Publication Description
Clinical patient management is dynamic. It is not based on a single decision but on a sequence of decisions, with adjustments of therapy overtime, where adjustment are personalized to individual patients. However, strategies allowing for such adjustments are infrequently studied. In the treatment of serious bacterial infections, there are two therapeutic decision points: empirical therapy when the patient is first seen by the clinician, and definitive therapy when drug susceptibility results are available to help guide therapeutic choices. COMparing Personalized Antibiotic StrategieS (COMPASS) is a trial design that compares strategies consistent with clinical practice rather than specific treatments. A strategy is a decision-rule guiding treatments of bacterial infections both at the empirical and at the definitive stages. Sequential multiple assignment randomized (SMART) COMPASS allows evaluation of strategies when there are multiple definitive therapy choices. SMART COMPASS is a pragmatic design, mirroring antibiotic treatment decision-making as they unfold in clinical practice and addressing the most relevant question for treating patients: identification of the patient-management strategy that optimizes ultimate patient outcomes. Complex statistical challenges are encountered during the design of SMART COMPASS including how to: appropriately estimate effects and associated standard errors within the context of sequential randomization, identify the best of several strategies while controlling trial-wise error, and calculate sample size and power when trying to identify the optimal strategy. Design considerations for SMART COMPASS are discussed.