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Bayesian Adaptive Methods for Clinical Trials

By Scott M. Berry, Bradley P. Carlin, J. Jack Lee, Peter Muller

CRC Press – 2010 – 323 pages

Series: Chapman & Hall/CRC Biostatistics Series

Purchasing Options:

  • Add to CartHardback: $104.95
    978-1-43-982548-8
    July 18th 2010

Description

Already popular in the analysis of medical device trials, adaptive Bayesian designs are increasingly being used in drug development for a wide variety of diseases and conditions, from Alzheimer’s disease and multiple sclerosis to obesity, diabetes, hepatitis C, and HIV. Written by leading pioneers of Bayesian clinical trial designs, Bayesian Adaptive Methods for Clinical Trials explores the growing role of Bayesian thinking in the rapidly changing world of clinical trial analysis.

The book first summarizes the current state of clinical trial design and analysis and introduces the main ideas and potential benefits of a Bayesian alternative. It then gives an overview of basic Bayesian methodological and computational tools needed for Bayesian clinical trials. With a focus on Bayesian designs that achieve good power and Type I error, the next chapters present Bayesian tools useful in early (Phase I) and middle (Phase II) clinical trials as well as two recent Bayesian adaptive Phase II studies: the BATTLE and ISPY-2 trials. In the following chapter on late (Phase III) studies, the authors emphasize modern adaptive methods and seamless Phase II–III trials for maximizing information usage and minimizing trial duration. They also describe a case study of a recently approved medical device to treat atrial fibrillation. The concluding chapter covers key special topics, such as the proper use of historical data, equivalence studies, and subgroup analysis.

For readers involved in clinical trials research, this book significantly updates and expands their statistical toolkits. The authors provide many detailed examples drawing on real data sets. The R and WinBUGS codes used throughout are available on supporting websites.

Scott Berry talks about the book on the CRC Press YouTube Channel.

Reviews

… researchers/statisticians who work in oncology clinical trials would especially benefit from this book. Having said that, much of the book should be accessible to nonstatistician readers with interest/involvement in clinical trials across different disease areas, while even Bayesian medical statistician readers should find the book to be a helpful resource. The authors, while clearly advocating the use of Bayesian approaches, nevertheless take a very pragmatic approach to the issue. They argue for Bayesian methods that demonstrate good frequentist properties and that are practical to use. This is a refreshing change from some other books and papers that also advocate Bayesian methods, but which while theoretically interesting, are difficult to implement in practice. In summary, I found this book to be well written and interesting. It is very timely given the interest in adaptive designs, and should be a useful resource for statisticians and nonstatisticians alike interested in adaptive clinical trials from a Bayesian perspective.

Biometrics, 67, September 2011

This is the first serious text on adaptive designs using the Bayesian approach. … This is the right book to get if you are interested in Bayesian methods for adaptive designs.

—Michael R. Chernick, Technometrics, August 2011

… a rich introduction to Bayesian clinical trial design in general. It is written in an extremely readable style and is furnished with numerous examples and a great deal of helpful supplementary code. … This work provides a good overall look at the Bayesian approach to clinical trials. It covers the theoretical framework, provides software for the many excellent examples, and even delves into the practical regulatory issues that arise with the use of the designs. The book would be a worthy addition to the practicing statistician’s library.

Journal of Statistical Software, November 2010, Volume 37

This fine book represents the most recent and exciting developments in this area, and gives ample justification for the power and elegance of Bayesian trial design and analysis. … This book, based on the many years of cumulative experience of the authors, manages to deal with [ideological, bureaucratic, practical and pragmatic] difficulties. Adaptive studies are a perfect application for a Bayesian approach, and I am confident that this book will be a major contribution to the science and practice of clinical trials.

—From the Foreword by David J. Spiegelhalter, MRC Biostatistics Unit, University of Cambridge, UK

Contents

Statistical Approaches for Clinical Trials

Introduction

Comparisons between Bayesian and frequentist approaches

Adaptivity in clinical trials

Features and use of the Bayesian adaptive approach

Basics of Bayesian Inference

Introduction to Bayes’ theorem

Bayesian inference

Bayesian computation

Hierarchical modeling and metaanalysis

Principles of Bayesian clinical trial design

Appendix: R Macros

Phase I Studies

Rule-based designs for determining the MTD

Model-based designs for determining the MTD

Efficacy versus toxicity

Combination therapy

Appendix: R Macros

Phase II Studies

Standard designs

Predictive probability

Sequential stopping

Adaptive randomization and dose allocation

Dose ranging and optimal biologic dosing

Hierarchical models for Phase II designs

Decision theoretic designs

Case studies: BATTLE and ISPY-2

Appendix: R Macros

Phase III Studies

Introduction to confirmatory studies

Bayesian adaptive confirmatory trials

Arm dropping

Modeling and prediction

Prior distributions and the paradigm clash

Phase III cancer trials

Phase II/III seamless trials

Case study: Ablation device to treat atrial fibrillation

Appendix: R Macros

Special Topics

Incorporating historical data

Equivalence studies

Multiplicity

Subgroup analysis

Appendix: R Macros

References

Author Index

Subject Index

Author Bio

Scott M. Berry is the President and Senior Statistical Scientist at Berry Consultants, a statistical consulting group specializing in adaptive clinical trial design in pharmaceutical and medical device research and development.

Bradley P. Carlin is Mayo Professor in Public Health and Head of the Division of Biostatistics at the University of Minnesota.

J. Jack Lee is Professor of Biostatistics at the University of Texas M.D. Anderson Cancer Center.

Peter Müller is a Robert R. Herring Distinguished Professor in Clinical Research in the Department of Biostatistics at the University of Texas M.D. Anderson Cancer Center.

Name: Bayesian Adaptive Methods for Clinical Trials (Hardback)CRC Press 
Description: By Scott M. Berry, Bradley P. Carlin, J. Jack Lee, Peter Muller. Already popular in the analysis of medical device trials, adaptive Bayesian designs are increasingly being used in drug development for a wide variety of diseases and conditions, from Alzheimer’s disease and multiple sclerosis to obesity,...
Categories: Clinical Trials - Pharmaceutical Science, Statistical Theory & Methods, Statistics for the Biological Sciences