<scp>A</scp> Comprehensive Assessment of Plasma <scp>CXCL9</scp> and <scp>CXCL10</scp> in Improving Clinical Prediction Models for Kidney Allograft Rejection

Chemokine levels may predict kidney graft rejection. This study evaluated whether adding early plasma chemokines C‐X‐C motif ligand 9 (CXCL9) or chemokines C‐X‐C motif ligand 10 (CXCL10) measurements to a standard‐of‐care model improves the prediction of the need for antirejection treatment and helps guide biopsy decisions. The benchmark model used recipient and donor age, human leukocyte antigen mismatches, and dialysis need in the first 3 days after transplantation. Plasma CXCL9 or CXCL10 was added, and the extended models were evaluated using likelihood ratio tests (LRTs), area under the receiver operating characteristic curve (ROC‐AUC), flexible calibration curves, and net benefit analysis. Model internal validation was performed through bootstrapping. Among 163 consecutively transplanted recipients on standard immunosuppression, 43 (26.4%) required antirejection therapy between Days 3 and 21 posttransplant. The chemokine‐extended models outperformed the benchmark (LRT p < 0.01), increasing discriminative ability (delta ROC‐AUC of 0.02) and improving calibration. Across the range of risk thresholds for biopsy, the extended models provided better clinical utility, resulting in up to 17 fewer unnecessary biopsies per 100 patients. These findings suggest that adding plasma CXCL9 or CXCL10 to a benchmark model can improve patient care by reducing the number of biopsies in individuals unlikely to require antirejection therapy.