Abstract

Many “Bayesian" clinical trial designs use posterior credible intervals as tools to define stopping boundaries for inferiority, futility, or superiority. However, the thresholds on posterior credible intervals that trigger termination of a trial are determined by frequentist operating characteristics. This practice can result in substantial overlap between the credible intervals associated with, say, stopping a trial for superiority and stopping a trial for inferiority, which severely limits the interpretation of posterior probability statements. In this article, we use formal Bayesian hypothesis tests to design single-arm phase II clinical trials. By using non-local prior densities to define null and alternative models, we obtain exponential convergence of Bayes factors under both null and alternative models. When compared to other commonly used Bayesian and frequentist designs, we show that our method provides better operating characteristics, uses fewer patients per correct decision, and provides more directly interpretable results. We also demonstrate that designs based on Bayesian hypothesis tests eliminates a potential source of bias often associated with Bayesian trial designs.

Disciplines

Biostatistics | Clinical Trials | Statistical Methodology | Statistical Models | Statistical Theory