Janowitz, T. et al. (2017) New model for estimating glomerular filtration rate in patients with cancer. Journal of Clinical Oncology, (doi: 10.1200/JCO.2017.72.7578) (PMID:28686534)
|
Text
140496.pdf - Published Version Available under License Creative Commons Attribution. 1MB |
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.
Item Type: | Articles |
---|---|
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Mark, Professor Patrick and White, Dr Jeffery |
Authors: | 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., and Earl, H. |
College/School: | College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health College of Medical Veterinary and Life Sciences > School of Cancer Sciences |
Journal Name: | Journal of Clinical Oncology |
Publisher: | American Society of Clinical Oncology |
ISSN: | 0732-183X |
ISSN (Online): | 1527-7755 |
Published Online: | 07 July 2017 |
Copyright Holders: | Copyright © 2017 American Society of Clinical Oncology |
First Published: | First published in Journal of Clinical Oncology 2017 |
Publisher Policy: | Reproduced under a Creative Commons License |
University Staff: Request a correction | Enlighten Editors: Update this record