SCI-TECHnetBASE: Group Sequential and Adaptive Methods for Clinical Trials, Second Edition (Interdisciplinary Statistics)

In clinical trials, monitoring accumulating data at regular intervals is essential for balancing ethical and financial considerations against scientific rigor. This comprehensive second edition reflects the remarkable evolution in adaptive clinical trial methodology over the past two decades. Since publication of the first edition, these approaches have transformed from theoretical concepts to widely accepted practices, now endorsed by regulatory authorities, including formal FDA guidance.

Features

• Eleven entirely new chapters, including optimal design construction, delayed "pipeline" data accommodation, and multiple comparison procedures
• Eight dedicated chapters on adaptive methods including sample size re-assessment, seamless Phase II/III trials, multi-arm multi-stage trials, and enrichment designs
• Exact methods for binary and Poisson data with applications to vaccine trials
• Expanded discussion of binding versus non-binding futility boundaries for enhanced decision-making
• A chapter with a thoroughly updated review of Bayesian approaches to sequential trial design and analysis
• Incorporates response-adaptive treatment assignment in group sequential designs
• Practical computational methods and software guidance for implementing the techniques

This definitive resource serves statisticians, clinical researchers, pharmaceutical scientists, and regulatory professionals involved in clinical trial design and analysis. The text balances theoretical foundations with practical implementation guidance, making it invaluable for both experienced practitioners and those new to adaptive trial methodology. With twice the content of the first edition, Group Sequential and Adaptive Methods for Clinical Trials, Second Edition provides the comprehensive understanding needed to design more efficient, ethical, and scientifically rigorous clinical trials, ultimately accelerating the delivery of effective treatments to patients.

Christopher Jennison is Professor of Statistics in the Department of Mathematical Sciences, University of Bath, UK. He has worked on the analysis of clinical trials at the Dana-Farber Cancer Institute, Boston and collaborated with medical researchers in areas such as cancer research, cardiology, gynaecology, and complementary medicine.

Bruce Turnbull is Emeritus Professor of Statistics in the School of Operations Research & Industrial Engineering and in the Department of Statistical Science, Cornell University, USA. He has a long experience of designing, monitoring, and analyzing clinical trials and has served on the Data Safety Monitoring Boards for international, multi-center trials for the treatment or prevention of cancer, heart disease and AIDS. He has also served as a consultant to pharmaceutical companies and health-related government review panels.