Product Description

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.

Product Details

• Amazon Sales Rank: #303389 in Books
• Published on: 2007-11-26
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 258 pages

Review

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)

Customer Reviews

just OK
The topics listed in the table of contents of the book are really interesting. On the other hand, the notations used in the book make it so much more difficult to read. For example, the letters chosen for many variables used have no relation at all with their meaning, so that constantly, throughout the book, you need to go back to previous chapters. Also, various statistical results are just used, without any proof or at least hints for proof. Therefore, one needs to read this book while having another graduate stats inference book at hand.

great book by experts in the field
This is one of two excellent books on group sequential methods and adaptive designs. All three authors are ASA Fellows. Wittes and Proschan have worked at the NIH and Proschan formerly worked at the FDA. Gordan Lan has published widely on group sequential methods and has developed software with David deMets that can be downloaded for free from deMets' website at the University of Wisconsin. Lan and deMets developed the theory of alpha spending functions that are commonly used in software such a EaSt (Cytel Corporation) to help determine an appropriate shape to the stopping boundary. Two group sequential methods with markedly different spending functions are the Pocock design anf the O'Brien-Fleming design. I have written a detailed book review for Technometrics, that also compares the book to Jennison and Turnbull's text. Both of these books will be classics. my review will appear in the May 2007 issue of Technometrics.