Zentrales Knochenmarkspender-Register Deutschland (ZKRD), Ulm, Germany.
National Marrow Donor Program (NMDP), Minneapolis, MN, USA.
HLA. 2016 Jun;87(6):439-48. doi: 10.1111/tan.12817. Epub 2016 May 24.
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.
人类白细胞抗原(HLA)匹配算法的准确性是正确、高效地识别需要造血干细胞移植的患者最佳非亲缘供体的前提条件。世界骨髓捐献者协会(World Marrow Donor Association)这项研究的目的是通过模拟输入数据对来自不同国际供者登记处的已建立的匹配算法进行验证,并比较输出结果。该实验使用不同数据集针对 HLA 匹配的三个具体方面进行了测试,任务的复杂性逐渐增加。前两个任务针对传统的匹配方法,通过计算抗原和等位基因差异来识别患者和供者 HLA 基因型之间的差异。第三个任务则使用单倍型频率预测 HLA 同一性的概率的当代匹配程序。在每个任务中,对参与计算机程序的结果之间的差异进行了分析、分类和量化。这项研究深入了解了参与的算法,最终产生了几乎完全相同的结果。对于这三个任务,未解决的差异总计不到 1%、4%和 2%,主要是因为程序设计中的个别决策。基于这些发现,为这三个输入数据集编制了参考结果,可以用于验证未来的匹配算法,从而提高全球供者搜索过程的质量。