Designing fecal microbiota transplant trials that account for differencesin donor stool efficacy

Abstract

1Fecal microbiota transplantation (FMT) is a highly effective intervention for patients suffering from recurrent Clostridium difficile, a common hospital-acquired infection. FMTs success as a therapy for C. difficile has inspired interest in performing clinical trials that experiment with FMT as a therapy for other conditions like inflammatory bowel disease, obesity, diabetes, and Parkinsons 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 examined the optimal Bayesian response-adaptive strategy for allocating patients to donors and formulated a computationally-tractable myopic heuristic. This heuristic 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 produce efficacious stool. 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 stool efficacy reduced the predicted statistical power to ~9%. For these simulations, using the heuristic 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.