Efficiency Perspectives on Adaptive Designs in Stroke Clinical Trials

An adaptive design allows the modifications of various features, such as sample size and treatment assignments, in a clinical study based on the analysis of interim data. The goal is to enhance statistical efficiency by maximizing relevant information obtained from the clinical data. The promise of efficiency, however, comes with a cost, per se, that is seldom made explicit in the literature. This article reviews some commonly used adaptive strategies in early-phase stroke trials and discusses their associated costs. Specifically, we illustrate the trade-offs in several clinical contexts, including dose-finding in the Neuroprotection with Statin Therapy for Acute Recovery Trial (NeuSTART), futility analyses and internal pilot in Phase 2 proof-of-concept trials, and sample size considerations in an imaging-based dose-selection trial. Through these illustrations, we demonstrate the potential tension between the perspectives of an individual investigator and that of the broader community of stakeholders. This understanding is critical to appreciate the limitations, as well as the full promise, of adaptive designs, so that investigators can deploy an appropriate statistical design--be it adaptive or not--in a clinical study.