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  5. #5465 RACE-FREE EGFR EQUATION IN KIDNEY RECIPIENTS: A DEVELOPMENT AND VALIDATION STUDY

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Article
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2023

#5465 RACE-FREE EGFR EQUATION IN KIDNEY RECIPIENTS: A DEVELOPMENT AND VALIDATION STUDY

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en
2023
Vol 38 (Supplement_1)
Vol. 38
DOI: 10.1093/ndt/gfad063c_5465

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Giuseppe Remuzzi
Giuseppe Remuzzi

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Marc Raynaud
Solaf Al Awadhi
Ivana Jurić
+24 more

Abstract

Abstract Background and Aims To assess the performances of the current eGFR equations, including the race-free CKD-EPI-2021, in the kidney transplant population, and compare these performances to a race-free kidney-recipient-specific (KRS) GFR equation. Method We included adult kidney recipients transplanted between 01/01/2000 and 01/01/2021 in 17 academic cohorts in Europe, the USA and Australia comprising 14 transplant centres and three clinical trials. Measured GFRs (mGFR) were assessed using 51Cr-EDTA, 99Tc-DTPA, inulin, iothalamate or iohexol clearance, according to the local practice. A KRS GFR equation was developed using additive and multiplicative stepwise linear regressions and its performance was compared to those of the current GFR equations. The performances were assessed with the P30 and the correct classification of chronic kidney disease (CKD) stage metrics. Results The study included 15 489 patients, having 50 464 GFR values both measured and estimated by creatinine-based equations. Among the current GFR equations, race-free CKD-EPI-2021 equation showed the lowest performance compared with MDRD and CKD-EPI-2009 equations. We then built a race-free KRS GFR equation based on an additive model including creatinine, age, and sex. We showed that using race did not increase the performance of the equation. We found that the race-free KRS GFR equation showed significantly improved performance compared with the race-free CKD-EPI-2021 equation and performed well in the external validation cohorts (P30 ranging from 73.0% to 91.3%). Finally, we showed that the race-free KRS GFR equation performed well in a series of kidney transplant recipient subpopulations stratified by race, sex, age, body mass index, donor type, therapeutics, creatinine and GFR measurement methods and timing. Based on these results we developed an online application that estimates GFR based on recipient age, sex and creatinine: https://transplant-prediction-system.shinyapps.io/eGFR_equation_KTX/ Conclusion Using multiple, international cohorts of kidney recipients, we developed and validated a new race-free KRS GFR equation that demonstrated high accuracy and outperformed the race-free CKD-EPI-2021 equation developed in individuals with native kidneys.

How to cite this publication

Marc Raynaud, Solaf Al Awadhi, Ivana Jurić, Gillian Divard, Yannis Lombardi, Nikolina Bašić‐Jukić, Olivier Aubert, Laurence Dubourg, Ingrid Masson, Christophe Mariat, Dominique Prié, Vincent Pernin, Timothy S. Larson, Mark D. Stegall, Boris Bikbov, Piero Ruggenenti, Laurent Mesnard, Arthur J. Matas, Brian J. Nankivell, Stephan J. L. Bakker, Christophe Legendre, Nassim Kamar, Flavio Vincenti, Giuseppe Remuzzi, Andrew Bentall, Carmen Lefaucheur, Alexandre Loupy (2023). #5465 RACE-FREE EGFR EQUATION IN KIDNEY RECIPIENTS: A DEVELOPMENT AND VALIDATION STUDY. , 38(Supplement_1), DOI: https://doi.org/10.1093/ndt/gfad063c_5465.

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Publication Details

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Article

Year

2023

Authors

27

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0

Total Files

0

Language

en

DOI

https://doi.org/10.1093/ndt/gfad063c_5465

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