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Multiple Analyses In Clinical Trials

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Multiple Analyses In Clinical Trials

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Author : Lemuel A. Moyé
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-17

Multiple Analyses In Clinical Trials written by Lemuel A. Moyé and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-17 with Medical categories.

One of the most challenging issues for clinical trial investigators, sponsors, and regulatory officials is the interpretation of experimental results that are composed of the results of multiple statistical analyses. These analyses may include the effect of therapy on multiple endpoints, the assessment of a subgroup analysis, and the evaluation of a dose-response relationship in complex mixtures. Multiple Analyses in Clinical Trials: Fundamentals for Clinical Investigators is an essentially nonmathematical discussion of the problems posed by the execution of multiple analyses in clinical trials. It concentrates on the rationale for the analyses, the difficulties posed by their interpretation, easily understood solutions, and useful problem sets. This text will help clinical investigators understand multiple analysis procedures and the key issues when designing their own work or reviewing the research of others. This book is written for advanced medical students, clinical investigators at all levels, research groups within the pharmaceutical industry, regulators at the local, state, and federal level, and biostatisticians. Only a basic background in health care and introductory statistics is required. Dr. Lemuel A. Moyé, M.D., Ph.D. is a physician and Professor of Biometry at the University of Texas School of Public Health. He has been Co-Principal Investigator of two multinational clinical trials examining the role of innovative therapy in post myocardial infarction survival (SAVE) and the use of cholesterol reducing agents in post myocardial infarction survival in patients with normal cholesterol levels (CARE). He has authored over one hundred articles in journals such as the Journal of the American Medical Association, the New England Journal of Medicine, Statistics in Medicine, and Controlled Clinical Trials. From the reviews: From the reviews: "A quick scan of the book indicates that it is not a typical statistics book...You can jumpin almost anywhere and just start reading...I like the book’s organization. There is a chapter on clinical trials. Then there are several chapters that explain the situations that arise from the occurrence of multiple analyses. Particular emphasis is given to multiple endpoints, situations where one continues a study to follow up on unanticipated results, and to subgroup analyses, interventions that impact only a fraction of the subjects in a study. The author is equally adept at describing clinical trials for the statistician as at explaining statistics to the clinical investigator. I enjoyed leafing through this book and would certainly enjoy have the opportunity to sit down and read it." Technometrics, August 2004 "Moyé’s background as a statistician and MD makes him especially qualified to write this book...The clinical trial examples are a major strength of the book...His medical background and extensive clinical trials experience shine through." Statistics in Medicine, 2004, 23:3551-3559 "The many examples from well known clinical trials are clearly one of the strengths of this book. It is also fascinating to share the author's experience with the FDA where he attended many meetings of Advisory Committees."Biometrics, December 2005 "According to the preface, this book is written for clinical investigators and research groups within the pharmaceutical industry, medical students and regulators. ... I admire the eloquency of the author. ... The author does a remarkable job ... . Without any doubt, the book is a valuable source of ideas for the intended audience. For statisticians it is an interesting source of experimental setups, that are actually used in practice and that consequently are worth while to be studied." (dr H. W. M. Hendriks, Kwantitatieve Methoden, Issue 72B41, 2005) "The book is entertaining and informative, sufficiently informal to recruit and retain the intended non-statisticalreadership, but sufficiently formal to detail methods. The author effectively sets up each issue with examples and conceptual discussion, grounding all in realistic examples." (T. A. Louis, Short Book Reviews, Vol. 24 (2), 2004) "Here in this book is a special situation for clinical trials in which the investigator must do statistical analyses for a number of different response measurements. ... The author felt that the clinical investigators needed a book that they could understand. This book is his effort to reach that audience. ... I like the book’s organization. ... I enjoyed leafing through this book and would certainly enjoy having the opportunity to sit down and read it." (Eric R. Ziegel, Technometrics, Vol. 46 (3), August, 2004) "This book is written primarily for clinical researchers who are interested in designing and analysing clinical trials. It concentrates on elucidating problems arising from multiple analyses in clinical trials ... . In general, the book is well written and easy to follow. ... Although this book is written for clinical investigators, I find it a useful reference book for statisticians in the pharmaceutical industry ... . Furthermore, senior statisticians may find the non-technical discussions and practical examples useful." (Shuying Yang, Pharmaceutical Statistics, Issue 3, 2004) "Without any doubt, the book is a valuable source of ideas for the intendend audience. For statisticians, it is an interesting source of experimental setups, that are actually used in practice and that consequently are worthwhile to be studied." (Dr. H.W.M. Hendriks, Kwantitatieve Methoden)

Multiple Testing Problems In Pharmaceutical Statistics

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Author : Alex Dmitrienko
language : en
Publisher: CRC Press
Release Date : 2009-12-08

Multiple Testing Problems In Pharmaceutical Statistics written by Alex Dmitrienko and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-08 with Mathematics categories.

