A consistency-adjusted strategy for accommodating an underpowered primary endpoint.
A clinical trial might involve more than one clinically important endpoint, each of which can characterize the treatment effect of the experimental drug under investigation. Underlying the concept of using such endpoints interchangeably to establish an efficacy claim, or pooling different endpoints to constitute a composite endpoint, is the assumption that findings from such endpoints are consistent with each other. While such an assumption about consistency of efficacy findings appears to be intuitive, it is seldom considered in the design and analysis literature of clinical trials with multiple endpoints. Failure to account for consistency of efficacy findings of two candidate endpoints to establish efficacy, at the design stage, has led to difficulties in interpreting study findings. This article presents a flexible testing strategy for accommodating findings of an alternative to the designated primary endpoint (or a subgroup) to support an efficacy claim. The method is built on the following two premises: (i) Efficacy findings of the designated primary endpoint, although nonsignificant, need to be supportive of those of the alternative endpoint, and (ii) the significance level allocated for testing the second endpoint is determined adaptively based on the magnitude of the p-value for the designated primary endpoint. The method takes into account the hierarchical ordering of the hypotheses tested and the correlation between the test statistics for the two endpoints to increase the chance of a positive trial. We discuss control of the type I error rate for the proposed test strategy and compare its power with that of other methods. In addition, we consider its application to two clinical trials.
Division of Biometrics IV, OB, OTS, CDER, Food and Drug Administration, Silver Spring, Maryland, USA.
Mohammad F
MF
Huque
Mohamed
M
Alosh
D002986:Clinical Trials as Topic / Q000379:methods / Q000706:statistics & numerical data*; D003661:Decision Support Techniques; D023381:Endpoint Determination / Q000379:methods / Q000706:statistics & numerical data*; D006801:Humans