School of Mathematics and Statistics, The University of Sydney, F07- Carslaw Building, Sydney, NSW, Australia.
Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia.
Sci Rep. 2023 Sep 29;13(1):16367. doi: 10.1038/s41598-023-41162-w.
Organ shortage is a major barrier in transplantation and rules guarding organ allocation decisions should be robust, transparent, ethical and fair. Whilst numerous allocation strategies have been proposed, it is often unrealistic to evaluate all of them in real-life settings. Hence, the capability of conducting simulations prior to deployment is important. Here, we developed a kidney allocation simulation framework (simKAP) that aims to evaluate the allocation process and the complex clinical decision-making process of organ acceptance in kidney transplantation. Our findings have shown that incorporation of both the clinical decision-making and a dynamic wait-listing process resulted in the best agreement between the actual and simulated data in almost all scenarios. Additionally, several hypothetical risk-based allocation strategies were generated, and we found that these strategies improved recipients' long-term post-transplant patient survival and reduced wait time for transplantation. The importance of simKAP lies in its ability for policymakers in any transplant community to evaluate any proposed allocation algorithm using in-silico simulation.
器官短缺是移植领域的一个主要障碍，管理器官分配决策的规则应该强大、透明、符合伦理且公平。虽然已经提出了许多分配策略，但在实际环境中评估所有策略往往不切实际。因此，在部署之前进行模拟的能力很重要。在这里，我们开发了一个肾脏分配模拟框架（simKAP），旨在评估肾脏移植中的分配过程和器官接受的复杂临床决策过程。我们的研究结果表明，在几乎所有情况下，将临床决策和动态候补名单过程结合起来，可使实际数据和模拟数据之间的一致性达到最佳。此外，还生成了几种基于风险的假设分配策略，我们发现这些策略提高了受者长期移植后患者的存活率，并减少了移植等待时间。simKAP 的重要性在于，它使任何移植社区的政策制定者都能够使用计算机模拟来评估任何拟议的分配算法。
