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Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate

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 formula...

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Autores principales: Williams, Edward H, Connell, Claire M, Weaver, James M J, Beh, Ian, Potts, Harry, Whitley, Cameron T, Bird, Nicholas, Al-Sayed, Tamer, Monaghan, Phillip J, Fehr, Martin, Cathomas, Richard, Bertelli, Gianfilippo, Quinton, Amy, Lewis, Paul, Shamash, Jonathan, Wilson, Peter, Dooley, Michael, Poole, Susan, Mark, Patrick B, Bookman, Michael A, Earl, Helena, Jodrell, Duncan, Tavaré, Simon, Lynch, Andy G, Janowitz, Tobias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6846361/
https://www.ncbi.nlm.nih.gov/pubmed/31750418
http://dx.doi.org/10.1093/jncics/pkz068
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author Williams, Edward H
Connell, Claire M
Weaver, James M J
Beh, Ian
Potts, Harry
Whitley, Cameron T
Bird, Nicholas
Al-Sayed, Tamer
Monaghan, Phillip J
Fehr, Martin
Cathomas, Richard
Bertelli, Gianfilippo
Quinton, Amy
Lewis, Paul
Shamash, Jonathan
Wilson, Peter
Dooley, Michael
Poole, Susan
Mark, Patrick B
Bookman, Michael A
Earl, Helena
Jodrell, Duncan
Tavaré, Simon
Lynch, Andy G
Janowitz, Tobias
author_facet Williams, Edward H
Connell, Claire M
Weaver, James M J
Beh, Ian
Potts, Harry
Whitley, Cameron T
Bird, Nicholas
Al-Sayed, Tamer
Monaghan, Phillip J
Fehr, Martin
Cathomas, Richard
Bertelli, Gianfilippo
Quinton, Amy
Lewis, Paul
Shamash, Jonathan
Wilson, Peter
Dooley, Michael
Poole, Susan
Mark, Patrick B
Bookman, Michael A
Earl, Helena
Jodrell, Duncan
Tavaré, Simon
Lynch, Andy G
Janowitz, Tobias
author_sort Williams, Edward H
collection PubMed
description 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).
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spelling pubmed-68463612019-11-18 Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate Williams, Edward H Connell, Claire M Weaver, James M J Beh, Ian Potts, Harry Whitley, Cameron T Bird, Nicholas Al-Sayed, Tamer Monaghan, Phillip J Fehr, Martin Cathomas, Richard Bertelli, Gianfilippo Quinton, Amy Lewis, Paul Shamash, Jonathan Wilson, Peter Dooley, Michael Poole, Susan Mark, Patrick B Bookman, Michael A Earl, Helena Jodrell, Duncan Tavaré, Simon Lynch, Andy G Janowitz, Tobias JNCI Cancer Spectr Brief Communication 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). Oxford University Press 2019-09-19 /pmc/articles/PMC6846361/ /pubmed/31750418 http://dx.doi.org/10.1093/jncics/pkz068 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ 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.
spellingShingle Brief Communication
Williams, Edward H
Connell, Claire M
Weaver, James M J
Beh, Ian
Potts, Harry
Whitley, Cameron T
Bird, Nicholas
Al-Sayed, Tamer
Monaghan, Phillip J
Fehr, Martin
Cathomas, Richard
Bertelli, Gianfilippo
Quinton, Amy
Lewis, Paul
Shamash, Jonathan
Wilson, Peter
Dooley, Michael
Poole, Susan
Mark, Patrick B
Bookman, Michael A
Earl, Helena
Jodrell, Duncan
Tavaré, Simon
Lynch, Andy G
Janowitz, Tobias
Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate
title Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate
title_full Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate
title_fullStr Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate
title_full_unstemmed Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate
title_short Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate
title_sort multicenter validation of the camgfr model for estimated glomerular filtration rate
topic Brief Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6846361/
https://www.ncbi.nlm.nih.gov/pubmed/31750418
http://dx.doi.org/10.1093/jncics/pkz068
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