RT Journal Article SR Electronic T1 Designing fecal microbiota transplant trials that account for differences in donor stool efficacy JF bioRxiv FD Cold Spring Harbor Laboratory SP 065383 DO 10.1101/065383 A1 Scott W. Olesen A1 Thomas Gurry A1 Eric J. Alm YR 2016 UL http://biorxiv.org/content/early/2016/07/25/065383.abstract AB Fecal microbiota transplantation (FMT) is a highly effective intervention for patients suffering from recurrent Clostridium difficile, a common hospital-acquired infection. FMT’s success as a therapy for C. difficile has inspired interest in performing clinical trials that experiment with FMT as a therapy for treating conditions like inflammatory bowel disease, obesity, diabetes, and Parkinson’s disease. Results from clinical trials that use FMT to treat inflammatory bowel disease suggest that, for at least one condition beyond C. difficile, most FMT donors produce stool that is not efficacious. The optimal strategies for identifying and using efficacious donors have not been investigated. We therefore formulated an optimal Bayesian response-adaptive donor selection strategy and a computationally-tractable myopic heuristic. This algorithm computes the probability that a donor is efficacious by updating prior expectations about the efficacy of FMT, the placebo rate, and the fraction of donors that are efficacious. In simulations designed to mimic a recent FMT clinical trial, for which traditional power calculations predict ~100% statistical power, we found that accounting for differences in donor efficacy reduced the predicted statistical power to ~9%. For these simulations, using the Bayesian allocation strategy more than quadrupled the statistical power to ~39%. We use the results of similar simulations to make recommendations about the number of patients, number of donors, and choice of clinical endpoint that clinical trials should use to optimize their ability to detect if FMT is effective for treating a condition.