Abstract
ABSTRACTFutility analyses provide a mechanism to stop a trial early because of low likelihood to achieve its efficacy objective. They are usually motivated by ethical and economic purposes, so that stopping a trial with poor efficacy could save patients and resources for other promising trials. There are various methods to address futility analyses in the literature but most focus on equally spaced interim looks. We consider a constrained optimization framework where the timing and the futility boundary are decided jointly to balance the risks between stopping trials which should continue, and continuing trials which should stop. The average sample size is used as a key parameter, which is evaluated under different degrees of power loss. Alternative objective functions and constraints are compared to assess the operating characteristics of the optimal futility scheme. Numerical results for single and multiple futility looks are provided. Supplementary materials for this article are available online.
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