Useful Statistical Approaches for Addressing Multiplicity Issues Includes practical examples from recent trials Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple comparison research with an emphasis on pharmaceutical applications. In each chapter, the expert contributors describe important multiplicity problems encountered in pre-clinical and clinical trial settings. The book begins with a broad introduction from a regulatory perspective to different types of multiplicity problems that commonly arise in confirmatory controlled clinical trials, before giving an overview of the concepts, principles, and procedures of multiple testing. It then presents statistical methods for analyzing clinical dose response studies that compare several dose levels with a control as well as statistical methods for analyzing multiple endpoints in clinical trials. After covering gatekeeping procedures for testing hierarchically ordered hypotheses, the book discusses statistical approaches for the design and analysis of adaptive designs and related confirmatory hypothesis testing problems. The final chapter focuses on the design of pharmacogenomic studies based on established statistical principles. It also describes the analysis of data collected in these studies, taking into account the numerous multiplicity issues that occur. This volume explains how to solve critical issues in multiple testing encountered in pre-clinical and clinical trial applications. It presents the necessary statistical methodology, along with examples and software code to show how to use the methods in practice.

Sharing Clinical Trial Data

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Author : Institute of Medicine
language : en
Publisher: National Academies Press
Release Date : 2015-04-20

Sharing Clinical Trial Data written by Institute of Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-20 with Medical categories.

Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.

Biomarker Analysis In Clinical Trials With R

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Author : Nusrat Rabbee
language : en
Publisher: CRC Press
Release Date : 2020-03-11

Biomarker Analysis In Clinical Trials With R written by Nusrat Rabbee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-11 with Mathematics categories.

The world is awash in data. This volume of data will continue to increase. In the pharmaceutical industry, much of this data explosion has happened around biomarker data. Great statisticians are needed to derive understanding from these data. This book will guide you as you begin the journey into communicating, understanding and synthesizing biomarker data. -From the Foreword, Jared Christensen, Vice President, Biostatistics Early Clinical Development, Pfizer, Inc. Biomarker Analysis in Clinical Trials with R offers practical guidance to statisticians in the pharmaceutical industry on how to incorporate biomarker data analysis in clinical trial studies. The book discusses the appropriate statistical methods for evaluating pharmacodynamic, predictive and surrogate biomarkers for delivering increased value in the drug development process. The topic of combining multiple biomarkers to predict drug response using machine learning is covered. Featuring copious reproducible code and examples in R, the book helps students, researchers and biostatisticians get started in tackling the hard problems of designing and analyzing trials with biomarkers. Features: Analysis of pharmacodynamic biomarkers for lending evidence target modulation. Design and analysis of trials with a predictive biomarker. Framework for analyzing surrogate biomarkers. Methods for combining multiple biomarkers to predict treatment response. Offers a biomarker statistical analysis plan. R code, data and models are given for each part: including regression models for survival and longitudinal data, as well as statistical learning models, such as graphical models and penalized regression models.

Multiple Analyses In Clinical Trials

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Author : Lemuel A. Moyé
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-07-30

Concentrating on the rationale for the analyses, the difficulties posed by their interpretation, easily understood solutions, and useful problem sets, this book will help clinical investigators understand multiple analysis procedures and key issues. It is written for advanced medical students, clinical investigators at all levels, research groups within the pharmaceutical industry, regulators at the local, state, and federal level, and biostatisticians.

Statistical Design Monitoring And Analysis Of Clinical Trials

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Author : Weichung Joe Shih
language : en
Publisher: CRC Press
Release Date : 2021-10-25

Statistical Design Monitoring And Analysis Of Clinical Trials written by Weichung Joe Shih and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-25 with Medical categories.

Statistical Design, Monitoring, and Analysis of Clinical Trials, Second Edition concentrates on the biostatistics component of clinical trials. This new edition is updated throughout and includes five new chapters. Developed from the authors’ courses taught to public health and medical students, residents, and fellows during the past 20 years, the text shows how biostatistics in clinical trials is an integration of many fundamental scientific principles and statistical methods. The book begins with ethical and safety principles, core trial design concepts, the principles and methods of sample size and power calculation, and analysis of covariance and stratified analysis. It then focuses on sequential designs and methods for two-stage Phase II cancer trials to Phase III group sequential trials, covering monitoring safety, futility, and efficacy. The authors also discuss the development of sample size reestimation and adaptive group sequential procedures, phase 2/3 seamless design and trials with predictive biomarkers, exploit multiple testing procedures, and explain the concept of estimand, intercurrent events, and different missing data processes, and describe how to analyze incomplete data by proper multiple imputations. This text reflects the academic research, commercial development, and public health aspects of clinical trials. It gives students and practitioners a multidisciplinary understanding of the concepts and techniques involved in designing, monitoring, and analyzing various types of trials. The book’s balanced set of homework assignments and in-class exercises are appropriate for students and researchers in (bio)statistics, epidemiology, medicine, pharmacy, and public health.

Design And Analysis Of Clinical Trials With Time To Event Endpoints

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Author : Karl E. Peace
language : en
Publisher: CRC Press
Release Date : 2009-04-23

Design And Analysis Of Clinical Trials With Time To Event Endpoints written by Karl E. Peace and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-23 with Mathematics categories.

