Interpreting a Bayesian phase II futility clinical trial

A resurgence of research into phase II trial design in the mid-2000s led to the use of futility designs in a wide variety of disease areas. Phase II futility studies differ from efficacy studies in that their null hypothesis is that treatment, relative to control, does not meet or exceed the level of benefit required to justify additional study. A rejection of the null hypothesis indicates that the treatment should not proceed to a larger confirmatory trial.

Bayesian approaches to the design of phase II futility clinical trials are presented and allow for the quantification of key probabilities, such as the predictive probability of current trial success or even the predictive probability of a future trial's success.

We provide an illustration of the design and interpretation of a phase II futility study constructed in a Bayesian framework. We focus on the operating characteristics of our motivating trial based on a simulation study, as well as the general interpretation of trial outcomes, type I, and type II errors in this framework.

Phase II futility clinical trials, when designed under in a Bayesian framework, offer an alternative approach to the design of mid-phase studies which provide unique benefits relative to trials designed in a frequentist framework and designs which focus on treatment efficacy.