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Abstract:
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Competing risks endpoints arise when patients can fail therapy from several causes. Analyzing these outcomes allows one to assess the direct benefit of treatment on a primary cause of failure in a clinical trial setting. Regression models can be used in clinical trials to adjust for residual imbalances in patient characteristics, improving the power to detect treatment differences. But, none of the competing risks methods currently available for use in group sequential trials adjust for covariates.
We propose a group sequential test for treatment effect that, because it is based on the Fine-Gray regression model, makes adjustment for covariates. Our derivations show that its sequence of test statistics has an asymptotic distribution with an independent increments structure, which allows standard techniques such as O'Brien-Fleming designs and error spending functions to be utilized to meet type I error rate and power specifications. Using a simulation study of randomized group sequential trials, we demonstrate that the proposed method preserves the type I error rate and power at their nominal levels in the presence of influential covariates.
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