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A double-ended queueing model for dynamic allocation of live organs based on a best-fit criterion

机译：基于最佳匹配准则的活体器官动态分配的双端排队模型

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摘要

We propose a novel approach, based on a Human Leukocyte Antigen (HLA) best-fit criterion, to dynamically allocate live organs (specifically, kidneys) to candidates needing transplantation. A 'reward' is assigned to each level of HLA fit, such that higher rewards are attributed to transplants between better-matched candidates and kidneys. We also envision future technologies by which it will be possible to store organs so that two queues may form: waiting candidates or stored kidneys. Consequently, a double-ended queue of candidates and kidneys is constructed, where the lifetime of a stored kidney is random, and candidates queueing for transplantation may die ('renege') while waiting. We derive expressions for the probability that a candidate gets a kidney before reneging; for the mean numbers of waiting candidates and of stored kidneys; and for a candidate's or kidney's mean sojourn time. Assuming a best-HLA-fit matching policy, we study three measures of effectiveness: (i) Rate of Reward from Transplantation (RRT); (ii) Expected Reward per Transplantation (ERT), calculated as RRT divided by the rate of performed transplantations, and (iii) Gained rate of reward per one dollar of expenditure. The optimal fraction of kidneys that should be stored so as to maximize the rate of reward per one dollar of expenditure is numerically determined. (C) 2018 Elsevier Inc. All rights reserved.
机译：我们提出了一种基于人类白细胞抗原（HLA）最适合标准的新颖方法，可以动态地将活体器官（特别是肾脏）分配给需要移植的候选人。为HLA适应度的每个级别分配了一个“奖励”，以便将更高的奖励归因于匹配程度更好的候选者和肾脏之间的移植。我们还预想了未来的技术，通过这种技术可以存储器官，从而形成两个队列：候诊的候选人或存储的肾脏。因此，构造了候选者和肾脏的双端队列，其中存储的肾脏的寿命是随机的，排队等待移植的候选者可能在等待时死亡（“叛逃”）。我们推导出表达求职者在性交之前有肾脏的概率的表达式。候诊候选人和肾脏储备的平均数；以及候选人或肾脏的平均逗留时间。假设最适合HLA的匹配政策，我们研究了三种有效性度量：（i）移植报酬率（RRT）； （ii）每次移植的预期报酬（ERT），以RRT除以进行的移植率计算得出；以及（iii）每1美元支出的获得的奖励率。通过数值确定应存储的最佳肾脏比例，以使每1美元支出的回报率最大化。 （C）2018 Elsevier Inc.保留所有权利。

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