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Interpreting a Bayesian Phase II Futility Clinical Trial (309874)
Jonathan Beall, Medical University of South Carolina*Christy Cassarly, Medical University of South Carolina
Renee' Martin, Medical University of South Carolina
Keywords: 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. While much work has focused on Phase II trials in the frequentist paradigm, a literature search returned no examples of futility trials conducted in the Bayesian setting. In addition to other benefits, Bayesian approaches 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. In this presentation, we provide an illustration of the design and interpretation of a Phase II futility study designed in the Bayesian framework. We focus on the operating characteristics of a motivating trial based on a simulation study, as well as the general interpretation of outcomes and type I and type II errors in this framework.