Design and Analysis of N-of-1 Trials that Incorporate Sequential Monitoring

Department of Epidemiology Seminar Series

Speaker:
Rebecca Betensky, PhD
Chair of the Department of Biostatistics
Professor of Biostatistics
School of Global Public Health
New York University

Abstract: For many diseases and disorders, such as Alzheimer’s disease, patients demonstrate considerable heterogeneity in their responses to treatment interventions. One treatment may be most effective for some patients, while another may be most effective for others, and neither may be effective for another subset of patients. This potentially renders the conventional parallel group design highly inefficient. An attractive alternative is the N-of-1 design, also called the multi-crossover randomized controlled trial. In this design, each participant services as their own control in a series of randomized blocks of treatment assignments. We propose novel designs for both the single-person and multi-person N-of-1 trials that employ sequential monitoring. In particular, we allow for early stopping for a single participant as soon as there is sufficient evidence of a preferred treatment for them, and early stopping for the group of participants as soon as there is sufficient evidence of a preferred treatment for the population of patients. We provide sample size calculations and decision rules for terminating the trial early, and illustrate their properties in simulation studies. We apply our proposed methods to a published brain tumor study and to a recently completed pilot trial using methylphenidate in mild cognitive impairment.