Article
Possibilities to improve sample size recalculation rules
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Published: | September 6, 2019 |
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Outline
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Introduction: Adaptive group sequential study designs can overcome planning uncertainties regarding parameter estimations for sample size calculations. At interim analyses, the underlying effect size is tested for significance and the trial is either stopped or continued. In the latter case, the sample size can be adapted. A variety of such sample size recalculation rules exists (e.g. [1], [2]). However, general points of criticism are a high variability in sample size or that the target power is not met (e.g. [3], [4]).
Methods: For a possible performance improvement, we discuss several innovative elements: First, we consider continuity correction methods to reduce the impact of steps in the recalculation function. Second, resampling arguments are explored to address the underlying randomness of the interim result. We simulated different sample size recalculation scenarios for a two-stage adaptive group sequential study design and a normally distributed outcome, and evaluated them by a conditional performance score in terms of sample size and conditional power.
Results: Depending on the underlying parameters, several considered scenarios show a relevant performance improvement. The proposed methods are easy to apply and can be combined with established recalculation scenarios.
Discussion: We present new elements to potentially improve the performance of established sample size recalculation rules in adaptive group sequential two-stage designs.
The work is supported by the German Research Foundation (grant RA 234714-1).
The authors declare that an ethics committee vote is not required.
References
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