A comparative reference study for the validation of HLA-matching algorithms in the search for allogeneic hematopoietic stem cell donors and cord blood units

• Published in: HLA Vol. 87; no. 6; pp. 439 - 448
• Main Authors: Bochtler, W., Gragert, L., Patel, Z. I., Robinson, J., Steiner, D., Hofmann, J. A., Pingel, J., Baouz, A., Melis, A., Schneider, J., Eberhard, H.-P., Oudshoorn, M., Marsh, S. G. E., Maiers, M., Müller, C. R.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.06.2016
• Subjects: Algorithms; Alleles; Cord Blood Stem Cell Transplantation; Datasets as Topic; donor registry; Gene Frequency; Haplotypes; Hematopoietic Stem Cell Transplantation; Histocompatibility Testing; HLA Antigens - classification; HLA Antigens - genetics; HLA Antigens - immunology; human leukocyte antigen; Humans; immunogenetics; matching algorithm; Original; patient-donor matching; Registries; Transplant Recipients; Transplantation, Homologous; Unrelated Donors; matching algorithm; donor registry; hematopoietic stem cell transplantation; immunogenetics; human leukocyte antigen; patient-donor matching
• ISSN: 2059-2302; 2059-2310; 2059-2310
• DOI: 10.1111/tan.12817

The accuracy of human leukocyte antigen (HLA)‐matching algorithms is a prerequisite for the correct and efficient identification of optimal unrelated donors for patients requiring hematopoietic stem cell transplantation. The goal of this World Marrow Donor Association study was to validate established matching algorithms from different international donor registries by challenging them with simulated input data and subsequently comparing the output. This experiment addressed three specific aspects of HLA matching using different data sets for tasks of increasing complexity. The first two tasks targeted the traditional matching approach identifying discrepancies between patient and donor HLA genotypes by counting antigen and allele differences. Contemporary matching procedures predicting the probability for HLA identity using haplotype frequencies were addressed by the third task. In each task, the identified disparities between the results of the participating computer programs were analyzed, classified and quantified. This study led to a deep understanding of the algorithms participating and finally produced virtually identical results. The unresolved discrepancies total to less than 1%, 4% and 2% for the three tasks and are mostly because of individual decisions in the design of the programs. Based on these findings, reference results for the three input data sets were compiled that can be used to validate future matching algorithms and thus improve the quality of the global donor search process.