Impact of HLA-DPB1 Matching on Outcome of Unrelated Transplant for Hematologic Malignant Diseases: A Systematic Review and Meta-analysis

Abstract

Objective: Human leukocyte antigen match is the most important donor factor affecting transplant outcome. The HLA-DPB1 mismatch on the clinical outcome of hematopoietic stem cell transplant (HSCT) is less clear. This study is the first meta-analysis to investigate the impact of HLA-DPB1 loci mismatch on clinical outcome after unrelated donor HSCT for hematologic malignant disease.

Methods: We electronically searched the PubMed, EMBASE, Cochrane Central Register of Controlled Trials, and a related database (January 1995-December 2018) for all relevant articles. Comparative studies were carried out to investigate the impact of HLA-DPB1 loci mismatch on clinical outcome after unrelated donor HSCT, that is, the disease-free survival, engraftment, graft-vs-host disease, relapse, and transplant-related mortality (TRM). We performed a meta-analysis using Review Manager 5.3.5 software and adopted funnel plot regression to assess the publication bias.

Results: A total of 1570 articles were retrieved; 21 studies including 27,852 patients were assessed. Pooled comparisons of studies found that the HLA-DPB1-mismatched group had a lower rate of disease-free survival than the DPB1-matched group and lower overall survival in non-T cell-depleted transplant than the DPB1-matched group. The DPB1-mismatched group has higher incidence of acute graft-vs-host disease (aGVHD) and severe (≥ III degree) aGVHD, lower relapse rate, and higher TRM. Moreover, compared with 1-antigen mismatch, 2-antigen mismatch in DPB1 had a higher risk of TRM and a lower relapse rate, and the nonpermissive DPB1 mismatch had significantly higher rate of severe aGvHD and lower rate of disease relapse.

Conclusions: This analysis confirmed that HLA-DPB1 has important influence on survival and transplant-related complications during unrelated donor HSCT, and HLA-DPB1 donor selection strategies have been proposed based on personalized algorithm.