Design and Analysis of N-Of-1 Trials That Incorporate Sequential Monitoring.

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 serves 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 N-of-1 studies of brain tumor excisions and of methylphenidate in mild cognitive impairment.