New model for estimating glomerular filtration rate in patients with cancer
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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 (51Cr) EDTA excretion measurements (51Cr-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. 51Cr-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.
Janowitz , T , Williams , E H , Marshall , A , Ainsworth , N , Thomas , P B , Sammut , S J , Shepherd , S , White , J , Mark , P B , Lynch , A G , Jodrell , D I , Tavaré , S & Earl , H 2017 , ' New model for estimating glomerular filtration rate in patients with cancer ' , Journal of Clinical Oncology , vol. 35 , no. 24 , pp. 2798-2805 . https://doi.org/10.1200/JCO.2017.72.7578
Journal of Clinical Oncology
© 2017 by American Society of Clinical Oncology. Licensed under the Creative Commons Attribution 4.0 License: http://creativecommons.org/licenses/by/4.0/
DescriptionT.J. was supported by the Wellcome Trust Translational Medicine and Therapeutics Programme and the University of Cambridge, Department of Oncology (RJAG/076). H.E. was supported by the National Institute of Health Research Cambridge Biomedical Research Centre and the University of Cambridge.
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