Optimal Older Donor and Recipient Matching to Enhance Liver Transplant Outcomes



 DESCRIPTION (provided by applicant): Liver transplantation (LT) is currently the only definitive treatment for patients with end stage liver disease (ESLD). Because of the critical organ shortage, more than 2,000 people die annually awaiting LT. The average ages of both patients with ESLD on LT waiting list and liver organ donors have been increasing over the past decade. Donation after brain death is currently the largest source of livers. Increasingly, donors after circulatory death (DCD), and other extended criteria donors (ECD) have been used to expand the pool of donor organs. ECD organs are often donated by older individuals, which have a higher rate of graft failure than organs from younger donors. Consequently, approximately 65% of donated livers from donors 65 years or older are discarded when their inclusion could expand the donor pool to save the lives dying on waiting list. Therefore, identifying the optimal recipients who might benefit from ECD livers and livers from older donors is of paramount importance to improve liver utilization and reduce waiting list mortality. The Scientific Registry of Transplant Recipients (SRTR) risk-adjustment models are used by the Centers for Medicare & Medicaid Services to certify transplant centers for reimbursement. The American Society of Transplant Surgeons (ASTS) has identified several important factors that are not considered in the SRTR models, including advanced coronary artery disease and other age-associated comorbidities. In addition, some interactions between donor and recipient risk factors have been identified but not incorporated in the SRTR model. The overall objective of this project is to improve individual donor-recipient matching for optimizing liver utilization and transplant outcomes of elderly donors and recipients. To accomplish the objective, we will use advanced biostatistical methods to conduct secondary data analysis based on enhanced donor and recipient risk factors and outcomes data to improve risk prediction models for individual donor-recipient matching, which can be used to assist patient-centered decision making and improve organ allocation in LT. We will merge institutional (Northwestern University Enterprise Data Warehouse [EDW]), and national (Organ Procurement and Transplant Network [OPTN], SRTR, and University Healthcare Consortium [UHC]) data sources to enhance donor and recipient risk factors and outcomes data including pre-transplant and post-transplant comorbidity conditions. We will then pursue the two Specific Aims: 1) To develop and validate statistical models for predicting short- and long-term outcomes for individual donor-recipient matching, considering interaction between donor and recipient risk factors. 2) To assist patient-specific decision making by comparing the risks and benefits of accepting a given donor liver vs. staying on the waiting list for a potential better liver.