Clinical Trial Design (PDF)

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.