Trial monitoring via a futility criterion for interim results on a count data endpoint and a continuous endpoint.

Abstract Assumptions made at design stage regarding the true treatment effect, background event rate and other factors may not always hold. Thus, long-term and large-scale studies may be designed with an interim analysis in order that the trials may be stopped early due to futility to save resource. There are many considerations of trial conducts for this type of trials. In this paper, we use a mock study to illustrate systematically the thinking and procedures for trial monitoring with a futility criterion for the interim results on a count data endpoint and a continuous endpoint. We focus on the discussions of blinded trial monitoring, the probability of meeting the futility criterion, conditional power/probability of success, Bayesian inference, potential delayed treatment effect and subgroup analysis. The experience should be applicable to future studies with similar features.