Adaptive Designs for Clinical Trials: Application to Healthcare Epidemiology Research

Abstract

Clinical trials with adaptive designs use data that accumulate during the course of the study to modify study elements in a prespecified manner. The goal is to provide flexibility such that a trial can serve as a definitive test of its primary hypothesis, preferably in a shorter time period, involving fewer human subjects, and at lower cost. Elements that may be modified include the sample size, end points, eligible population, randomization ratio, and interventions. Accumulating data used to drive these modifications include the outcomes, subject enrollment (including factors associated with the outcomes), and information about the application of the interventions. This review discusses the types of adaptive designs for clinical trials, emphasizing their advantages and limitations in comparison with conventional designs, and opportunities for applying these designs to healthcare epidemiology research, including studies of interventions to prevent healthcare-associated infections, combat antimicrobial resistance, and improve antimicrobial stewardship.