Cargando…

New Model for Estimating Glomerular Filtration Rate in Patients With Cancer

PURPOSE: The glomerular filtration rate (GFR) is essential for carboplatin chemotherapy dosing; however, the best method to estimate GFR in patients with cancer is unknown. We identify the most accurate and least biased method. METHODS: We obtained data on age, sex, height, weight, serum creatinine...

Descripción completa

Detalles Bibliográficos
Autores principales: Janowitz, Tobias, Williams, Edward H., Marshall, Andrea, Ainsworth, Nicola, Thomas, Peter B., Sammut, Stephen J., Shepherd, Scott, White, Jeff, Mark, Patrick B., Lynch, Andy G., Jodrell, Duncan I., Tavaré, Simon, Earl, Helena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Clinical Oncology 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562175/
https://www.ncbi.nlm.nih.gov/pubmed/28686534
http://dx.doi.org/10.1200/JCO.2017.72.7578
_version_ 1783257933377699840
author Janowitz, Tobias
Williams, Edward H.
Marshall, Andrea
Ainsworth, Nicola
Thomas, Peter B.
Sammut, Stephen J.
Shepherd, Scott
White, Jeff
Mark, Patrick B.
Lynch, Andy G.
Jodrell, Duncan I.
Tavaré, Simon
Earl, Helena
author_facet Janowitz, Tobias
Williams, Edward H.
Marshall, Andrea
Ainsworth, Nicola
Thomas, Peter B.
Sammut, Stephen J.
Shepherd, Scott
White, Jeff
Mark, Patrick B.
Lynch, Andy G.
Jodrell, Duncan I.
Tavaré, Simon
Earl, Helena
author_sort Janowitz, Tobias
collection PubMed
description PURPOSE: The glomerular filtration rate (GFR) is essential for carboplatin chemotherapy dosing; however, the best method to estimate GFR in patients with cancer is unknown. We identify the most accurate and least biased method. METHODS: We obtained data on age, sex, height, weight, serum creatinine concentrations, and results for GFR from chromium-51 ((51)Cr) EDTA excretion measurements ((51)Cr-EDTA GFR) from white patients ≥ 18 years of age with histologically confirmed cancer diagnoses at the Cambridge University Hospital NHS Trust, United Kingdom. We developed a new multivariable linear model for GFR using statistical regression analysis. (51)Cr-EDTA GFR was compared with the estimated GFR (eGFR) from seven published models and our new model, using the statistics root-mean-squared-error (RMSE) and median residual and on an internal and external validation data set. We performed a comparison of carboplatin dosing accuracy on the basis of an absolute percentage error > 20%. RESULTS: Between August 2006 and January 2013, data from 2,471 patients were obtained. The new model improved the eGFR accuracy (RMSE, 15.00 mL/min; 95% CI, 14.12 to 16.00 mL/min) compared with all published models. Body surface area (BSA)–adjusted chronic kidney disease epidemiology (CKD-EPI) was the most accurate published model for eGFR (RMSE, 16.30 mL/min; 95% CI, 15.34 to 17.38 mL/min) for the internal validation set. Importantly, the new model reduced the fraction of patients with a carboplatin dose absolute percentage error > 20% to 14.17% in contrast to 18.62% for the BSA-adjusted CKD-EPI and 25.51% for the Cockcroft-Gault formula. The results were externally validated. CONCLUSION: In a large data set from patients with cancer, BSA-adjusted CKD-EPI is the most accurate published model to predict GFR. The new model improves this estimation and may present a new standard of care.
format Online
Article
Text
id pubmed-5562175
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher American Society of Clinical Oncology
record_format MEDLINE/PubMed
