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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
  • , Margriet F C de Jong
  • , Judith A Kal-van Gestel
  • , Marcia M L Kho
  • , Jeroen D Langereis
  • , Karlijn A M I van der Pant
  • , Claudia M Ranzijn
  • , Dave L Roelen
  • , Eric Spierings
  • , Christina E M Voorter
  • , Jacqueline van de Wetering
  • Arjan D van Zuilen, Joke I Roodnat, Annelies E de Weerd
*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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.

Original languageEnglish
Article number15423
Number of pages12
JournalTransplant international : official journal of the European Society for Organ Transplantation
Volume39
DOIs
Publication statusPublished - 4 Mar 2026

Keywords

  • ABO Blood-Group System
  • Algorithms
  • Blood Group Incompatibility
  • Female
  • HLA Antigens/immunology
  • Histocompatibility Testing
  • Humans
  • Kidney Transplantation/methods
  • Living Donors
  • Male
  • Monte Carlo Method
  • Netherlands
  • Retrospective Studies
  • Tissue and Organ Procurement/methods

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