern analysis applied to cancer research.
Download or read book Clinical Trial Biostatistics and Biopharmaceutical Applications written by Walter R. Young and published by CRC Press. This book was released on 2014-11-20 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since 1945, "The Annual Deming Conference on Applied Statistics" has been an important event in the statistics profession. In Clinical Trial Biostatistics and Biopharmaceutical Applications, prominent speakers from past Deming conferences present novel biostatistical methodologies in clinical trials as well as up-to-date biostatistical applications
Download or read book Principles and Applications of Biostatistics written by Ray M. Merrill and published by Jones & Bartlett Learning. This book was released on 2021-09-03 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles and Applications of Biostatistics covers the primary concepts and methods that are required for a fundamental understanding of the use and interpretation of statistics for the biological and health sciences–from data presentation to multiple regression and analysis of variance. With a focus clarity, brevity, and accuracy, this text provides understandable and focused explanation of statistical principles and applications along with practical examples (provided in R and Microsoft Excel) and problems drawn from biological health and medical settings. Key Features: • Practical questions follow each problem to encourage students to consider why the problem likely exists, help formulate hypotheses, and then statistically assess those hypotheses. • Abundant assignment problems at the end of sections and each chapter cover a variety of application areas of biostatistics. • Rationale boxes offer explanations of why certain methods are used for specific cases.
Download or read book The Evolution of the Use of Mathematics in Cancer Research written by Pedro Jose Gutiérrez Diez and published by Springer Science & Business Media. This book was released on 2012-02-17 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book will provide an exhaustive and clear explanation of how Statistics, Mathematics and Informatics have been used in cancer research, and seeks to help cancer researchers in achieving their objectives. To do so, state-of-the-art Biostatistics, Biomathematics and Bioinformatics methods will be described and discussed in detail through illustrative and capital examples taken from cancer research work already published. The book will provide a guide for cancer researchers in using Statistics, Mathematics and Informatics, clarifying the contribution of these logical sciences to the study of cancer, thoroughly explaining their procedures and methods, and providing criteria to their appropriate use.
Download or read book Cure Models written by Yingwei Peng and published by Chapman & Hall/CRC. This book was released on 2022-09-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book in the last 25 years that provides a comprehensive and systematic introduction to the basics of modern cure models, including estimation, inference, software. Statistical researchers, graduate students, and practitioners in other disciplines will have a thorough review of modern cure model methodology.
Download or read book Statistical Methods for Survival Trial Design written by Jianrong Wu and published by CRC Press. This book was released on 2018-06-14 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R provides a thorough presentation of the principles of designing and monitoring cancer clinical trials in which time-to-event is the primary endpoint. Traditional cancer trial designs with time-to-event endpoints are often limited to the exponential model or proportional hazards model. In practice, however, those model assumptions may not be satisfied for long-term survival trials. This book is the first to cover comprehensively the many newly developed methodologies for survival trial design, including trial design under the Weibull survival models; extensions of the sample size calculations under the proportional hazard models; and trial design under mixture cure models, complex survival models, Cox regression models, and competing-risk models. A general sequential procedure based on the sequential conditional probability ratio test is also implemented for survival trial monitoring. All methodologies are presented with sufficient detail for interested researchers or graduate students.
Download or read book Biostatistical Methods written by Stephen W. Looney and published by Springer Science & Business Media. This book was released on 2008-02-03 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leading biostatisticians and biomedical researchers describe many of the key techniques used to solve commonly occurring data analytic problems in molecular biology, and demonstrate how these methods can be used in the development of new markers for exposure to a risk factor or for disease outcomes. Major areas of application include microarray analysis, proteomic studies, image quantitation, genetic susceptibility and association, evaluation of new biomarkers, and power analysis and sample size.
