Treatment Comparisons in Adaptive Platform Trials Adjusting for Temporal Drift

Authors

Beibei Guo
Li Wang
Ying Yuan

Publication Date

1-1-2024

Journal

Statistics in Biopharmaceutical Research

Abstract

An adaptive platform trial (APT) is a multi-arm trial in the context of a single disease where treatment arms are allowed to enter or leave the trial based on some decision rule. If a treatment enters the trial later than the control arm, there exist non-concurrent controls who were not randomized between the two arms under comparison. As APTs typically take long periods of time to conduct, temporal drift may occur, which requires the treatment comparisons to be adjusted for this temporal change. Under the causal inference framework, we propose two approaches for treatment comparisons in APTs that account for temporal drift, both based on propensity score weighting. In particular, to address unmeasured confounders, one approach is doubly robust in the sense that it remains valid so long as either the propensity score model is correctly specified or the time effect model is correctly specified. Simulation study shows that our proposed approaches have desirable operating characteristics with well controlled type I error rates and high power with or without unmeasured confounders.

Keywords

Temporal drift, adaptive platform trial, concurrent controls, non-concurrent controls, propensity score

DOI

10.1080/19466315.2023.2292238

PMID

39184873

PMCID

PMC11343491

PubMedCentral® Posted Date

1-5-2025

PubMedCentral® Full Text Version

Author MSS

Published Open-Access

yes