ArticleHLA2024
Combined Molecular Mismatch Approaches to Predict Immunological Events Within the First Year After Renal Transplantation.
Article in HLA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Association of eplet mismatch load and allograft injury in kidney transplant recipients.Clinical kidney journal · 2026Article
- Application of machine learning in the research progress of post-kidney transplant rejection.World journal of transplantation · 2026Review
- Evaluation of dnDSA risk stratification using the updated PIRCHE-T2 model in two kidney transplant cohorts.Frontiers in immunology · 2026Article
- Clinical application of PIRCHE scores: reclassifying immunologic risk in patients with medium eplet mismatch.Frontiers in immunology · 2026Article
- Eplet mismatch analysis in kidney transplantation: from concept to clinical practice.Clinical transplantation and research · 2025Review
- Article
- Article
- Advancing risk stratification in kidney transplantation: integrating HLA-derived T-cell epitope and B-cell epitope matching algorithms for enhanced predictive accuracy of HLA compatibility.Frontiers in immunology · 2025Article
- The role of eplet matching in solid organ transplantation.Frontiers in transplantation · 2025Review
- Predicted indirectly recognizable HLA epitopes scores and clinical outcomes after haploidentical stem cell transplantation in pediatric patients with relapsed neuroblastoma.Frontiers in immunology · 2025Article
- An integrative algorithm combining HLA epitope registry, PIRCHE-T2, and PIRCHE-B outcomes to improve immunological risk stratification in kidney transplantation.Frontiers in immunology · 2025Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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