Statistical Modeling to Adjust for Time Trends in Adaptive Platform Trials Utilizing Non-Concurrent Controls.

ABSTRACT: Utilizing non-concurrent control (NCC) data in the analysis of late-entering arms in platform trials has recently received considerable attention. While incorporating NCC can lead to increased power and lower sample sizes, it might introduce bias to the effect estimators if temporal drifts are present. Aiming to mitigate this potential bias, we propose various frequentist model-based approaches that leverage the NCC, while adjusting for time. One of the currently available models incorporates time as a categorical fixed effect, separating the trial duration into periods, defined as time intervals bounded by any arm entering or leaving the platform. In this work, we propose two extensions of this model. First, we consider an alternative definition of time by dividing the trial into fixed-le

SUBMITTER: Krotka P 

PROVIDER: S-EPMC12150008 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature