• adaptive design;
  • Bayesian statistics;
  • oncology;
  • treatment selection

This paper discusses the application of an adaptive design for treatment arm selection in an oncology trial, with survival as the primary endpoint and disease progression as a key secondary endpoint. We carried out treatment arm selection at an interim analysis by using Bayesian predictive power combining evidence from the two endpoints. At the final analysis, we carried out a frequentist statistical test of efficacy on the survival endpoint. We investigated several approaches (Bonferroni approach, ‘Dunnett-like’ approach, a conditional error function approach and a combination p-value approach) with respect to their power and the precise conditions under which type I error control is attained. Copyright © 2011 John Wiley & Sons, Ltd.