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Scand J Clin Lab Invest Suppl. 2008;241:30-8. doi: 10.1080/00365510802141140.

Reliability of GFR formulas based on serum creatinine, with special reference to the MDRD Study equation.

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1
Welch Center for Prevention, Epidemiology and Clinical Research, Department of Epidemiology, Medicine and Biostatistics, The Johns Hopkins Medical Institutions, Baltimore, MD 21287, USA. coresh@jhu.edu

Abstract

Estimation of glomerular filtration rate (GFR) is central to the diagnosis, evaluation and management of chronic kidney disease (CKD). This review summarizes data on the performance of equations using serum creatinine to estimate GFR, particularly the Modification of Diet in Renal Disease (MDRD) Study equation. The size of studies evaluating GFR estimation equations and their level of sophistication in estimating bias, precision, validity and sensitivity to the source population have improved over the past decade. We update our review from 2006, which included 7 studies with over 500 individuals and 12 studies with 50-499 individuals with measured GFR evaluating the MDRD Study and Cockcroft-Gault equations. More recent studies include an individual level pooling analysis of 5504 participants in 10 studies which showed that creatinine calibration to reference methods improved the performance of the MDRD Study equation but increased bias for the Cockcroft-Gault equation. The MDRD Study equation had a bias of 3.0 %, interquartile range of 29.0 % and percentage of estimates within 30 % of the measured GFR value (P(30)) of 82 % for estimates below 60 mL/(min x 1.73 m(2)). Above this value, the bias was greater (8.7 %) and estimates are less useful since 30 % error is a large absolute error in GFR. Results vary across studies but are generally similar with disappointing performance in the high GFR range, which is of particular interest in early diabetic nephropathy. New equations using serum creatinine can reduce the bias present in the high GFR range but are unlikely to dramatically improve precision, suggesting a need for additional markers. Finally, algorithms are needed to tailor clinical practice based on data from GFR estimates and other participant characteristics, including the source population and level of proteinuria.

PMID:
18569962
DOI:
10.1080/00365510802141140
[Indexed for MEDLINE]
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