GFR estimation: from physiology to public health.
Estimating glomerular filtration rate (GFR) is essential for clinical practice, research, and public health. Appropriate interpretation of estimated GFR (eGFR) requires understanding the principles of physiology, laboratory medicine, epidemiology, and biostatistics used in the development and validation of GFR estimating equations. Equations developed in diverse populations are less biased at higher GFRs than equations developed in chronic kidney disease (CKD) populations and are more appropriate for general use. Equations that include multiple endogenous filtration markers are more precise than equations including a single filtration marker. The CKD-EPI (CKD Epidemiology Collaboration) equations are the most accurate GFR estimating equations that have been evaluated in large diverse populations and are applicable for general clinical use. The 2009 CKD-EPI creatinine equation is more accurate in estimating GFR and prognosis than the 2006 MDRD (Modification of Diet in Renal Disease) Study equation and provides lower estimates of prevalence of decreased eGFR. It is useful as a "first test" for decreased eGFR and should replace the MDRD Study equation for routine reporting of serum creatinine-based eGFR by clinical laboratories. The 2012 CKD-EPI cystatin C equation is as accurate as the 2009 CKD-EPI creatinine equation in estimating GFR, does not require specification of race, and may be more accurate in patients with decreased muscle mass. The 2012 CKD-EPI creatinine-cystatin C equation is more accurate than the 2009 CKD-EPI creatinine and 2012 CKD-EPI cystatin C equations and is useful as a confirmatory test for decreased eGFR as determined by serum creatinine-based eGFR. Further improvement in GFR estimating equations will require development in more broadly representative populations, including diverse racial and ethnic groups, use of multiple filtration markers, and evaluation using statistical techniques to compare eGFR to "true GFR."
William B. Schwartz Division of Nephrology, Tufts Medical Center, Department of Medicine, Tufts University School of Medicine, Boston, MA. Electronic address: alevey@tuftsmedicalcenter.org.
Andrew S
AS
Levey
William B. Schwartz Division of Nephrology, Tufts Medical Center, Department of Medicine, Tufts University School of Medicine, Boston, MA.
Lesley A
LA
Inker
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, MD.
Josef
J
Coresh
D014943:Global Health; D005919:Glomerular Filtration Rate / Q000502:physiology*; D006801:Humans; D007677:Kidney Function Tests; D008433:Mathematics; D015995:Prevalence; D011379:Prognosis; D011634:Public Health; D051436:Renal Insufficiency, Chronic / Q000453:epidemiology / Q000503:physiopathology*
Estimated glomerular filtration rate (eGFR); GFR estimating equation; chronic kidney disease; filtration marker; kidney function; public health; renal insufficiency