Statistical Monitoring of Clinical Trials: A Unified Approach

ISBN-13: 9781441921345 / Angielski / Miękka / 2010 / 268 str.

Michael A. Proschan; K. K. Gordon Lan; Janet Turk Wittes

Opis

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. The so-called B-value approach to monitoring allows us to use, for different types of trials, the same boundaries and the same simple formula for computing conditional power. Although Brownian motion may sound complicated, the authors make the approach easy by starting with a simple example and building on it, one piece at a time, ultimately showing that Brownian motion works for many different types of clinical trials. The book will be very valuable to statisticians involved in clinical trials. The main body of the chapters is accessible to anyone with knowledge of a standard mathematical statistics text. More mathematically advanced readers will find rigorous developments in appendices at the end of chapters. Reading the book will develop insight into not only monitoring, but power, survival analysis, safety, and other statistical issues germane to clinical trials. Michael Proschan, Gordon Lan, and Janet Wittes are elected Fellows of the American Statistical Association. All have spent formative years in the Biostatistics Research Branch of the National Heart, Lung, and Blood Institute (NHLBI/NIH). While there, they were intimately involved in the design and statistical monitoring of large-scale randomized clinical trials, developing methodology to aid in their monitoring. For example, Lan developed, with DeMets, the now widely-used spending function approach to group sequential designs, whose properties were further investigated by Proschan. The B-value approach used in the book was introduced in a very influential paper by Lan and Wittes. The statistical theory behind conditional power was developed by Lan, along with Simon and Halperin, and was the cornerstone for the conditional error approach to adaptive clinical trials introduced by Proschan and Hunsberger. All three authors have expertise in adaptive methodology for clinical trials. Michael Proschan is a Mathematical Statistician at the National Institutes of Health; Gordon Lan is Senior Director of Biometrics at Johnson & Johnson Pharmaceutical Research and Development, L.L.C.; Janet Wittes is President of Statistics Collaborative, a statistical consulting company she founded in 1990.

Recenzje

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)

Spis treści

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.

Blurb

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. The so-called B-value approach to monitoring allows us to use, for different types of trials, the same boundaries and the same simple formula for computing conditional power. Although Brownian motion may sound complicated, the authors make the approach easy by starting with a simple example and building on it, one piece at a time, ultimately showing that Brownian motion works for many different types of clinical trials.

The book will be very valuable to statisticians involved in clinical trials. The main body of the chapters is accessible to anyone with knowledge of a standard mathematical statistics text. More mathematically advanced readers will find rigorous developments in appendices at the end of chapters. Reading the book will develop insight into not only monitoring, but power, survival analysis, safety, and other statistical issues germane to clinical trials.

Michael Proschan, Gordon Lan, and Janet Wittes are elected Fellows of the American Statistical Association. All have spent formative years in the Biostatistics Research Branch of the National Heart, Lung, and Blood Institute (NHLBI/NIH). While there, they were intimately involved in the design and statistical monitoring of large-scale randomized clinical trials, developing methodology to aid in their monitoring. For example, Lan developed, with DeMets, the now widely-used spending function approach to group sequential designs, whose properties were further investigated by Proschan. The B-value approach used in the book was introduced in a very influential paper by Lan and Wittes. The statistical theory behind conditional power was developed by Lan, along with Simon and Halperin, and was the cornerstone for the conditional error approach to adaptive clinical trials introduced by Proschan and Hunsberger. All three authors have expertise in adaptive methodology for clinical trials.

Michael Proschan is a Mathematical Statistician at the National Institutes of Health; Gordon Lan is Senior Director of Biometrics at Johnson & Johnson Pharmaceutical Research & Development, L.L.C.; Janet Wittes is President of Statistics Collaborative, a statistical consulting company she founded in 1990.