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dc.contributor.authorWilliams, Edward H.
dc.contributor.authorConnell, Claire M.
dc.contributor.authorWeaver, James M. J.
dc.contributor.authorBeh, Ian
dc.contributor.authorPotts, Harry
dc.contributor.authorWhitley, Cameron T.
dc.contributor.authorBird, Nicholas
dc.contributor.authorAl-Sayed, Tamer
dc.contributor.authorFehr, Martin
dc.contributor.authorCathomas, Richard
dc.contributor.authorBertelli, Gianfilippo
dc.contributor.authorQuinton, Amy
dc.contributor.authorLewis, Paul
dc.contributor.authorShamash, Jonathan
dc.contributor.authorWilson, Peter
dc.contributor.authorDooley, Michael
dc.contributor.authorPoole, Susan
dc.contributor.authorMark, Patrick B.
dc.contributor.authorBookman, Michael
dc.contributor.authorEarl, Helena
dc.contributor.authorJodrell, Duncan
dc.contributor.authorTavaré, Simon
dc.contributor.authorLynch, Andy
dc.contributor.authorJanowitz, Tobias
dc.date.accessioned2020-01-06T11:30:05Z
dc.date.available2020-01-06T11:30:05Z
dc.date.issued2019-12
dc.identifier.citationWilliams , 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/pkz068en
dc.identifier.issn2515-5091
dc.identifier.otherPURE: 259452795
dc.identifier.otherPURE UUID: 99175122-e0c8-4672-9cfc-8149b6eabce2
dc.identifier.otherORCID: /0000-0002-7876-7338/work/63381025
dc.identifier.otherWOS: 000503271700015
dc.identifier.otherScopus: 85087185771
dc.identifier.urihttp://hdl.handle.net/10023/19221
dc.descriptionThis 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).en
dc.description.abstractImportant 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).
dc.format.extent4
dc.language.isoeng
dc.relation.ispartofJNCI Cancer Spectrumen
dc.rightsCopyright © 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.en
dc.subjectRC0254 Neoplasms. Tumors. Oncology (including Cancer)en
dc.subject3rd-DASen
dc.subject.lccRC0254en
dc.titleMulticenter validation of the CamGFR model for estimated glomerular filtration rateen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.Statisticsen
dc.contributor.institutionUniversity of St Andrews.Sir James Mackenzie Institute for Early Diagnosisen
dc.contributor.institutionUniversity of St Andrews.Cellular Medicine Divisionen
dc.contributor.institutionUniversity of St Andrews.School of Medicineen
dc.identifier.doihttps://doi.org/10.1093/jncics/pkz068
dc.description.statusPeer revieweden


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