Interim Futility Analysis for Longitudinal Data With Adaptive Timing and Error Rate Preservation

ABSTRACT

There are many clinical trials where longitudinal endpoints are used and the primary endpoint is quite often either based on the rate of change or change from baseline at a specific long-term follow-up time point. When such trials are monitored, it is possible that interim futility analyses will be planned such that the trials can be terminated early if the treatment does not induce any benefit to the patients. For such trials, subjects with incomplete follow-up pose challenges in the timing, analysis, and decision making at the interim futility look. We propose an efficient interim futility analysis based on the slope of a linear regression, which incorporates all the data available at the interim analysis. Our approach has the added advantage of providing a data-driven decision on triggering the interim analysis when sufficient information has been collected such that the desired properties for the established futility rule are guaranteed. The construction of interim futility rules and the timing of the interim analysis are discussed and the method is illustrated with an example involving a placebo-controlled comparison of longitudinal proteinuria measurements. Supplementary materials for this article are available online.

Keywords:

• Between subject variability
• Fisher's information
• Inverse variance weighted average
• Linear mixed effect model
• Within-subject variability

Supplementary Materials

The online supplementary materials contain the derivation of the Fisher's Information for Slope of Regression.