Optimization and Simulation of Kidney Paired Donation Programs

双肾捐献方案的优化与模拟 摘要 一种称为肾脏配对捐赠（KPD）的不断发展的策略提供了克服障碍的方法 许多肾衰竭患者面临的问题是， 不相容的活体捐赠者KPD程序使用计算机算法来匹配一个不兼容的 第一对供体/受体配对与具有互补不亲和性的另一对，使得第一对的供体 给予第二个接受者，反之亦然。更复杂的器官交换涉及三个或更多的器官。 更多的夫妇也被认为是利他主义或非定向捐赠者（NDD），他们自愿捐赠肾脏 从而有可能创造一系列的肾脏移植。这样的捐助者和链条已经成为 在KPD计划中越来越重要。检查池中所有潜在移植的可行性并不是 逻辑上是可能的，因此KPD程序中的一个基本问题是选择 在存在的许多可能性中考虑匹配。我们以前已经开发了 选择考虑到过程中的不确定性的潜在匹配;即， 在计算机算法上识别的移植通常在尝试将它们放入 实践我们开发的方法，考虑到这种不确定性的问题，从而提供新的和 选择潜在匹配的更好战略，以便在潜在匹配时提出后备方案， 发现移植物不能存活。这种方法有可能大大增加数量和/或 进行移植的效用。 在这次更新中，我们将建立在初步成功的基础上，并扩展我们的方法， KPD的其他重要方面。我们的匹配算法将被推广到允许 非传统供体来源，包括来自相容配对的供体、已故供体，以及 国际KPD计划，以解锁现有KPD中的许多潜在移植。我们将开发 计算算法，这将允许选择更大的子集，这反过来将导致更大的 后备选项的数量以及潜在移植的增加。我们将进一步发展我们的微 模拟模型，以纳入和审查捐助者创新来源的结果， 用户界面和可视化方法。我们已经开发并将改进计算器， 根据供体和受体的特征预测移植物存活率等结果， 我们的匹配方法中。该提案旨在提高 肾移植在患者生活质量和降低医疗费用方面具有相关益处。

OPTIMIZATION AND SIMULATION OF KIDNEY PAIRED DONATION PROGRAMS ABSTRACT An evolving strategy known as kidney paired donation (KPD) provides an approach to overcome the barriers faced by many patients with kidney failure who present with willing, but immunologically or blood type incompatible living donors. KPD programs use a computerized algorithm to match one incompatible donor/recipient pair to another pair with a complementary incompatibility, such that the donor of the first pair gives to the recipient of the second, and vice versa. More complex exchanges of organs involving three or more pairs are also considered as are altruistic or non-directed donors (NDD) who donate a kidney voluntarily and thereby have the potential to create a chain of kidney transplants. Such donors and chains have become increasingly important in KPD programs. Checking the viability of all potential transplants in a pool is not logistically possible, and so a fundamental problem in a KPD program is selecting an optimal subset of matches to consider among the many possibilities that exist. We have previously developed methods of selecting potential matches that take account of the uncertainty in the process; namely that potential transplants that are identified on a computer algorithm often fail when an attempt is made to put them into practice. We develop approaches to the problem that take account of this uncertainty and so provide new and better strategies for choosing potential matches with a view to presenting fall back options when potential transplants are found not to be viable. This approach has the potential to greatly increase the number and/or utility of transplants performed. In this renewal, we will build on initial successes and extend our methods to incorporate several important additional aspects of KPD. Our matching algorithms will be generalized to allow for nontraditional sources of donors, including donors from compatible pairs, deceased donors, and international KPD programs to unlock many potential transplants in existing KPDs. We will develop computational algorithms that will allow selection of larger subsets, which in turn will lead to a greater number of fallback options and increases in potential transplants. We will further develop our micro simulation model to include and examine the results of innovative sources of donors and to enhance the user interface and methods of visualization. We have developed and will refine calculators to predict outcomes such as graft survival based on donor and recipient characteristics and incorporate these calculations into our matching methods. This proposal aims to increase the number and quality of kidney transplants with associated benefits in patient quality of life and reduced medical costs.