spelling pubmed-55621752018-03-16 New Model for Estimating Glomerular Filtration Rate in Patients With Cancer Janowitz, Tobias Williams, Edward H. Marshall, Andrea Ainsworth, Nicola Thomas, Peter B. Sammut, Stephen J. Shepherd, Scott White, Jeff Mark, Patrick B. Lynch, Andy G. Jodrell, Duncan I. Tavaré, Simon Earl, Helena J Clin Oncol ORIGINAL REPORTS PURPOSE: The glomerular filtration rate (GFR) is essential for carboplatin chemotherapy dosing; however, the best method to estimate GFR in patients with cancer is unknown. We identify the most accurate and least biased method. METHODS: We obtained data on age, sex, height, weight, serum creatinine concentrations, and results for GFR from chromium-51 ((51)Cr) EDTA excretion measurements ((51)Cr-EDTA GFR) from white patients ≥ 18 years of age with histologically confirmed cancer diagnoses at the Cambridge University Hospital NHS Trust, United Kingdom. We developed a new multivariable linear model for GFR using statistical regression analysis. (51)Cr-EDTA GFR was compared with the estimated GFR (eGFR) from seven published models and our new model, using the statistics root-mean-squared-error (RMSE) and median residual and on an internal and external validation data set. We performed a comparison of carboplatin dosing accuracy on the basis of an absolute percentage error > 20%. RESULTS: Between August 2006 and January 2013, data from 2,471 patients were obtained. The new model improved the eGFR accuracy (RMSE, 15.00 mL/min; 95% CI, 14.12 to 16.00 mL/min) compared with all published models. Body surface area (BSA)–adjusted chronic kidney disease epidemiology (CKD-EPI) was the most accurate published model for eGFR (RMSE, 16.30 mL/min; 95% CI, 15.34 to 17.38 mL/min) for the internal validation set. Importantly, the new model reduced the fraction of patients with a carboplatin dose absolute percentage error > 20% to 14.17% in contrast to 18.62% for the BSA-adjusted CKD-EPI and 25.51% for the Cockcroft-Gault formula. The results were externally validated. CONCLUSION: In a large data set from patients with cancer, BSA-adjusted CKD-EPI is the most accurate published model to predict GFR. The new model improves this estimation and may present a new standard of care. American Society of Clinical Oncology 2017-08-20 2017-07-07 /pmc/articles/PMC5562175/ /pubmed/28686534 http://dx.doi.org/10.1200/JCO.2017.72.7578 Text en © 2017 by American Society of Clinical Oncology http://creativecommons.org/licenses/by/4.0/ Licensed under the Creative Commons Attribution 4.0 License: http://creativecommons.org/licenses/by/4.0/
spellingShingle ORIGINAL REPORTS
Janowitz, Tobias
Williams, Edward H.
Marshall, Andrea
Ainsworth, Nicola
Thomas, Peter B.
Sammut, Stephen J.
Shepherd, Scott
White, Jeff
Mark, Patrick B.
Lynch, Andy G.
Jodrell, Duncan I.
Tavaré, Simon
Earl, Helena
New Model for Estimating Glomerular Filtration Rate in Patients With Cancer
title New Model for Estimating Glomerular Filtration Rate in Patients With Cancer
title_full New Model for Estimating Glomerular Filtration Rate in Patients With Cancer
title_fullStr New Model for Estimating Glomerular Filtration Rate in Patients With Cancer
title_full_unstemmed New Model for Estimating Glomerular Filtration Rate in Patients With Cancer
title_short New Model for Estimating Glomerular Filtration Rate in Patients With Cancer
title_sort new model for estimating glomerular filtration rate in patients with cancer
topic ORIGINAL REPORTS
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562175/
https://www.ncbi.nlm.nih.gov/pubmed/28686534
http://dx.doi.org/10.1200/JCO.2017.72.7578
work_keys_str_mv AT janowitztobias newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT williamsedwardh newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT marshallandrea newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT ainsworthnicola newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT thomaspeterb newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT sammutstephenj newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT shepherdscott newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT whitejeff newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT markpatrickb newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT lynchandyg newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT jodrellduncani newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT tavaresimon newmodelforestimatingglomerularfiltrationrateinpatientswithcancer
AT earlhelena newmodelforestimatingglomerularfiltrationrateinpatientswithcancer