Evidence map›Paper›PMID 41858495›Full record

ArticleTransplant international : official journal of the European Society for Organ Transplantation2026

Novel Allocation Strategies Can Boost Kidney Exchange Programs: A Monte Carlo Simulation.

Mattheüs F Klaassen, Marry de Klerk, Marije C Baas, Hanneke Bouwsma, Laura B Bungener, Maarten H L Christiaans, Twan Dollevoet, Kristiaan Glorie, Sebastiaan Heidt, Aline C Hemke and 13 more

Abstract read
In one paragraph

Article in Transplant international : official journal of the European Society for Organ Transplantation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Nurturing a Sustainable Transplantation Journey: the best of ESOT Congress 2025.Transplant international : official journal of the European Society for Organ Transplantation · 2026
    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

23 authors.

Mattheüs F KlaassenDepartment of Internal Medicine, Erasmus MC Transplant Institute, University Medical Center Rotterdam, Rotterdam, Netherlands.
Marry de KlerkDepartment of Internal Medicine, Erasmus MC Transplant Institute, University Medical Center Rotterdam, Rotterdam, Netherlands.
Marije C BaasDepartment of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands.
Hanneke BouwsmaDepartment of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands.
Laura B BungenerDepartment of Laboratory Medicine, University Medical Center Groningen, Groningen, Netherlands.
Maarten H L ChristiaansDepartment of Internal Medicine, Maastricht University Medical Center, Maastricht, Netherlands.
Twan DollevoetErasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands.
Kristiaan GlorieErasmus Q-Intelligence, Erasmus University Rotterdam, Rotterdam, Netherlands.
Sebastiaan HeidtDepartment of Internal Medicine, Erasmus MC Transplant Institute, University Medical Center Rotterdam, Rotterdam, Netherlands.
Aline C HemkeDutch Transplant Foundation, Leiden, Netherlands.
Margriet F C de JongDepartment of Internal Medicine, University Medical Center Groningen, Groningen, Netherlands.
Judith A Kal-van GestelDepartment of Internal Medicine, Erasmus MC Transplant Institute, University Medical Center Rotterdam, Rotterdam, Netherlands.
Marcia M L KhoDepartment of Internal Medicine, Erasmus MC Transplant Institute, University Medical Center Rotterdam, Rotterdam, Netherlands.
Jeroen D LangereisDepartment of Laboratory Medicine, Radboud University Medical Center, Nijmegen, Netherlands.
Karlijn A M I van der PantDepartment of Internal Medicine, Amsterdam University Medical Center, Amsterdam, Netherlands.
Claudia M RanzijnDepartment of Immunogenetics, Sanquin Diagnostic Services, Amsterdam, Netherlands.
Dave L RoelenDepartment of Immunology, Leiden University Medical Center, Leiden, Netherlands.
Eric SpieringsCentral Diagnostics Laboratory and Center of Translational Immunology, University Medical Center Utrecht, Utrecht, Netherlands.
Christina E M VoorterDepartment of Transplantation Immunology, Maastricht University Medical Center, Maastricht, Netherlands.
Jacqueline van de WeteringDepartment of Internal Medicine, Erasmus MC Transplant Institute, University Medical Center Rotterdam, Rotterdam, Netherlands.
Arjan D van ZuilenDepartment of Internal Medicine, University Medical Center Utrecht, Utrecht, Netherlands.
Joke I RoodnatDepartment of Internal Medicine, Erasmus MC Transplant Institute, University Medical Center Rotterdam, Rotterdam, Netherlands.
Annelies E de WeerdDepartment of Internal Medicine, Erasmus MC Transplant Institute, University Medical Center Rotterdam, Rotterdam, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney exchange programs (KEPs) enhance access to living donor kidney transplantation. Nonetheless, transplant rates in KEP remain low for highly immunized and blood type O patients. In the Netherlands, a novel allocation algorithm is being implemented, allowing ABO-incompatible matching for long waiting patients, next to prioritization and 'low-level' HLA-incompatible matching for selected highly immunized patients. We simulated this novel algorithm along with additional scenarios, by using a retrospective, 6-year cohort of Dutch KEP. For each scenario, 30 simulations were repeated with Monte Carlo technique. The novel algorithm increased median KEP transplant rate for incompatible pairs (53% versus 44%, p < 0.001) and for difficult-to-match subgroups. HLA-incompatible matching increased transplant rate for selected highly immunized patients significantly, while participation with multiple donors per recipient did not. In additional simulations, including all non-KEP unspecified donors (n = 150) for local KEP participation increased transplant rate for incompatible pairs up to 64% (p < 0.001). Simulating additional KEP participation by compatible pairs (n = 149), on the condition a KEP match should have fewer HLA mismatches, resulted in 58% being matched in KEP. In conclusion, differential matching algorithms can boost KEP transplant rates, allowing incompatible matching for difficult-to-match subgroups, facilitating participation of unspecified donors, and optimizing the HLA matching of compatible pairs.

Indexed as

Kidney TransplantationTissue and Organ ProcurementABO Blood-Group SystemAlgorithmsBlood Group IncompatibilityFemaleHistocompatibility TestingHLA AntigensHumansLiving DonorsMonte Carlo MethodNetherlandsRetrospective StudiesABO Blood-Group SystemHLA Antigensallocationkidney paired donationkidney transplantationliving donorsimulation

Identifiers

PMID41858495
PMCPMC12995821

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.