Product Description

Although adaptive design methods are flexible and useful in clinical research, little or no regulatory guidelines are available. One of the first books on the topic, Adaptive Design Methods in Clinical Trials presents the principles and methodologies in adaptive design and analysis that pertain to adaptations made to trial or statistical procedures that are based on accrued data of ongoing clinical trials. The book also offers a well-balanced summary of current regulatory perspectives and recently developed statistical methods in this area.

After an introduction to basic concepts and statistical considerations of adaptive design methods, the book questions the impact on target patient populations as the result of protocol amendments and discusses the generalization of statistical inference. The authors also present various adaptive design methods, including where hypotheses are modified during the conduct of clinical trials, for dose selection, and commonly used adaptive group sequential design methods in clinical trials. Following a discussion of blind procedures for sample size re-estimation, the book describes statistical tests for seamless phase II/III adaptive designs and statistical inference for switching adaptively from one treatment to another. The book concludes with computer simulations and various case studies of clinical trials.

By providing theoretical and computer simulation results, method comparisons, and practical guidelines for choosing an optimal design, Adaptive Design Methods in Clinical Trials fills the need for a unified, comprehensive, and updated resource in the clinical research and development of adaptive design and analysis.

Product Details

• Amazon Sales Rank: #738396 in Books
• Published on: 2006-11-16
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 296 pages

Review
The book covers a vast area. To my knowledge this book is the first attempt to provide a concise description of various methodologies in a highly dynamic area. The authors deserve to be praised for bringing this huge range of approaches, including very recent trends, together in one book … .
—Tim Friede,  University of Warwick, Biometrics, March 2008

…This book is one of the first of its kind to be released solely dealing with adaptive designs in clinical trials. … a useful reference for those who have a mathematical background and wish to understand some of the adaptive design methodologies. …With the ever-increasing need for adaptive trials, we could see this book having a large influence …
—Pharmaceutical Statistics, 2008

…a useful reference source for anyone interested in advancing innovative trial designs and wishing to incorporate adaptations, modifications, and changes to the drug, device, and biological developmental processes.
—C.M. O’Brien, International Statistical Review, Vol. 75, No. 2, 2007

…uses a broad definition of adaptive design methods… .This breadth of coverage is to be commended and makes the book a useful reference and overview for anyone who is starting to explore this area … the book is worth reading.
—Angela Wade, University College London, UK

Customer Reviews

Great contribution to pharmaceutical industry
I meet the second author, Mark Chang, at a conference on adaptive designs. I work as a professional statistician in the pharmaceutical industry. For the past several years, at least ten, these ideas have been the topic of research and it is being investigated as a possible way to speed up drug development and its development is being encouraged by the FDA. There has not been a formal statistical text covering the existing theory and its application to clinical trials. Consequently, when we knew this was coming out we preordered it and have been studying it since it came out last November.

The book has lived up to expectations. Adaptive designs are very similar to group sequential designs in that they have planned times to make preliminary assessment of the trial data and then decide whether or not to continue the trial or modify the design. Adaptive designs can be more flexible than their group sequential counterparts. They even can allow changes to the protocol as long as the criteria for making such changes are mapped out in advance of the trial.

These methods have been controversial in the past and simulation studies are often required to determine their properties. But there has been enough development now that some designs are being applied in real trials. In fact we are considering a two stage adaptive design similar to the ones described in this text (except applied to bioequivalence).

Later this year Mark Chang is coming out with an applied text that include SAS macros to aid in the implementation of the methods. A preview of the manuscript was displayed at an adaptive trials conference that I attended recently. I can enthusiastically recommend that one even more than this one! However, any biostatistician working on clinical trials should have this book on his or her bookshelf.

This book is a "beta" version
This book's best features are its bibliography (about 240 entries) and its broad survey and taxonomy of adaptive methods. Its publication represents an important step in popularizing adaptive trials and, thus, streamlining drug/device/biologic development pipelines.

The book is, however, filled with inaccuracies on several levels: incorrect grammar and equation references, undefined symbols, a reference to a non-existent appendix, unclear language (e.g., what is the "statistical strength for rejecting Ho" on Page 150?), mathematical typos [e.g., P(x|y,theta) rather than P(y|theta) in the integrand for the posterior predictive probability distribution P(y|x)], and misapplications of statistical philosophy (e.g., using Neyman-Pearson hypothesis testing for statistical inference, identifying the p-value as a post-hoc type I error rate). In the sample I took of about 1/3 of the pages, about 120 errors occur. The book should be considered only a pre-publication "beta" version. Any second edition should receive much more attention to detail.

A statistician or clinical scientist planning a potentially adaptive trial could use this book to learn about some of the aspects of a trial that can be made adaptive. The book could also help him/her to assess the assumptions and mathematical complexity of methods under consideration. However, when it comes to actually performing an analysis, one would want to use the bibliography to obtain the relevant articles and books, perhaps together with Chang's "Adaptive Design Theory and Implementation Using SAS and R" (Chapman & Hall/CRC Biostatistics).

Overall, this book disappointed me. The authors should have had several more collaborators and copyeditors check their work.