Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2009 May 5;150(9):604-12.
doi: 10.7326/0003-4819-150-9-200905050-00006.

A new equation to estimate glomerular filtration rate

Andrew S Levey  1 , Lesley A Stevens, Christopher H Schmid, Yaping Lucy Zhang, Alejandro F Castro 3rd, Harold I Feldman, John W Kusek, Paul Eggers, Frederick Van Lente, Tom Greene, Josef Coresh; CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration)
Affiliations

A new equation to estimate glomerular filtration rate

Andrew S Levey et al. Ann Intern Med. .

Erratum in

  • Ann Intern Med. 2011 Sep 20;155(6):408

Abstract

Background: Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values.

Objective: To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.

Design: Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates.

Setting: Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006.

Participants: 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES.

Measurements: GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age.

Results: In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%).

Limitation: The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR.

Conclusion: The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use.

Primary funding source: National Institute of Diabetes and Digestive and Kidney Diseases.

PubMed Disclaimer

Conflict of interest statement

Disclosure of conflicts of interest: We have received confirmation from Drs. Levey, Stevens, Schmid, Feldman, Kusek, Eggers, Greene, Coresh and Ms. Zhang that they have returned completed conflicts of interest forms to Annals. We are awaiting confirmation from Dr. Van Lente and Mr. Castro.

Figures

Figure 1
Figure 1. Comparison of performance of Modification of Diet in Renal Disease (MDRD) Study and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations by estimated GFR in the external validation dataset
Panel 1. Measured vs. estimated GFR. Panel 2. Difference between measured and estimated vs. estimated GFR. Shown are smoothed regression line and 95% CI (computed using the lowess smoothing function in R), using quantile regression, excluding lowest and highest 2.5% of estimated GFR values. To convert GFR from mL/min/1.73 m2 to mL/s/m2, multiply by 0.0167.
See this image and copyright information in PMC

Comment in

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis. 2002;39(2):S1–266. - PubMed
    1. Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney function - measured and estimated glomerular filtration rate. N Engl J Med. 2006;354:2473–83. - PubMed
    1. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130(6):461–470. - PubMed
    1. Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. 2006;145(4):247–54. - PubMed
    1. Miller WG. Reporting estimated GFR: a laboratory perspective. Am J Kidney Dis. 2008;52(4):645–8. - PubMed

Publication types