Contents:

FUNDAMENTALS OF CLINICAL TRIALS

EXERCISES

PHASE II TRIAL DESIGN

OUTCOMES

PHASE III TRIAL DESIGN

PHASE I TRIAL DESIGN

A balanced treatment of the theories, methodologies, and design issues involved in clinical trials using statistical methods

There has been enormous interest and development in Bayesian adaptive designs, especially for early phases of clinical trials. However, for phase III trials, frequentist methods still play a dominant role through controlling type I and type II errors in the hypothesis testing framework. From practical perspectives, Clinical Trial Design: Bayesian and Frequentist Adaptive Methods provides comprehensive coverage of both Bayesian and frequentist approaches to all phases of clinical trial design. Before underpinning various adaptive methods, the book establishes an overview of the fundamentals of clinical trials as well as a comparison of Bayesian and frequentist statistics.

Recognizing that clinical trial design is one of the most important and useful skills in the pharmaceutical industry, this book provides detailed discussions on a variety of statistical designs, their properties, and operating characteristics for phase I, II, and III clinical trials as well as an introduction to phase IV trials. Many practical issues and challenges arising in clinical trials are addressed. Additional topics of coverage include:

Risk and benefit analysis for toxicity and efficacy trade-offs

Bayesian predictive probability trial monitoring

Bayesian adaptive randomization

Late onset toxicity and response

Dose finding in drug combination trials

Targeted therapy designs

The author utilizes cutting-edge clinical trial designs and statistical methods that have been employed at the world's leading medical centers as well as in the pharmaceutical industry. The software used throughout the book is freely available on the book's related website, equipping readers with the necessary tools for designing clinical trials.

Clinical Trial Design is an excellent book for courses on the topic at the graduate level. The book also serves as a valuable reference for statisticians and biostatisticians in the pharmaceutical industry as well as for researchers and practitioners who design, conduct, and monitor clinical trials in their everyday work. Common terms and phrases: adaptive designs adaptive randomization allocation ratio analysis Bayesian beta distribution binary biomarker Biometrics cancer censored clinical trials cohort continual reassessment method denote dose combination dose escalation dose level endpoints enrolled error rate estimator example experimental drug experimental treatment Figure frequentist futility given hypothesis testing interim likelihood function marginal maximum sample monitoring moving-reference multivariate noninferiority trial null hypothesis number of patients number of responses number of subjects optimal p-value parameter phase II trial posterior distribution posterior probability predictive probability prespecified prior distribution procedure random variable randomization probabilities reject respectively response rate sample size scenario selection percentages significance level simulated specified stage standard treatment stopping boundaries subtrials superiority trial target toxicity probability test statistic therapy time-to-event total number total sample toxicity and efficacy treated patients treatment difference treatment effect trial designs two-arm trial two-stage design type I error variance versus