Improved Efficiency for Cross-Arm Comparisons via Platform Designs

TL;DR

This paper demonstrates that platform trials can be more statistically efficient than separate two-arm trials for comparing multiple interventions, especially due to shared controls and adaptive non-inferiority testing.

Contribution

It provides theoretical and numerical evidence of platform trials' efficiency advantages and introduces a novel adaptive non-inferiority testing procedure.

Findings

Platform trials achieve equal or better precision with fewer participants.

Sharing controls among interventions enhances statistical efficiency.

Adaptive non-inferiority testing improves power in platform trials.

Abstract

Though platform trials have been touted for their flexibility and streamlined use of trial resources, their statistical efficiency is not well understood. We fill this gap by establishing their greater efficiency for comparing the relative efficacy of multiple interventions over using several separate, two-arm trials, where the relative efficacy of an arbitrary pair of interventions is evaluated by contrasting their relative risks as compared to control. In theoretical and numerical studies, we demonstrate that the inference of such a contrast using data from a platform trial enjoys identical or better precision than using data from separate trials, even when the former enrolls substantially fewer participants. This benefit is attributed to the sharing of controls among interventions under contemporaneous randomization, which is a key feature of platform trials. We further provide a novel procedure for establishing the non-inferiority of a given intervention relative to the most efficacious of the other interventions under evaluation, where this procedure is adaptive in the sense that it need not be \textit{a priori} known which of these other interventions is most efficacious. Our numerical studies show that this testing procedure can attain substantially better power when the data arise from a platform trial rather than multiple separate trials. Our results are illustrated using data from two monoclonal antibody trials for the prevention of HIV.