Clinical performance of the iPREDICTLIVING tool for the prediction of the post‐transplant recipient and living donor outcomes in a European cohort

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Auteurs principaux: Manuela Almeida, Catarina Ribeiro, José Silvano, Sofia Pedroso, Sandra Tafulo, La Salete Martins, Miguel Ramos, Jorge Malheiro
Format: Artículo Open Access
Publié: Wiley 2024
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author Manuela Almeida
Catarina Ribeiro
José Silvano
Sofia Pedroso
Sandra Tafulo
La Salete Martins
Miguel Ramos
Jorge Malheiro
author_facet Manuela Almeida
Catarina Ribeiro
José Silvano
Sofia Pedroso
Sandra Tafulo
La Salete Martins
Miguel Ramos
Jorge Malheiro
Manuela Almeida
Catarina Ribeiro
José Silvano
Sofia Pedroso
Sandra Tafulo
La Salete Martins
Miguel Ramos
Jorge Malheiro
collection Wiley Open Access
contents Clinical performance of the iPREDICTLIVING tool for the prediction of the post‐transplant recipient and living donor outcomes in a European cohort Manuela Almeida Catarina Ribeiro José Silvano Sofia Pedroso Sandra Tafulo La Salete Martins Miguel Ramos Jorge Malheiro Clinical Transplantation AbstractA living donor kidney transplant (LDKT) is the best treatment for ESRD. A prediction tool based on clinical and demographic data available pre‐KT was developed in a Norwegian cohort with three different models to predict graft loss, recipient death, and donor candidate's risk of death, the iPREDICTLIVING tool. No external validations are yet available. We sought to evaluate its predictive performance in our cohort of 352 pairs LKDT submitted to KT from 1998 to 2019. The model for censored graft failure (CGF) showed the worse discriminative performance with Harrell's C of .665 and a time‐dependent AUC of .566, with a calibration slope of .998. For recipient death, at 10 years, the model had a Harrell's C of .776, a time‐dependent AUC of .773, and a calibration slope of 1.003. The models for donor death were reasonably discriminative, although with a poor calibration, particularly for 20 years of death, with a Harrell's C of .712 and AUC of .694 with a calibration slope of .955. These models have moderate discriminative and calibration performance in our population. The tool was validated in this Northern Portuguese cohort, Caucasian, with a low incidence of diabetes and other comorbidities. It can improve the informed decision‐making process at the living donor consultation joining clinical and other relevant information. 10.1111/ctr.15283 http://creativecommons.org/licenses/by-nc/4.0/
doi_str_mv 10.1111/ctr.15283
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institution Wiley Open Access
license_str_mv http://creativecommons.org/licenses/by-nc/4.0/
publishDate 2024
publisher Wiley
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spellingShingle Clinical performance of the iPREDICTLIVING tool for the prediction of the post‐transplant recipient and living donor outcomes in a European cohort
Manuela Almeida
Catarina Ribeiro
José Silvano
Sofia Pedroso
Sandra Tafulo
La Salete Martins
Miguel Ramos
Jorge Malheiro
Clinical Transplantation
Clinical performance of the iPREDICTLIVING tool for the prediction of the post‐transplant recipient and living donor outcomes in a European cohort Manuela Almeida Catarina Ribeiro José Silvano Sofia Pedroso Sandra Tafulo La Salete Martins Miguel Ramos Jorge Malheiro Clinical Transplantation AbstractA living donor kidney transplant (LDKT) is the best treatment for ESRD. A prediction tool based on clinical and demographic data available pre‐KT was developed in a Norwegian cohort with three different models to predict graft loss, recipient death, and donor candidate's risk of death, the iPREDICTLIVING tool. No external validations are yet available. We sought to evaluate its predictive performance in our cohort of 352 pairs LKDT submitted to KT from 1998 to 2019. The model for censored graft failure (CGF) showed the worse discriminative performance with Harrell's C of .665 and a time‐dependent AUC of .566, with a calibration slope of .998. For recipient death, at 10 years, the model had a Harrell's C of .776, a time‐dependent AUC of .773, and a calibration slope of 1.003. The models for donor death were reasonably discriminative, although with a poor calibration, particularly for 20 years of death, with a Harrell's C of .712 and AUC of .694 with a calibration slope of .955. These models have moderate discriminative and calibration performance in our population. The tool was validated in this Northern Portuguese cohort, Caucasian, with a low incidence of diabetes and other comorbidities. It can improve the informed decision‐making process at the living donor consultation joining clinical and other relevant information. 10.1111/ctr.15283 http://creativecommons.org/licenses/by-nc/4.0/
title Clinical performance of the iPREDICTLIVING tool for the prediction of the post‐transplant recipient and living donor outcomes in a European cohort
topic Clinical Transplantation
url https://onlinelibrary.wiley.com/doi/10.1111/ctr.15283