Combined Molecular Mismatch Approaches to Predict Immunological Events Within the First Year After Renal Transplantation

Abstract

Several molecular mismatch assessment approaches exist, but data on their combined use are limited. In this study, we aimed to define distinct risk groups for rejection based on the combination of three molecular mismatch assessment approaches (i.e., eplet mismatch count, the number of highly immunogenic eplets and PIRCHE‐II score) in 439 consecutive immunological standard risk transplantations. For each molecular mismatch assessment approach, ROC analyses were used to define cut‐offs for prediction of (sub) clinical rejection according to Banff 2019 classification within the first year post‐transplant as a reference. If all three scores were below the cut‐off, the patient was assigned to the low‐risk group (19% of patients); if all three scores were above the cut‐off, the patient was assigned to the high‐risk group (21% of patients). The one‐year incidence of (sub) clinical rejection was 12% in the low‐risk group and 33% in the high‐risk group (p = 0.003). Internal validation of the assigned risk groups for prediction of other outcomes revealed a high consistency: clinical rejection (6% vs. 24%; p = 0.004), ATG‐treated rejection (1% vs. 16%; p < 0.001) and development of de novo HLA‐DSA at 5 years post‐transplant (6% vs. 25%; p = 0.003). The molecular mismatch risk group was an independent predictor for (sub) clinical rejection (high‐risk vs. low‐risk: hazard ratio 3.11 [95%‐CI 1.50–6.45]; p = 0.002). We conclude that combining molecular mismatch approaches allows us to distinguish low‐ and high‐risk groups among standard renal allograft recipients. Independent validation in other patient populations and different ethnicities is required.