Abstract: PUB354
Review of Real-World Evidence for Pretransplant Risk Assessment Tests in Kidney Transplantation
Session Information
Category: Transplantation
- 2102 Transplantation: Clinical
Authors
- Knight, Richard J., Thermo Fisher Scientific, West Hills, California, United States
- Litchfield, Maria Catterina, Thermo Fisher Scientific, West Hills, California, United States
- Dale, Bethany L, Thermo Fisher Scientific, West Hills, California, United States
- Liedtky, Tina, Thermo Fisher Scientific, West Hills, California, United States
- Kuang, Yuting, IQVIA Inc, San Mateo, California, United States
- Jin, He, IQVIA Inc, San Mateo, California, United States
- Wang, Yu, IQVIA Inc, San Mateo, California, United States
- Uyei, Jennifer, IQVIA Inc, San Mateo, California, United States
- McGonigle, Joseph, IQVIA Inc, San Mateo, California, United States
Background
Immunosuppression protocols for kidney transplant care are often based on population-based characteristics such as age, race, and prior transplant. Pre-transplant biomarker tests may improve risk stratification and tailor immunosuppression regimens for the individual recipient. This review synthesized evidence on the clinical performance of pre-transplant tests in predicting outcomes after kidney transplantation in the United States (US).
Methods
EMBASE and MEDLINE were searched up to March 2025. Studies evaluating the clinical performance of pre-transplant tests in kidney transplantation in the US were included.
Results
Of 1043 references identified, 27 references on 5 pre-transplant tests were included (Table). For emerging tests, the pre-transplant risk assessment assay (PTRA), a recipient-only test based on transcriptomic signature, effectively classified recipient immunologic risk for early acute rejection (OR=6.13, high vs low risk) [1]. Based on donor-recipient HLA epitope/eplet mismatch, PIRCHE-II and HLAMatchmaker predicted risk for post-transplant dnDSA and graft rejection. A higher PIRCHE-II score was associated with TCMR (HR=1.23) [2]. Similarly, the risk of TCMR (OR=1.05) and AMR (OR=1.12) increased with each DQ eplet mismatch detected by HLAMatchmaker [3]. For tests commonly used in routine care, presence of pre-transplant Class I & II DSA predicted 1-year acute AMR (OR=39 vs no DSA) [4]. cPRA alone was not a reliable predictor of post-transplant outcomes [5].
Conclusion
Emerging pre-transplant tools show promising performance in predicting early kidney graft rejection on an individual patient level, highlighting their potential value in tailoring immunosuppression regimens. Ongoing research on costs, turnaround time, ease of use, and their impact on clinical outcomes will further inform usage optimization of these tests.
| Name of tests (number of references) | Methods | Required input | Outcomes predicted by test results |
| Pre-Transplant Risk Assessment (PTRA) (n=2) | A 29-gene mRNA signature combined with a machine-learning shrinkage discriminate analysis algorithm to produce a risk score (high risk vs low risk) | Recipient only | Early acute rejection in the first 60 days post- transplant |
| Predicted Indirectly Recognizable HLA Epitopes (PIRCHE-II) (n=8) | A computational algorithm that predicts T cell epitopes by assessing whether mismatched donor Human Leukocyte Antigens (HLA)-derived peptides can bind to HLA class II molecules | Both donor and recipient | De novo DSA (dnDSA), antibody-mediated rejection (AMR), T cell-mediated rejection (TCMR), alloimmune mediated graft failure, death-censored graft survival Acute rejection (AR) and graft rejection 1 year post transplant were assessed but association not detected (n=2) |
| HLAMatchmaker (n=15) | A structurally based computer algorithm that enables HLA matching at the eplet level, and quantifies the eplet mismatch load | Both donor and recipient | dnDSA, AR, AMR, TCMR, Banff t scores, graft failure/ survival Long-term allograft failure assessed but association not detected (n=1) |
| Pre-transplant Donor-Specific Antibody (DSA) testing (n=5) | An assessment performed before transplant to detect recipient pre-formed antibodies against donor HLA antigens. Detection methods include virtual crossmatch and physical crossmatch | Both donor and recipient | dnDSA, AR, AMR, death-censored graft survival, estimated glomerular filtration rate (eGFR) TCMR assessed but association not detected (n=1) |
| Calculated Panel Reactive Antibody (cPRA) score (n=3) | Based on population HLA frequencies, cPRA estimates the percentage of donors with unacceptable HLA antigens for a recipient | Recipient only | Chronic AMR and microvascular inflammation AR and graft loss assessed but association not detected (n=2) |
| Citations: [1] Gallon, 2023, 10.1681/ASN.20233411B4a; [2] Crane, 2023, 10.1016/j.ajt.2023.05.014 (vol 23, No.6, S759); [3] Senev, 2020, 10.1681/ASN.2020010019; [4] Kannabhira, 2015, 10.1097/TP.0000000000000511; [5] Lan, 2021, 10.2215/CJN.13640820 | |||
Funding
- Commercial Support – Thermo Fisher Scientific