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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Am J Kidney Dis. Author manuscript; available in PMC 2010 July 1.
Published in final edited form as:
PMCID: PMC2704460
NIHMSID: NIHMS115405

Prevalence of CKD in the United States: GFR Estimating Equations Matter

To the Editor:

The sensitivity analysis by Snyder et al. (1) evaluated prevalence estimates of CKD in the adult general population by using different equations for estimated glomerular filtration rate (eGFR). The prevalence of stages 3 and 4 chronic kidney disease (CKD; eGFR, 15-59 ml/min/1.73 m2) was lower with the Mayo Clinic Quadratic (MCQ) equation (2) at 6.3% than with the MDRD Study equation (3) at 8.3%. As Snyder et al. note, the MCQ equation was developed using approximately two-thirds healthy persons and one-third clinical CKD patients, whereas the MDRD Study equation was developed using only clinical CKD patients. The MCQ was not developed with a standardized serum creatinine assay and Snyder et al. corrected for this using an indirect method.(4) A direct correction based on exchanged frozen serum samples is also available (5) and may lead to different results. Having a universal threshold (<60 ml/min/1.73 m2) for a standard equation (MDRD Study equation) has lead to a consistent literature, but the epidemiology of CKD may be distorted. We found that the inclusion of healthy persons in the sample used to develop an estimating equation led to a higher risk of eGFR <60 ml/min/1.73 m2 in men than in women, whereas an equation developed using only clinical CKD patients led to a higher risk of eGFR <60 ml/min/1.73 m2 in women than in men.(6) The use of demographics in equations to model the non-GFR determinants of serum creatinine among clinical CKD patients may not be transferable to the general population where demographics also reflect risk of CKD.(7) There may not be a single equation that is accurate for both the general population and for nephrology clinics.

Footnotes

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References

1. Snyder JJ, Foley RN, Collins AJ. Prevalence of CKD in the United States: a sensitivity analysis using the National Health and Nutrition Examination Survey (NHANES) 1999-2004. Am J Kidney Dis. 2009;53:218–228. [PMC free article] [PubMed]
2. Rule AD, Larson TS, Bergstralh EJ, Slezak JM, Jacobsen SJ, Cosio FG. Using Serum Creatinine To Estimate Glomerular FIltration Rate: Accuracy in Good Health and in Chronic Kidney Disease. Annals of Internal Medicine. 2004;141:929–937. [PubMed]
3. Levey AS, Coresh J, Greene T, 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;145:247–254. [PubMed]
4. Stevens LA, Manzi J, Levey AS, et al. Impact of creatinine calibration on performance of GFR estimating equations in a pooled individual patient database. Am J Kidney Dis. 2007;50:21–35. [PubMed]
5. Rule AD, Larson TS. Do we need another equation to estimate GFR from serum creatinine in renal allograft recipients? Nephrol Dial Transplant. 2008;23:2427–2428. author reply 2428. [PMC free article] [PubMed]
6. Rule AD, Rodeheffer RJ, Larson TS, et al. Limitations of estimating glomerular filtration rate from serum creatinine in the general population. Mayo Clinic Proceedings. 2006;81:1427–1434. see comment. [PubMed]
7. Rule AD, Bailey KR, Schwartz GL, Khosla S, Lieske JC, Melton LJ. For estimating creatinine clearance measuring muscle mass gives better results than those based on demographics. Kidney Int. 2009 [PMC free article] [PubMed]