Optimal Older Donor and Recipient Matching to Enhance Liver Transplant Outcomes

 描述（由申请人提供）：肝移植（LT）目前是终末期肝病（ESLD）患者的唯一确定性治疗方法。由于严重的器官短缺，每年有2,000多人死于等待LT。在过去十年中，LT等候名单上的ESLD患者和肝脏器官捐献者的平均年龄一直在增加。脑死亡后的捐赠是目前最大的肝脏来源。循环死亡后供体（DCD）和其他扩展标准供体（ECD）已越来越多地用于扩大供体器官库。ECD器官通常由老年人捐赠，其移植失败率高于年轻捐赠者。因此，大约65%来自65岁或以上捐赠者的捐赠肝脏被丢弃，当他们的加入可以扩大捐赠者库以挽救等待名单上死亡的生命时。因此，确定可能受益于ECD肝脏和老年供体肝脏的最佳受体对于提高肝脏利用率和降低等待名单死亡率至关重要。医疗保险和医疗补助服务中心使用移植接受者科学登记处（SRTR）风险调整模型来认证移植中心的报销。美国移植外科医师协会（ASTS）已经确定了SRTR模型中未考虑的几个重要因素，包括晚期冠状动脉疾病和其他年龄相关的合并症。此外，捐助者和接受者之间的一些相互作用的风险因素已经确定，但没有纳入SRTR模型。该项目的总体目标是改善个体供体-受体匹配，以优化肝脏利用， 老年供体和受体的移植结果。为了实现这一目标，我们将使用先进的生物统计学方法，根据增强的供体和受体风险因素和结果数据进行二次数据分析，以改进个体供体-受体匹配的风险预测模型，这可用于帮助以患者为中心的决策制定和改善LT中的器官分配。（西北大学企业数据仓库[EDW]），和国家（器官获取和移植网络[OPTN]，SRTR，和大学医疗保健联盟[UHC]）数据源，以增强供体和受体的风险因素和结果数据，包括移植前和移植后移植并发症。然后，我们将追求两个具体目标：1）开发和验证统计模型，用于预测单个供体-受体匹配的短期和长期结果，考虑供体和受体风险因素之间的相互作用。2)通过比较接受给定供体肝脏与留在等待名单上等待潜在更好的肝脏的风险和益处，帮助患者做出特定的决策。

 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.