A New Equation to Estimate Glomerular Filtration Rate

  1. Andrew S. Levey, MD;
  2. Lesley A. Stevens, MD, MS;
  3. Christopher H. Schmid, PhD;
  4. Yaping (Lucy) Zhang, MS;
  5. Alejandro F. Castro III, MPH;
  6. Harold I. Feldman, MD, MSCE;
  7. John W. Kusek, PhD;
  8. Paul Eggers, PhD;
  9. Frederick Van Lente, PhD;
  10. Tom Greene, PhD;
  11. Josef Coresh, MD, PhD, MHS; and
  12. for the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration)*
  1. From Tufts Medical Center, Boston, Massachusetts; Johns Hopkins University, Baltimore, Maryland; University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania; National Institutes of Health, Bethesda, Maryland; Cleveland Clinic Foundation, Cleveland, Ohio; and University of Utah, Salt Lake City, Utah.

    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 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.

    Article and Author 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.

    • Potential Financial Conflicts of Interest: 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.

    • Requests for Single Reprints: 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.

    • ↵* For a list of other CKD-EPI staff and collaborators, see the Appendix.

    Responses to this article

    • GFR estimation using the CKD-EPI equation
      • Andrew S Levey and
      • Lesley A. Stevens, MD, MS and Josef Coresh, MD, PhD
      Ann Intern Med published online October 26, 2009
    • Prevalence of chronic kidney disease by the new CKD-EPI and the MDRD study equations in Asians
      • Charumathi Sabanayagam and
      • Tien Y Wong, MD, PhD, E Shyong Tai, MB.ChB, MRCP
      Ann Intern Med published online October 26, 2009
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    1. Ann Intern Med May 5, 2009 vol. 150 no. 9 604-612
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