New Model for Estimating Glomerular Filtration Rate in Patients With Cancer

Author:

Janowitz Tobias1,Williams Edward H.1,Marshall Andrea1,Ainsworth Nicola1,Thomas Peter B.1,Sammut Stephen J.1,Shepherd Scott1,White Jeff1,Mark Patrick B.1,Lynch Andy G.1,Jodrell Duncan I.1,Tavaré Simon1,Earl Helena1

Affiliation:

1. Tobias Janowitz, Edward H. Williams, Stephen J. Sammut, Andy G. Lynch, Duncan I. Jodrell, Simon Tavaré, and Helena Earl, Cancer Research UK Cambridge Institute, Tobias Janowitz, Peter B. Thomas, and Duncan I. Jodrell, University of Cambridge, Addenbrooke’s Hospital, Cambridge; Andrea Marshall, University of Warwick, Coventry; Nicola Ainsworth, Queen Elizabeth Hospital, King’s Lynn; Scott Shepherd, Royal Marsden Hospital, London; Jeff White, NHS Greater Glasgow and Clyde; and Patrick B. Mark, Institute of...

Abstract

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.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

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