Statistical Monitoring of Clinical Trials: A Unified Approach (Statistics for

Statistical Monitoring of Clinical Trials
$ P* l* M0 x3 S4 O! Z4 o$ L5 W临床试验的统计学

Randomized clinical trials are the gold standard for establishing many clinical practice guidelines and are central to evidence based medicine. Obtaining the best evidence through clinical trials must be done within the boundaries of rigorous science and ethical principles. One fundamental principle is that trials should not continue longer than necessary to reach their objectives. Therefore, trials must be monitored for recruitment progress, quality of data, adherence to patient care or prevention standards, and early evidence of benefit or harm. Frequently, a group of external experts, independent from the investigators and trial sponsor, is charged with this monitoring responsibility, especially for safety and early benefit. This group is referred to by various names, such as a data monitoring committee or a data and safety monitoring board. This book, through a series of case studies presented by many distinguished clinical trial experts, illustrates the complexity of this monitoring process. The editors provide an overview of the process and a summary of a multitude of the lessons learned from the cases presented. This book should be useful to anyone serving on a data and safety monitoring board, or planning to do so, for colleagues in academia, industry and governmental agencies, and for teaching students in biostatistics, epidemiology, clinical trials and medical ethics. No other text has as extensive a collection of cases which provide insight into the many issues, often conflicting, that must be examined before recommendations to continue or discontinue a trial can be made. While depth in statistical methods is not required, some familiarity with statistical design and analysis issues in clinical trials is helpful. The cases cover trials which were terminated early for convincing evidence of benefit, or for harmful effects. Cases with complex issues are also included. This series of cases should provide broad background information for potential monitoring committee members and better prepare them for the challenges that may exist in the trials for which they are responsible. The three editors have contributed two overview chapters as well as several case studies to go along with cases contributed by a distinguished group of colleagues experienced in the design, monitoring and analysis of clinical trials. Dr. David DeMets is currently Professor and Chair, Department of Biostatistics and Medical Informatics at the University of Wisconsin-Madison. He is past president of the Eastern North American Region (ENAR) of the International Biometric Society, a past member of the Board of Directors of the American Statistical Association and an elected Fellow. He recently received the Robert Gordon Lectureship Award, given by the National Institutes of Health, for significant contributions to the field of clinical trials. Dr. Curt Furberg, is currently Professor (and former Chair) of the Department of Public Health Sciences at Wake Forest University. Previously, he was Head of the Clinical Trials Branch and Associate Director of the Clinical Applications and Prevention Program at the National Heart, Lung, and Blood Institute. Dr. Lawrence Friedman is a former Director of the Division of Epidemiology and Clinical Applications and a former Assistant Director for Ethics and Clinical Research at the National Heart, Lung, and Blood Institute. All three are past presidents of the Society of Clinical Trials. The editors have collaborated previously as coauthors of a text: the Fundamentals of Clinical Trials.
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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
4 y5 N' \6 C! ~0 q/ r"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)
& |" o- G* W4 C"[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)
+ o  Z5 n( B( Y6 k7 w% @' u1 a"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)
. ?8 X- z0 |; ^8 j4 D! f"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 books 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)
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4 }5 K$ {/ P/ I. hProduct Description

8 w& k% p, `- f$ KThe 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.
# b0 ~. s4 d$ T4 H  i% nThe 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.
9 o0 F# [' R# x6 S3 p# h& v$ sMichael 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.
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不应该是那样翻译的吧

i think this book is prepare for the DBA