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Abstract:
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This paper considers a framework for inference in adaptive bioequivalence trials with unblinded sample size re-estimation (SSR). If the sample size is small and the variance unknown, as is often the case in bioequivalence trials, using boundaries derived under the assumption of a normally distributed test statistic may lead to type I error inflation. While this problem can be overcome with p-value combination methods, these approaches generally do not directly provide confidence intervals for the geometric mean ratio on the scale of the original pharmacokinetic endpoint. We consider an approach that involves pre-specifying a range of final sample sizes to allow some flexibility in the SSR procedure, yet uses pre-defined constant boundaries based on a "piecewise t-distribution" to derive repeated confidence intervals (RCIs) for the treatment effect. The RCIs have guaranteed coverage, and can be used for inference and clinical interpretation in the same way that conventional two-sided confidence intervals are typically used when applying the two one-sided testing (TOST) procedure.
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