Evidence map›Paper›PMID 34314431›Full record

ArticlePLoS computational biology2021

Computational Eurotransplant kidney allocation simulations demonstrate the feasibility and benefit of T-cell epitope matching.

Matthias Niemann, Nils Lachmann, Kirsten Geneugelijk, Eric Spierings

Abstract readValidation Study
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Novel Allocation Strategies Can Boost Kidney Exchange Programs: A Monte Carlo Simulation.Transplant international : official journal of the European Society for Organ Transplantation · 2026
    Article
  2. A discrete time simulation model for kidney allocation in Germany.Transplant international : official journal of the European Society for Organ Transplantation · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. The Progress and Challenges of Implementing HLA Molecular Matching in Clinical Practice.Transplant international : official journal of the European Society for Organ Transplantation · 2025
    Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Alloimmune Risk Stratification for Kidney Transplant Rejection.Transplant international : official journal of the European Society for Organ Transplantation · 2022
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Matthias NiemannPIRCHE AG, Berlin, Germany.ORCID 0000-0002-3514-9812
Nils LachmannCenter for Tumor Medicine, H&I Laboratory, Charité University Medicine Berlin, Berlin, Germany.ORCID 0000-0002-2081-3098
Kirsten GeneugelijkCenter of Translational Immunology, UMC Utrecht, Utrecht, The Netherlands.
Eric SpieringsCenter of Translational Immunology, UMC Utrecht, Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlgorithmsCloud ComputingComputational BiologyComputer SimulationEpitopes, T-LymphocyteEuropeFeasibility StudiesGraft SurvivalHistocompatibility TestingHumansKidney TransplantationMarkov ChainsMonte Carlo MethodTime FactorsTissue and Organ ProcurementUser-Computer InterfaceEpitopes, T-Lymphocyte

Identifiers

PMID34314431
PMCPMC8345832

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.