Adaptive Design Methods in Clinical Trials: (Chapman & Hall/CRC Biostatistics Series)

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.

Table of Contents:
INTRODUCTION What Is Adaptive Design Regulatory Perspectives Target Patient Population Statistical Inference Practical Issues Aims and Scope of the Book PROTOCOL AMENDMENT Actual Patient Population Estimation of Shift and Scale Parameters Statistical Inference Sample Size Adjustment Statistical Inference with Covariate Adjustment Concluding Remarks ADAPTIVE RANDOMIZATION Conventional Randomization Treatment-Adaptive Randomization Covariate-Adaptive Randomization Response-Adaptive Randomization Issues with Adaptive Randomization Summary ADAPTIVE HYPOTHESES Modifications of Hypotheses Switch from Superiority to Noninferiority Concluding Remarks ADAPTIVE DOSE-ESCALATION TRIALS Introduction CRM in Phase I Oncology Study Hybrid Frequentist-Bayesian Adaptive Design Simulations Concluding Remarks ADAPTIVE GROUP SEQUENTIAL DESIGN Sequential Methods General Approach for Group Sequential Design Early Stopping Boundaries Alpha Spending Function Group Sequential Design Based on Independent P-Values Calculation of Stopping Boundaries Group Sequential Trial Monitoring Conditional Power Practical Issues ADAPTIVE SAMPLE SIZE ADJUSTMENT Sample Size Re-Estimation without Unblinding Data Cui-Hung-Wang's Method Proschan-Hunsberger's Method Muller-Schafer Method Bauer-Köhne Method Generalization of Independent P-Value Approaches Inverse-Normal Method Concluding Remarks ADAPTIVE SEAMLESS PHASE II/III DESIGN Why a Seamless Design Is Efficient Step-wise Test and Adaptive Procedures Contrast Test and Naive P-Value Comparisons of Seamless Design Drop-the-Loser Adaptive Design Summary ADAPTIVE TREATMENT SWITCHING Latent Event Times Proportional Hazard Model with Latent Hazard Rate Mixed Exponential Model Concluding Remarks BAYESIAN APPROACH Basic Concepts of Bayesian Approach Multiple-Stage Design for Single-Arm Trial Bayesian Optimal Adaptive Designs Concluding Remarks CLINICAL TRIAL SIMULATION Simulation Framework Early Phases Development Late Phases Development Software Application Examples Concluding Remarks CASE STUDIES Basic Considerations Adaptive Group Sequential Design Adaptive Dose-Escalation Design Adaptive Seamless Phase II/III Design SUBJECT INDEX BIBLIOGRAPHY