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 m2), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m2), 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 m2 (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m2, 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.
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Author, Article and Disclosure Information
Acknowledgment: The authors thank Aghogho Okparavero, MBBS, MPH, for his assistance in communications and manuscript preparation.
Grant Support: By grants UO1 DK 053869, UO1 DK 067651, and UO1 DK 35073 as part of a cooperative agreement with the National Institute of Diabetes and Digestive and Kidney Diseases.
Disclosures:Stock ownership or options (other than mutual funds): J.W. Kusek (Pfizer, Eli Lilly, DeCode Genetics).
Reproducible Research Statement:Study protocol: Available from Dr. Levey (address below). Statistical code and data set: Not available.
Corresponding Author: Andrew S. Levey, MD, Division of Nephrology, Tufts Medical Center, 800 Washington Street, Box 391, Boston, MA 02111.
Current Author Addresses: Drs. Levey and Stevens and Ms. Zhang: Division of Nephrology, Tufts Medical Center, 800 Washington Street, Box 391, Boston, MA 02111.
Dr. Schmid: The Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street, Box 063, Boston, MA 02111.
Mr. Castro and Dr. Coresh: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 2024 East Monument Street, Suite 2-600, Baltimore, MD 21205.
Dr. Feldman: Clinical Epidemiology Unit, University of Pennsylvania School of Medicine, 923 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104.
Drs. Kusek and Eggers: Kidney and Urology Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 6707 Democracy Boulevard, Bethesda, MD 20817.
Dr. Van Lente: Department of Clinical Pathology, Cleveland Clinic Foundation, 9500 Euclid Avenue, Mail Code L11, Cleveland, OH 44195.
Dr. Greene: Division of Clinical Epidemiology, 30 North 1900 East, Room AC221, Salt Lake City, UT 84132.
Author Contributions: Conception and design: A.S. Levey, L.A. Stevens, C.H. Schmid, H.I. Feldman, F. Van Lente, T. Greene, J. Coresh.
Analysis and interpretation of the data: A.S. Levey, L.A. Stevens, C.H. Schmid, H.I. Feldman, P. Eggers, F. Van Lente, T. Greene, J. Coresh.
Drafting of the article: A.S. Levey, C.H. Schmid, F. Van Lente, J. Coresh.
Critical revision of the article for important intellectual content: A.S. Levey, L.A. Stevens, C.H. Schmid, H.I. Feldman, J.W. Kusek, P. Eggers, T. Greene, J. Coresh.
Final approval of the article: A.S. Levey, L.A. Stevens, C.H. Schmid, Y. Zhang, H.I. Feldman, J.W. Kusek, T. Greene, J. Coresh.
Provision of study materials or patients: A.S. Levey.
Statistical expertise: C.H. Schmid, Y. Zhang, T. Greene, J. Coresh.
Obtaining of funding: A.S. Levey, J.W. Kusek, P. Eggers, J. Coresh.
Administrative, technical, or logistic support: A.S. Levey, L.A. Stevens, Y. Zhang, P. Eggers.
Collection and assembly of data: A.S. Levey, L.A. Stevens, Y. Zhang, F. Van Lente.

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