Titel: Statistical Methods for Monitoring Clinical Trials
Autor/en: Michael A. Proschan, K. K. Gordon Lan, Janet Turk Wittes
A Unified Approach.
'Statistics for Biology and Health'.
1st ed. 2006. Corr. 2nd printing 2007.
26. November 2007 - gebunden - XIV
The approach taken in this book is, to studies monitored over time, what the Central Limit Theorem is to studies with only one analysis. Just as the Central Limit Theorem shows that test statistics involving very different types of clinical trial outcomes are asymptotically normal, this book shows that the joint distribution of the test statistics at different analysis times is asymptotically multivariate normal with the correlation structure of Brownian motion ("the B-value") - irrespective of the test statistic. Thus, this book offers statisticians an accessible, incremental approach to understanding Brownian motion as related to clinical trials.
A General Framework.- Power: Conditional, Unconditional, and Predictive.- Historical Monitoring Boundaries.- Spending Functions.- Practical Survival Monitoring.- Inference Following a Group-Sequential Trial.- Options When Brownian Motion Does Not Hold.- Monitoring for Safety.- Bayesian Monitoring.- Adaptive Sample Size Methods.- Topics Not Covered.- Appendix I: The Logrank and Related Tests.- Appendix II: Group-Sequential Software.
From the reviews:
"The book covers most of the important topics in statistical monitoring of clinical trials, including monitoring boundary, conditional power, inference following a group-sequential trial, and adaptive sample size....[and] is valuable for anyone currently involved with or interested in monitoring clinical trials. (T.C. Bailey for Biotmetrics, Issue 63, September 2007)
"The extensive practical experience of the authors is reflected in the presentation of much of the material. This book wouild provide a valuable source of information for statisticians wishing to learn more about issues and methods for the interim monitoring of clinical trials." S.W. Lagakos for Short Book Reviews of the ISI, December 2006
"In summary, this book is an excellent and thorough advanced textbook on the fundamental concepts and properties of group sequential trials literature. ...[T]his book is highly recommended, since it offers a compendium of interesting, sometimes exciting and astonishing results in this area of statistics." Gernot Wassmer for Journal of Biopharmaceutical Statistics, Issue 6, 2007
"This text by Proschan, Lan, and Wittes is very well written and provides thorough and nearly complete coverage of the latest developments in group sequential methods. ... I highly recommend this book for any statistician and/or practitioner involved in the analysis of clinical trials. ... this is an interesting and well-written book ... ." (Michael R. Chernick, Technometrics, Vol. 49 (2), 2007)
"[This] new book gives an excellent overview of issues related to the design and conduct of sequential clinical trials. Researchers working in this area will find this comprehensive book very useful." (Alex Dmitrienko, Biopharmaceutical Network, June 2007)
"This volume presents a comprehensive manual how to perform (repeated) interim analyses in clinical trials in different testing situations. ... The book presents a very clear and comprehensive overview of multiple kinds of data monitoring and interim analyses in clinical trials. All topics are illustrated with numerous numerical examples or case studies." (Christina Wunder, Zentralblatt MATH, Vol. 1121 (23), 2007)
"This book is a well-written introduction to interim monitoring and statistical analyses of clinical trials. ... This book will be equally useful for graduate students in statistics as well as working statisticians. ... Because of the book's simple style, it will ... also provide clinicians and other nonstatisticians with an overview of the main ideas of interim monitoring and the corresponding statistical methods. ... Overall, this book will be helpful to anyone involved in the statistical monitoring of clinical trials in drug development." (Somesh Chattopadhyay and Thomas Hammerstrom, Journal of the American Statistical Association, Vol. 103 (481), 2008)