Adaptive designs for comparative effectiveness research trials

Abstract

Medical and health policy decision-makers require improved design and analysis methods for comparative effectiveness research (CER) trials. In CER trials, there may be limited information to guide initial design choices. In general settings, adaptive designs (ADs) have effectively overcome limits on initial information. However, CER trials have fundamental differences from standard clinical trials including population heterogeneity and a vaguer concept of a “minimum clinically meaningful difference”. The objective of this article is to explore the use of a particular form of ADs for comparing treatments within the CER trial context. To achieve this, the authors review the current state of clinical CER. They also identify areas of CER as particularly strong candidates for application of novel AD and illustrate the potential usefulness of the designs and methods for two group comparisons. The authors found that ADs can stabilize power. Furthermore, the designs ensure adequate power for true effects are at least at clinically significant pre-planned effect size, or when variability is larger than expected. The designs allow for sample size savings when the true effect is larger or when variability is smaller than planned. The authors conclude that ADs in CER have great potential to allow trials to successfully and efficiently make important comparisons.