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Clinical Trials In Oncology Third Edition

Author: Stephanie Green
Publisher: CRC Press
ISBN: 1439814481
Size: 47.83 MB
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The third edition of the bestselling Clinical Trials in Oncology provides a concise, nontechnical, and thoroughly up-to-date review of methods and issues related to cancer clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the pitfalls inherent in these processes. In addition, the book has been restructured to have separate chapters and expanded discussions on general clinical trials issues, and issues specific to Phases I, II, and III. New sections cover innovations in Phase I designs, randomized Phase II designs, and overcoming the challenges of array data. Although this book focuses on cancer trials, the same issues and concepts are important in any clinical setting. As always, the authors use clear, lucid prose and a multitude of real-world examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Armed with Clinical Trials in Oncology, Third Edition, clinicians and statisticians can avoid the many hazards that can jeopardize the success of a trial.

Design And Analysis Of Quality Of Life Studies In Clinical Trials Second Edition

Author: Diane L. Fairclough
Publisher: CRC Press
ISBN: 1420061186
Size: 13.58 MB
Format: PDF, ePub
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Design Principles and Analysis Techniques for HRQoL Clinical Trials SAS, R, and SPSS examples realistically show how to implement methods Focusing on longitudinal studies, Design and Analysis of Quality of Life Studies in Clinical Trials, Second Edition addresses design and analysis aspects in enough detail so that readers can apply statistical methods, such as mixed effect models, to their own studies. The author illustrates the implementation of the methods using the statistical software packages SAS, SPSS, and R. New to the Second Edition Data sets available for download online, allowing readers to replicate the analyses presented in the text New chapter on testing models that involve moderation and mediation Revised discussions of multiple comparisons procedures that focus on the integration of health-related quality of life (HRQoL) outcomes with other study outcomes using gatekeeper strategies Recent methodological developments for the analysis of trials with missing data New chapter on quality adjusted life-years (QALYs) and QTWiST specific to clinical trials Additional examples of the implementation of basic models and other selected applications in R and SPSS This edition continues to provide practical information for researchers directly involved in the design and analysis of HRQoL studies as well as for those who evaluate the design and interpret the results of HRQoL research. By following the examples in the book, readers will be able to apply the steps to their own trials.

Oncology Clinical Trials

Author: William Kevin Kelly, DO
Publisher: Springer Publishing Company
ISBN: 0826168736
Size: 79.61 MB
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The second edition of Oncology Clinical Trials has been thoroughly revised and updated and now contains the latest designs and methods of conducting and analyzing cancer clinical trials in the era of precision medicine with biologic agents—including trials investigating the safety and efficacy of targeted therapies, immunotherapies, and combination therapies as well as novel radiation therapy modalities. Now divided into six sections this revamped book provides the necessary background and expert guidance from the principles governing oncology clinical trials to the innovative statistical design methods permeating the field; from conducting trials in a safe and effective manner, analyzing and interpreting the data, to a forward-looking assessment and discussion of regulatory issues impacting domestic, international, and global clinical trials. Considered by many as the gold standard reference on oncology clinical trials in the field, the second edition continues to provide examples of real-life flaws and real-world examples for how to successfully design, conduct and analyze quality clinical trials and interpret them. With chapters written by oncologists, researchers, biostatisticians, clinical research administrators, and industry and FDA representatives, this volume provides a comprehensive guide in the design, conduct, monitoring, analysis, and reporting of clinical trials in oncology. NEW TO THIS EDITION: Outlines how to design clinical trials with and without biomarker testing—including genomics-based “basket” trials, and adaptive trials for all phases during treatment and quality-of-life trials Includes new chapters on immunotherapy trials, radiation therapy trials, multi-arm trials, meta-analysis and adaptive design, use of genomics, dose modifications and use of ancillary treatments in investigational studies, establishing surrogate endpoints, practical issues with correlative studies, cost-effectiveness analysis, and more Comprehensively covers all regulatory aspects in the pursuit of global oncology trials Digital access to the ebook included

Clinical Trials In Oncology Second Edition

Author: Stephanie Green
Publisher: Chapman and Hall/CRC
ISBN: 9781584883029
Size: 78.87 MB
Format: PDF, Docs
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Studies that are unimpeachably thorough, non-political, unbiased, and properly designed... These are the standards to which everyone in clinical research aspires. Yet, the difficulties in designing trials and interpreting data are subtle and ever present. The new edition of Clinical Trials in Oncology provides a concise, nontechnical, and now thoroughly up-to-date review of methods and issues related to clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the major pitfalls that are seemingly inherent in these processes. This edition includes a new section that describes recent innovations in Phase I designs. Another new section on microarray data examines the challenges presented by massive data sets and describes approaches used to meet those challenges. As always, the authors use clear, lucid prose and a multitude of real-world trials as examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Although the book focuses on cancer trials, the issues and concepts are important in any clinical setting. Clinical Trials in Oncology, Second Edition works to improve the mutual understanding by clinicians and statisticians of the principles of clinical trials and helps them avoid the many hazards that can jeopardize the success of a trial.

