All Times EDT
Keywords: sequential multiple assignment randomized trial, rare disease, small sample, Bayesian
Sequential, multiple assignment, randomized trial (SMART) designs are often motivated to identify tailored sequences of treatments or dynamic treatment regimens (DTRs) in larger samples. SMARTs employ at least two randomizations in sequence where only some groups may be re-randomized based on response or other characteristics related to previous treatment. We have turned standard SMART designs and analyses on their head, and instead of focusing on DTRs, we apply the design to small samples to obtain more information from a small sample of individuals. This talk will provide an overview of small sample SMART (snSMART) designs and primarily Bayesian methods for analyses. The differences between snSMART and SMART designs will be highlighted and methods to analyze snSMART data will be presented. All of our methods are motivated by the current snSMART ARAMIS which seeks to find an effective treatment for individuals with the rare disease of isolated skin vasculitis, but the methods apply broadly to any disease affecting small numbers of individuals.