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

Fuente: Wiley Open Access
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Auteurs principaux: Alvaro Assis de Souza, Dennis A. Hesselink, Carolien C. H. M. Maas, Andrew P. Stubbs, Marian Clahsen‐van Groningen, Carla C. Baan, David van Klaveren, Karin Boer
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Publié: Wiley 2025
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author Alvaro Assis de Souza
Dennis A. Hesselink
Carolien C. H. M. Maas
Andrew P. Stubbs
Marian Clahsen‐van Groningen
Carla C. Baan
David van Klaveren
Karin Boer
author_facet Alvaro Assis de Souza
Dennis A. Hesselink
Carolien C. H. M. Maas
Andrew P. Stubbs
Marian Clahsen‐van Groningen
Carla C. Baan
David van Klaveren
Karin Boer
Alvaro Assis de Souza
Dennis A. Hesselink
Carolien C. H. M. Maas
Andrew P. Stubbs
Marian Clahsen‐van Groningen
Carla C. Baan
David van Klaveren
Karin Boer
collection Wiley Open Access
contents A Comprehensive Assessment of Plasma CXCL9 and CXCL10 in Improving Clinical Prediction Models for Kidney Allograft Rejection Alvaro Assis de Souza Dennis A. Hesselink Carolien C. H. M. Maas Andrew P. Stubbs Marian Clahsen‐van Groningen Carla C. Baan David van Klaveren Karin Boer Clinical Transplantation ABSTRACT 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. 10.1111/ctr.70299 http://creativecommons.org/licenses/by-nc/4.0/
doi_str_mv 10.1111/ctr.70299
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institution Wiley Open Access
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publisher Wiley
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spellingShingle A Comprehensive Assessment of Plasma CXCL9 and CXCL10 in Improving Clinical Prediction Models for Kidney Allograft Rejection
Alvaro Assis de Souza
Dennis A. Hesselink
Carolien C. H. M. Maas
Andrew P. Stubbs
Marian Clahsen‐van Groningen
Carla C. Baan
David van Klaveren
Karin Boer
Clinical Transplantation
A Comprehensive Assessment of Plasma CXCL9 and CXCL10 in Improving Clinical Prediction Models for Kidney Allograft Rejection Alvaro Assis de Souza Dennis A. Hesselink Carolien C. H. M. Maas Andrew P. Stubbs Marian Clahsen‐van Groningen Carla C. Baan David van Klaveren Karin Boer Clinical Transplantation ABSTRACT 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. 10.1111/ctr.70299 http://creativecommons.org/licenses/by-nc/4.0/
title A Comprehensive Assessment of Plasma CXCL9 and CXCL10 in Improving Clinical Prediction Models for Kidney Allograft Rejection
topic Clinical Transplantation
url https://onlinelibrary.wiley.com/doi/10.1111/ctr.70299