Bayesian Disease Mapping

Author: Andrew B. Lawson
Publisher: CRC Press
ISBN: 1466504811
Size: 71.56 MB
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Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. A biostatistics professor and WHO advisor, the author illustrates the use of Bayesian hierarchical modeling in the geographical analysis of disease through a range of real-world datasets. New to the Second Edition Three new chapters on regression and ecological analysis, putative hazard modeling, and disease map surveillance Expanded material on case event modeling and spatiotemporal analysis New and updated examples Two new appendices featuring examples of integrated nested Laplace approximation (INLA) and conditional autoregressive (CAR) models In addition to these new topics, the book covers more conventional areas such as relative risk estimation, clustering, spatial survival analysis, and longitudinal analysis. After an introduction to Bayesian inference, computation, and model assessment, the text focuses on important themes, including disease map reconstruction, cluster detection, regression and ecological analysis, putative hazard modeling, analysis of multiple scales and multiple diseases, spatial survival and longitudinal studies, spatiotemporal methods, and map surveillance. It shows how Bayesian disease mapping can yield significant insights into georeferenced health data. WinBUGS and R are used throughout for data manipulation and simulation.

Visualizing Data Patterns With Micromaps

Author: Daniel B. Carr
Publisher: CRC Press
ISBN: 9781420075748
Size: 64.93 MB
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After more than 15 years of development drawing on research in cognitive psychology, statistical graphics, computer science, and cartography, micromap designs are becoming part of mainstream statistical visualizations. Bringing together the research of two leaders in this field, Visualizing Data Patterns with Micromaps presents the many design variations and applications of micromaps, which link statistical information to an organized set of small maps. This full-color book helps readers simultaneously explore the statistical and geographic patterns in their data. After illustrating the three main types of micromaps, the authors summarize the research behind the design of visualization tools that support exploration and communication of spatial data patterns. They then explain how these research findings can be applied to micromap designs in general and detail the specifics involved with linked, conditioned, and comparative micromap designs. To compare and contrast their purposes, limitations, and strengths, the final chapter applies all three of these techniques to the same demographic data for Louisiana before and after Hurricanes Katrina and Rita. Supplementary website Offering numerous ancillary features, the book’s website at http://mason.gmu.edu/~dcarr/Micromaps/ provides many boundary files and real data sets that address topics, such species biodiversity and alcoholism. One complete folder of data examples presents cancer statistics, risk factors, and demographic data. The site includes CCmaps, the dynamic implementation of conditioned micromaps written in Java, as well as a link to a generalized micromaps program. It also contains R functions and scripts for linked and comparative micromaps, enabling re-creation of all the corresponding examples in the book.

Age Period Cohort Analysis

Author: Yang Yang
Publisher: CRC Press
ISBN: 1466507535
Size: 40.98 MB
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Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of the authors’ collaborative work in age-period-cohort (APC) analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs: age-by-time period tables of population rates or proportions, repeated cross-section sample surveys, and accelerated longitudinal panel studies. The authors show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables develop along the age, period, and cohort dimensions. The book makes two essential contributions to quantitative studies of time-related change. Through the introduction of the GLMM framework, it shows how innovative estimation methods and new model specifications can be used to tackle the "model identification problem" that has hampered the development and empirical application of APC analysis. The book also addresses the major criticism against APC analysis by explaining the use of new models within the GLMM framework to uncover mechanisms underlying age patterns and temporal trends. Encompassing both methodological expositions and empirical studies, this book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. It compares new and existing models and methods and provides useful guidelines on how to conduct APC analysis. For empirical illustrations, the text incorporates examples from a variety of disciplines, such as sociology, demography, and epidemiology. Along with details on empirical analyses, software and programs to estimate the models are available on the book’s web page.

Cancer Clinical Trials

Author: Stephen L. George
Publisher: CRC Press
ISBN: 1498706908
Size: 17.64 MB
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Cancer Clinical Trials: Current and Controversial Issues in Design and Analysis provides statisticians with an understanding of the critical challenges currently encountered in oncology trials. Well-known statisticians from academic institutions, regulatory and government agencies (such as the U.S. FDA and National Cancer Institute), and the pharmaceutical industry share their extensive experiences in cancer clinical trials and present examples taken from actual trials. The book covers topics that are often perplexing and sometimes controversial in cancer clinical trials. Most of the issues addressed are also important for clinical trials in other settings. After discussing general topics, the book focuses on aspects of early and late phase clinical trials. It also explores personalized medicine, including biomarker-based clinical trials, adaptive clinical trial designs, and dynamic treatment regimes.

Phase I Cancer Clinical Trials

Author: Elizabeth A. Eisenhauer
Publisher: Oxford University Press
ISBN: 0199359032
Size: 75.28 MB
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Phase I trials are a critical first step in the study of novel cancer therapeutic approaches. Their primary goals are to identify the recommended dose, schedule and pharmacologic behavior of new agents or new combinations of agents and to describe the adverse effects of treatment. In cancer therapeutics, such studies have particular challenges. Due to the nature of the effects of treatment, most such studies are conducted in patients with advanced malignancy, rather than in healthy volunteers. Further, the endpoints of these trials are usually measures adverse effects rather than molecular target or anti-tumor effects. These factors render the design, conduct, analysis and ethical aspects of phase I cancer trials unique. As the only comprehensive book on this topic, Phase I Cancer Clinical Trials is a useful resource for oncology trainees or specialists interested in understanding cancer drug development. New to this edition are chapters on Phase 0 Trials and Immunotherapeutics, and updated information on the process, pitfalls, and logistics of Phase I Trials

Computational Genome Analysis

Author: Richard C. Deonier
Publisher: Springer Science & Business Media
ISBN: 0387288074
Size: 68.26 MB
Format: PDF, Kindle
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This book presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters.