AUTHOR=Eberhard Hans-Peter , Müller Carlheinz R. TITLE=The Impact of HLA-C Matching on Donor Identification Rates in a European-Caucasian Population JOURNAL=Frontiers in Immunology VOLUME=5 YEAR=2014 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2014.00501 DOI=10.3389/fimmu.2014.00501 ISSN=1664-3224 ABSTRACT=

The degree of HLA concordance with the patient has long been known to be the major donor-related prediction factor for the success of hematopoietic stem cell transplantations and, with the progress of HLA typing technology, selection criteria became more stringent with regard to the recommended loci and resolution. A late refinement was HLA-C matching, which gained broader acceptance only after the turn of the millennium. The enormous HLA polymorphism has always necessitated registries with a large number of donors in order to be able to provide well-matched donors to a substantial fraction of patients. Using a biostatistical approach, we investigated the impact of adding HLA-C at low or high resolution as a supplementary matching criterion on some key parameters in donor provision for a European-Caucasian population. Starting point is donor selection based on allele level matching for HLA-A, -B, -DRB1, and, optionally, HLA-DQB1. Without typing for HLA-C, 68% of the donors selected based on matching for HLA-A, -B, -DRB1, and -DQB1 at high resolution will also match for HLA-C, 29% will have a single and only 3% will have two HLA-C alleles different from the patient. In order to provide the same fraction of patients with a fully matched donor, a registry would have to be about twice the size if HLA-C is considered in addition to the four other loci, with the exact factor increasing with the registry’s size. If the provision of donors with up to a single allele mismatch is considered, this factor doubles due to the strong linkage between HLA-B and -C. These figures only change slightly when HLA-DQB1 is completely ignored or HLA-C matching is only considered at low resolution. Our results contribute to quantifying the medical and economic impact of the progress in donor selection algorithms.