Evidence-Based Organ Allocation

Background. There is sufficient cadaveric kidney supply to meet the demands of suitable transplant candidates. The comparative equity and efficiency characteristics of alternative organ allocation strategies have not been rigorously examined. Methods. We developed a five-compartment Monte Carlo simulation model to compare alternative organ allocation strategies, accommodating dynamic changes in recipient and donor characteristics, patient and graft survival rates, and quality of life. Four distinct allocation strategies were compared: first-come first-transplanted, a point system currently utilized by the United Network of Organ Sharing, an efficiency-based algorithm, whose additional goal was to promote equitable allocation among African American and non-African American candidates. Results. A 10-year computer simulation run was performed. The distributive efficiency policy was associated with a 3.5% (plus, minus symbol) 0.8% increase in quality-adjusted life expectancy, a decrease in the median waiting time to transplantation (6.6 months vs. 16.3 months), and an increase in the overall likelihood of transplantation (60.9% vs. 44.8%), compared with the United Network of Organ Sharing algorithm. Improved equity and efficiency measures were evident across categories of race (African American vs. other), gender, and age (<50 or _>50 years). The distributive efficiency algorithm yielded an increase in quality-adjusted life expectancy that is roughly 65% of the estimated improvement achieved by the use of cyclosporin, and is comparable to what would be achieved by a 23% increase in the supply of donor organs. Conclusion. Evidence-based organ allocation strategies in cadaveric kidney transplantation would yield improved equity and efficiency measures compared with existing algorithms.