416.1: Impact of HLA-A,B DR and DQ on Deceased Kidney Transplant Outcomes in the Tacrolimus/MMF Era: An Artificial Intelligence Approach

Abstract

Introduction: One of the biological barriers that can impact outcomes in kidney transplantation is HLA mismatch. Several immunotherapy protocols were implemented to reduce this detrimental effect. The aim of our study is to assess the effect of HLA mismatches on acute rejection rates and graft survival in the Tacrolimus era. Moreover, to determine the most important factors affecting survival. Methodology: All kidney transplant patients registered in UNOS database between 01/01 2005 and 01/12/2019 were retrospectively reviewed. Inclusion criteria: deceased donor transplants that were discharged on Tacrolimus/Mycophenolate Mofetil. Exclusion criteria: multiple organ transplants, previous kidney transplants, recipient age<18 years old, living donor transplants, missing data about induction therapy, missing HLA mismatch or ABO incompatible transplant. We used double-selection lasso (least absolute shrinkage and selection operator) logistic regression model to assess for the effect of HLA-A, B, DR, and DQ on acute rejection rates at one-year post-transplant. Variables of interest were HLA-A,B,DR and DQ mismatch. Variables Lasso selected from were: recipient characteristics (age, sex, BMI, ethnicity, diabetes, recipient/donor CMV status, pre-transplant dialysis), donor characteristics (KDPI score) and transplant characteristics (induction therapy, steroid intake, cold ischemia time, delayed graft function, PRA). Acute rejection was defined as biopsy proven or clinically suspected rejection. For survival analysis, we fit a penalised Cox model after choosing best alpha. Cross-validated grid-search was used to evaluate the best alpha. The variables included in the penalised cox model: donor, recipient and transplant factors. We visualised the coefficients variations across different α using ridge regression model in figure 1. Results: 66,021 were included. Worse acute rejection rates at one-year post-transplant were noted with incremental increase in HLA-DQ (Two HLA-DQ: OR=1.24, P=0.005,95%CI:1.10-1.40; One HLA DQ:OR=1.19,P=0.01,95%CI:1.06-1.33), HLA-DR mismatches (Two HLA-DR: OR=1.41, P<0.01, 95%CI:1.25-1.61; One HLA-DR: OR=1.27,p<0.01, 95%CI:1.13-1.43),Two HLA-B (OR=1.19,P=0.049) and HLA-A(Two HLA-A: OR=1.18, P=0.01; One HLA-A: OR=1.16,P=0.02). In the penalized cox regression model, only Two HLA-DR mismatch was associated with worse survival (HR=1.13, P<0.01, 95%CI: 1.05-1.21). KDPI was the most important factor affecting graft survival (KDPI>80%: HR=2.3, P<0.01; KDPI 60-80%: HR=1.57, P<0.01; KDPI 40-60%: HR=1.23, P<0.01). Delayed graft function affected graft survival by HR=1.50 (P<0.01). Mean follow-up time was 3.79 years. Conclusion: HLA-DQ, DR,B and A mismatches play a vital role in the occurrence of acute rejection in the Tacrolimus/MMF era. However, only 2-HLA-DR mismatch has significant effect on graft survival. KDPI>40% and delayed graft function play the most important role in determining graft survival.