Abstract 23239: Cost-Effectiveness of Repair versus Replacement for Severe Ischemic Mitral Regurgitation: A Randomized Clinical Trial From the Cardiothoracic Surgical Trials Network

Background: We recently reported no difference in left ventricular end systolic volume index (LVESVI) or survival at 2 years post surgery between patients with severe ischemic MR randomized to mitral valve (MV) repair (n=126) or replacement (n=125). However, MV replacement provided more durable correction of MR, as well as fewer heart failure events and cardiovascular readmissions over time. These events have important clinical and economic implications, requiring a cost-effectiveness analysis to elucidate. Methods: We conducted a cost-effectiveness analysis using patient-level cost and clinical data from the trial, and developed a microsimulation model for projecting readmission rates and mortality events over a 10-year period. Andersen-Gill modelling was used for these projections, accounting for competing risks. We performed bootstrap resampling to assess parameter uncertainty and threshold analyses to test model assumptions. Results: The mean age of the trial cohort was 68±10 years, mean baseline LVESVI was 63.4±26.8, and 2-year mortality was 19.0% for MV repair and 23.2% for MV replacement patients (HR 0.79, 95% CI 0.46-1.35; p=0.39). The clinical outcomes of the model will be expressed in quality-adjusted life years using longitudinally measured SF-6D scores. Cost outcomes will be derived from claims data using cost-to-charge ratios, and include the index hospitalization and all readmissions. Predictive validity was established by developing the microsimulation model in 1-year data and comparing predicted with observed outcomes at 2 years (Figure). Conclusions: The benefits of these procedures, which have upfront risks and costs, extend beyond 2 years. Our cost-effectiveness analysis will delineate the long-term cost-benefit trade-offs between MV repair versus replacement that should inform surgical decision making, and examine how differences in life expectancy and risk profiles of different patient groups affect cost-effectiveness.