Multicenter validation of the CamGFR model for estimated glomerular filtration rate
Abstract
Important oncological management decisions rely on kidney function assessed by serum creatinine-based estimated glomerular filtration rate (eGFR). However, no large-scale multicentre comparison of methods to determine eGFR in patients with cancer are available. To compare the performance of formulas for eGFR based on routine clinical parameters and serum creatinine not calibrated with isotope dilution mass spectrometry (non-IDMS), we studied 3,620 patients with cancer and 166 without cancer who had their GFR measured with an exogenous nuclear tracer at one of seven clinical centres. The mean measured GFR was 86 ml/min. Accuracy of all models was centre-dependent, reflecting inter-centre variability of non-IDMS creatinine measurements. CamGFR was the most accurate model for eGFR (root-mean-squared-error (RMSE) 17.3 ml/min) followed by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) model (RMSE 18.2 ml/min).Important oncological management decisions rely on kidney function assessed by serum creatinine-based estimated glomerular filtration rate (eGFR). However, no large-scale multicentre comparison of methods to determine eGFR in patients with cancer are available. To compare the performance of formulas for eGFR based on routine clinical parameters and serum creatinine not calibrated with isotope dilution mass spectrometry (non-IDMS), we studied 3,620 patients with cancer and 166 without cancer who had their GFR measured with an exogenous nuclear tracer at one of seven clinical centres. The mean measured GFR was 86 ml/min. Accuracy of all models was centre-dependent, reflecting inter-centre variability of non-IDMS creatinine measurements. CamGFR was the most accurate model for eGFR (root-mean-squared-error (RMSE) 17.3 ml/min) followed by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) model (RMSE 18.2 ml/min).Important oncological management decisions rely on kidney function assessed by serum creatinine–based estimated glomerular filtration rate (eGFR). However, no large-scale multicenter comparisons of methods to determine eGFR in patients with cancer are available. To compare the performance of formulas for eGFR based on routine clinical parameters and serum creatinine not calibrated with isotope dilution mass spectrometry, we studied 3620 patients with cancer and 166 without cancer who had their glomerular filtration rate (GFR) measured with an exogenous nuclear tracer at one of seven clinical centers. The mean measured GFR was 86 mL/min. Accuracy of all models was center dependent, reflecting intercenter variability of isotope dilution mass spectrometry–creatinine measurements. CamGFR was the most accurate model for eGFR (root-mean-squared error 17.3 mL/min) followed by the Chronic Kidney Disease Epidemiology Collaboration model (root-mean-squared error 18.2 mL/min).
Citation
Williams , E H , Connell , C M , Weaver , J M J , Beh , I , Potts , H , Whitley , C T , Bird , N , Al-Sayed , T , Fehr , M , Cathomas , R , Bertelli , G , Quinton , A , Lewis , P , Shamash , J , Wilson , P , Dooley , M , Poole , S , Mark , P B , Bookman , M , Earl , H , Jodrell , D , Tavaré , S , Lynch , A & Janowitz , T 2019 , ' Multicenter validation of the CamGFR model for estimated glomerular filtration rate ' , JNCI Cancer Spectrum , vol. 3 , no. 4 , pkz068 . https://doi.org/10.1093/jncics/pkz068
Publication
JNCI Cancer Spectrum
Status
Peer reviewed
ISSN
2515-5091Type
Journal article
Rights
Copyright © The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Description
This work was supported by Cancer Research UK (EHW, TJ: C42738/A24868); National Institute of Health Research Cambridge Biomedical Research Centre (HE); National Institute of Health Research UK Academic Clinical Fellowship (CMC); and National Institutes of Health USA Cancer Center support grant (TJ: 5P30CA045508-31).Collections
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