Using time-to-event analysis methodology requires careful definition of the event, censored observation, provision of adequate follow-up, number of events, and independence or "noninformativeness" of the censoring mechanisms relative to the event. Design and Analysis of Clinical Trials with Time-to-Event Endpoints provides a thorough presentation o

Analysis Of Clinical Trials Using Sas

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Author : Alex Dmitrienko
language : en
Publisher: SAS Institute
Release Date : 2017-07-17

Analysis Of Clinical Trials Using Sas written by Alex Dmitrienko and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-17 with Computers categories.

Analysis of Clinical Trials Using SAS®: A Practical Guide, Second Edition bridges the gap between modern statistical methodology and real-world clinical trial applications. Tutorial material and step-by-step instructions illustrated with examples from actual trials serve to define relevant statistical approaches, describe their clinical trial applications, and implement the approaches rapidly and efficiently using the power of SAS. Topics reflect the International Conference on Harmonization (ICH) guidelines for the pharmaceutical industry and address important statistical problems encountered in clinical trials. Commonly used methods are covered, including dose-escalation and dose-finding methods that are applied in Phase I and Phase II clinical trials, as well as important trial designs and analysis strategies that are employed in Phase II and Phase III clinical trials, such as multiplicity adjustment, data monitoring, and methods for handling incomplete data. This book also features recommendations from clinical trial experts and a discussion of relevant regulatory guidelines. This new edition includes more examples and case studies, new approaches for addressing statistical problems, and the following new technological updates: SAS procedures used in group sequential trials (PROC SEQDESIGN and PROC SEQTEST) SAS procedures used in repeated measures analysis (PROC GLIMMIX and PROC GEE) macros for implementing a broad range of randomization-based methods in clinical trials, performing complex multiplicity adjustments, and investigating the design and analysis of early phase trials (Phase I dose-escalation trials and Phase II dose-finding trials) Clinical statisticians, research scientists, and graduate students in biostatistics will greatly benefit from the decades of clinical research experience and the ready-to-use SAS macros compiled in this book.

Statistical Design Monitoring And Analysis Of Clinical Trials

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Author : Weichung Joe Shih
language : en
Publisher: CRC Press
Release Date : 2021-10-26

Statistical Design, Monitoring, and Analysis of Clinical Trials, Second Edition concentrates on the biostatistics component of clinical trials. This new edition is updated throughout and includes five new chapters. Developed from the authors' courses taught to public health and medical students, residents, and fellows during the past 20 years, the text shows how biostatistics in clinical trials is an integration of many fundamental scientific principles and statistical methods. The book begins with ethical and safety principles, core trial design concepts, the principles and methods of sample size and power calculation, and analysis of covariance and stratified analysis. It then focuses on sequential designs and methods for two-stage Phase II cancer trials to Phase III group sequential trials, covering monitoring safety, futility, and efficacy. The authors also discuss the development of sample size reestimation and adaptive group sequential procedures, phase 2/3 seamless design and trials with predictive biomarkers, exploit multiple testing procedures, and explain the concept of estimand, intercurrent events, and different missing data processes, and describe how to analyze incomplete data by proper multiple imputations. This text reflects the academic research, commercial development, and public health aspects of clinical trials. It gives students and practitioners a multidisciplinary understanding of the concepts and techniques involved in designing, monitoring, and analyzing various types of trials. The book's balanced set of homework assignments and in-class exercises are appropriate for students and researchers in (bio)statistics, epidemiology, medicine, pharmacy, and public health.

Clinical Trial Data Analysis Using R And Sas

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Author : Ding-Geng (Din) Chen
language : en
Publisher: CRC Press
Release Date : 2017-06-01

Clinical Trial Data Analysis Using R And Sas written by Ding-Geng (Din) Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-01 with Mathematics categories.

Review of the First Edition "The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it ...The example-based approach is easy to follow and makes the book a very helpful desktop reference for many biostatistics methods."—Journal of Statistical Software Clinical Trial Data Analysis Using R and SAS, Second Edition provides a thorough presentation of biostatistical analyses of clinical trial data with step-by-step implementations using R and SAS. The book’s practical, detailed approach draws on the authors’ 30 years’ experience in biostatistical research and clinical development. The authors develop step-by-step analysis code using appropriate R packages and functions and SAS PROCS, which enables readers to gain an understanding of the analysis methods and R and SAS implementation so that they can use these two popular software packages to analyze their own clinical trial data. What’s New in the Second Edition Adds SAS programs along with the R programs for clinical trial data analysis. Updates all the statistical analysis with updated R packages. Includes correlated data analysis with multivariate analysis of variance. Applies R and SAS to clinical trial data from hypertension, duodenal ulcer, beta blockers, familial andenomatous polyposis, and breast cancer trials. Covers the biostatistical aspects of various clinical trials, including treatment comparisons, time-to-event endpoints, longitudinal clinical trials, and bioequivalence trials.

Multiple Analyses In Clinical Trials

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