 Computational Eurotransplant kidney allocation simulations demonstrate the feasibility and benefit of T-cell epitope matchingMatthias Niemann, Nils Lachmann, Kirsten Geneugelijk and Eric Spierings PLOS Computational Biology, 2021, vol. 17, issue 7, 1-22 Abstract: The EuroTransplant Kidney Allocation System (ETKAS) aims at allocating organs to patients on the waiting list fairly whilst optimizing HLA match grades. ETKAS currently considers the number of HLA-A, -B, -DR mismatches. Evidently, epitope matching is biologically and clinically more relevant. We here executed ETKAS-based computer simulations to evaluate the impact of epitope matching on allocation and compared the strategies. A virtual population of 400,000 individuals was generated using the National Marrow Donor Program (NMDP) haplotype frequency dataset of 2011. Using this population, a waiting list of 10,400 patients was constructed and maintained during simulation, matching the 2015 Eurotransplant Annual Report characteristics. Unacceptable antigens were assigned randomly relative to their frequency using HLAMatchmaker. Over 22,600 kidneys were allocated in 10 years in triplicate using Markov Chain Monte Carlo simulations on 32-CPU-core cloud-computing instances. T-cell epitopes were calculated using the www.pirche.com portal. Waiting list effects were evaluated against ETKAS for five epitope matching scenarios. Baseline simulations of ETKAS slightly overestimated reported average HLA match grades. The best balanced scenario maintained prioritisation of HLA A-B-DR fully matched donors while replacing the HLA match grade by PIRCHE-II score and exchanging the HLA mismatch probability (MMP) by epitope MMP. This setup showed no considerable impact on kidney exchange rates and waiting time. PIRCHE-II scores improved, whereas the average HLA match grade diminishes slightly, yet leading to an improved estimated graft survival. We conclude that epitope-based matching in deceased donor kidney allocation is feasible while maintaining equal balances on the waiting list.Author summary: Kidney transplantation is the best treatment option for patients suffering permanent loss of kidney function. High degrees of histocompatibility between patients and organ donors improve long-term function of transplanted kidneys. In order to ensure fair access to transplantation whilst maximising utility of each donor kidney, organ allocation organizations established recipient waiting lists and well-balanced algorithms to allocate donors to patients. Changing the allocation algorithms requires careful consideration of side-effects to avoid disadvantages of certain groups of patients. In this study, we evaluated the feasibility of modifying the existing Eurotransplant Kidney Allocation System (ETKAS) to incorporate indirect T-cell epitope matching, a novel technique for assessing functional histocompatibility. Using Markov chain Monte Carlo simulations, we compared the modified allocation to the current algorithm and found an overall improvement of indirect T cell epitope compatibility. Simultaneously, we observed no negative impact on allocation fairness or waiting times. Our simulation framework may serve as a basis to evaluate further adjustments to ETKAS in the future. From our results, we conclude that epitope matching can be safely incorporated into ETKAS. Date: 2021 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1009248 DOI: 10.1371/journal.pcbi.1009248 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
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