Download or read book Statistical Methods for Survival Trial Design written by Jianrong Wu and published by CRC Press. This book was released on 2018-06-14 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R provides a thorough presentation of the principles of designing and monitoring cancer clinical trials in which time-to-event is the primary endpoint. Traditional cancer trial designs with time-to-event endpoints are often limited to the exponential model or proportional hazards model. In practice, however, those model assumptions may not be satisfied for long-term survival trials. This book is the first to cover comprehensively the many newly developed methodologies for survival trial design, including trial design under the Weibull survival models; extensions of the sample size calculations under the proportional hazard models; and trial design under mixture cure models, complex survival models, Cox regression models, and competing-risk models. A general sequential procedure based on the sequential conditional probability ratio test is also implemented for survival trial monitoring. All methodologies are presented with sufficient detail for interested researchers or graduate students.
Download or read book Statistical Methods for Cancer Studies written by Richard G. Cornell and published by CRC Press. This book was released on 2020-11-26 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on public health and epidemiologic aspects of cancer, and explores the sources of information concerning the frequency of occurrence of human cancer. It describes statistical methods useful in studying problems arising in the field of cancer and its concurrent development.
Download or read book High Dimensional Data Analysis in Cancer Research written by Xiaochun Li and published by Springer. This book was released on 2008-12-12 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate analysis is a mainstay of statistical tools in the analysis of biomedical data. It concerns with associating data matrices of n rows by p columns, with rows representing samples (or patients) and columns attributes of samples, to some response variables, e.g., patients outcome. Classically, the sample size n is much larger than p, the number of variables. The properties of statistical models have been mostly discussed under the assumption of fixed p and infinite n. The advance of biological sciences and technologies has revolutionized the process of investigations of cancer. The biomedical data collection has become more automatic and more extensive. We are in the era of p as a large fraction of n, and even much larger than n. Take proteomics as an example. Although proteomic techniques have been researched and developed for many decades to identify proteins or peptides uniquely associated with a given disease state, until recently this has been mostly a laborious process, carried out one protein at a time. The advent of high throughput proteome-wide technologies such as liquid chromatography-tandem mass spectroscopy make it possible to generate proteomic signatures that facilitate rapid development of new strategies for proteomics-based detection of disease. This poses new challenges and calls for scalable solutions to the analysis of such high dimensional data. In this volume, we will present the systematic and analytical approaches and strategies from both biostatistics and bioinformatics to the analysis of correlated and high-dimensional data.
Download or read book Handbook of Statistics in Clinical Oncology Third Edition written by John Crowley and published by CRC Press. This book was released on 2012-03-26 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many new challenges have arisen in the area of oncology clinical trials. New cancer therapies are often based on cytostatic or targeted agents, which pose new challenges in the design and analysis of all phases of trials. The literature on adaptive trial designs and early stopping has been exploding. Inclusion of high-dimensional data and imaging techniques have become common practice, and statistical methods on how to analyse such data have been refined in this area. A compilation of statistical topics relevant to these new advances in cancer research, this third edition of Handbook of Statistics in Clinical Oncology focuses on the design and analysis of oncology clinical trials and translational research. Addressing the many challenges that have arisen since the publication of its predecessor, this third edition covers the newest developments involved in the design and analysis of cancer clinical trials, incorporating updates to all four parts: Phase I trials: Updated recommendations regarding the standard 3 + 3 and continual reassessment approaches, along with new chapters on phase 0 trials and phase I trial design for targeted agents. Phase II trials: Updates to current experience in single-arm and randomized phase II trial designs. New chapters include phase II designs with multiple strata and phase II/III designs. Phase III trials: Many new chapters include interim analyses and early stopping considerations, phase III trial designs for targeted agents and for testing the ability of markers, adaptive trial designs, cure rate survival models, statistical methods of imaging, as well as a thorough review of software for the design and analysis of clinical trials. Exploratory and high-dimensional data analyses: All chapters in this part have been thoroughly updated since the last edition. New chapters address methods for analyzing SNP data and for developing a score based on gene expression data. In addition, chapters on risk calculators and forensic bioinformatics have been added. Accessible to statisticians and oncologists interested in clinical trial methodology, the book is a single-source collection of up-to-date statistical approaches to research in clinical oncology.
Download or read book Biostatistical Applications in Health Research written by Robert P. Hirsch and published by . This book was released on 2008 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt:
