Bayesian Design of Single-arm Clinical Trials with Binary Endpoints : A Review

Abstract

The aim of single-arm clinical trials of a new drug is to determine whether it has sufficient promising activity to warrant its further development. For the last several years Bayesian statistical methods have been proposed and used. Bayesian approaches are ideal for earlier phase exploratory trials or proof-of-concept studies as they take into account information that accrues during a trial. Posterior and predictive probabilities are then updated and so become more accurate as the trial progresses. If the relevant external information is available, the decision will be made with a smaller sample size. The goal of this paper is to provide a review for statisticians who use Bayesian methods for the first time or investigators who have some statistical background. In addition, a clinical trial is presented as a real example to illustrate how to conduct a Bayesian approach for single-arm clinical trials with binary endpoints.