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Type of bind: Hardcover
Dewey Decimal Number: 610.74
EAN num: 9781584887768
ISBN number: 1584887761
Label: Chapman & Hall/CRC
Manufacturer: Chapman & Hall/CRC
Quantity: 1
Page Count: 296
Printing Date: November 16, 2006
Publishing house: Chapman & Hall/CRC
Sale Popularity Level: 282671
Studio: Chapman & Hall/CRC
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Although adaptive design methods are flexible and useful in clinical research, little or no regulatory guidelines are available. One of the very 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 discusion 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.
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Rated by buyers 
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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.
Rated by buyers 
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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.
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