Berry / Carlin / Lee Bayesian Adaptive Methods for Clinical Trials

Erscheinungsjahr 2010
ISBN: 978-1-4398-2551-8
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 323 Seiten

Reihe: Chapman & Hall/CRC Biostatistics Series

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.

Zielgruppe

Researchers and practitioners in biostatistics, pharmaceutical research, medicine, and epidemiology; graduate students in biostatistics.

Autoren/Hrsg.

Berry, Scott M.

Carlin, Bradley P.

Lee, J. Jack

Muller, Peter

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Biomedizin, Medizinische Forschung, Klinische Studien
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung

Inhaltsverzeichnis

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

Über Autor(innen)

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.