Bayesian decision theoretic two‐stage design in phase II clinical trials with survival endpoint

In this paper, we consider two‐stage designs with failure‐time endpoints in single‐arm phase II trials. We propose designs in which stopping rules are constructed by comparing the Bayes risk of stopping at stage I with the expected Bayes risk of continuing to stage II using both the observed data in stage I and the predicted survival data in stage II. Terminal decision rules are constructed by comparing the posterior expected loss of a rejection decision versus an acceptance decision. Simple threshold loss functions are applied to time‐to‐event data modeled either parametrically or nonparametrically, and the cost parameters in the loss structure are calibrated to obtain desired type I error and power. We ran simulation studies to evaluate design properties including types I and II errors, probability of early stopping, expected sample size, and expected trial duration and compared them with the Simon two‐stage designs and a design, which is an extension of the Simon's designs with time‐to‐event endpoints. An example based on a recently conducted phase II sarcoma trial illustrates the method. Copyright © 2012 John Wiley & Sons, Ltd.