Rescuing Kidneys at Risk of Discard

项目摘要。肾移植(KT)是许多患者透析的一种更好的选择 在寿命、生活质量、发病率和终末期肾病(ESRD)护理成本方面。然而， 在2017年等待接受KT的9.5万名患者中，只有不到2万人获得了KT。同年，大约 4000名患者死亡，另有4700名患者因病情过重而被从等待名单中删除 去移植。尽管等待名单很长，但超过3500个(19%)的已故捐赠者肾脏被丢弃。 “没有找到受赠者”是1325个捐赠肾脏被丢弃的原因。报废率 低质量肾脏显著增加，最低质量肾脏高达60% 十进制。即使许多被丢弃的肾脏，即使是那些质量最差的肾脏，也会发生这种丢弃 与继续接受透析相比，给一些接受者带来了显著的生存好处。 目前的肾脏分配系统不能有效地分配高丢弃风险的肾脏。这个 患者优先排序算法不能快速确定哪些患者将从这种肾脏中受益最大，并且 捐赠的肾脏被浪费了。需要改进肾脏分配系统，以减少 在将其公平分配给受益最大的患者的同时，减少丢弃的肾脏的数量。然而， 修订分配政策是具有挑战性的，因为患者和移植专业人员必须权衡风险和 接受低质量肾脏的好处与等待高质量肾脏的风险相对较低。这个 移植社区和患者接受低质量肾脏的偏好尚不清楚。 这项拟议的研究旨在开发拯救活着的死者的肾脏分配算法 捐献的肾脏被丢弃。开发的算法将(I)使用以下方法识别有可能被丢弃的肾脏 肾脏捐赠者概况指数或新的肾脏丢弃风险评分等措施；(Ii)识别患者 人群，例如等待移植时间较长或功能状态较低的人群，谁将受益于 大多数来自可存活的肾脏。移植临床医生(外科医生和肾科医生)和患者的偏好 (关于透析和移植接受者)将通过离散选择实验来引发，这些实验将量化 有丢弃风险的肾脏的分配效率和公平性权衡。一种离散事件仿真软件 发动机将被开发出来。模拟引擎将包括移植中心和患者特定的肾脏 接受行为，以及开发的分配算法。不同分配算法的优势 将在模拟中进行评估。 器官共享联合网络、器官采购协会的代表 组织和美国肾脏患者协会将在科学顾问委员会任职。这个 开发的分配算法将通过减少肾脏丢弃，帮助每年挽救约1,000人的生命。 研究成果将广泛传播给移植社区，以促进快速实施。

Project Summary. Kidney transplantation (KT) is a superior alternative to dialysis for many patients with respect to longevity, quality of life, morbidity, and the cost of End-Stage Renal Disease (ESRD) care. However, of the 95,000 patients waitlisted for a KT in 2017, less than 20,000 received a KT. In the same year, about 4,000 patients died, while another 4,700 were removed from the waitlist because they were considered too sick to transplant. Despite the long waitlist, more than 3,500 (19%) of the deceased donor kidneys were discarded. “No Recipient Found” was the stated reason for discarding 1,325 of the donated kidneys. The discard rate increases significantly for the low-quality kidneys, reaching as high as 60% for the kidneys in the lowest quality decile. This discard occurs even though many discarded kidneys, even those in the lowest quality decile, would have conferred significant survival benefits to some recipients relative to remaining on dialysis. The current kidney allocation system does not efficiently allocate kidneys at high risk of discard. The patient prioritization algorithm does not quickly identify patients who will benefit most from such kidneys, and the donated kidneys are wasted. Improvements to the kidney allocation system are needed to reduce the number of discarded kidneys while allocating them equitably to patients who would most benefit. However, revising allocation policy is challenging because patients and transplant professionals must weigh the risks and benefits of accepting a low-quality kidney against the risks of waiting for a much higher quality kidney. The transplant community and patient preferences in accepting low-quality kidneys are unknown. The proposed study aims to develop kidney allocation algorithms that rescue viable deceased donor kidneys from discard. The developed algorithms will (i) identify kidneys at risk of discard using measures such as Kidney Donor Profile Index, or a novel Kidney Discard Risk Score; (ii) identify patient populations, such as those with longer waiting times to transplant or low functional status, who will benefit the most from viable kidneys. Preferences of the transplant clinicians (Surgeons and Nephrologists) and patients (on dialysis and transplant recipients) will be elicited using discrete-choice experiments that will quantify allocation efficiency and fairness tradeoffs for kidneys at risk of discard. A discrete event simulation software engine will be developed. The simulation engine will incorporate transplant center and patient-specific kidney acceptance behaviors, and the developed allocation algorithms. The benefits of different allocation algorithms will be evaluated in the simulation. Representatives from the United Network of Organ Sharing, Association of Organ Procurement Organizations, and the American Association of Kidney Patients will serve on the scientific advisory board. The developed allocation algorithms will help save approximately 1,000 lives yearly by reducing kidney discards. The research outcome will be widely disseminated to the transplant community to foster rapid implementation.