» Articles » PMID: 20515483

MDRD or CKD-EPI Study Equations for Estimating Prevalence of Stage 3 CKD in Epidemiological Studies: Which Difference? Is This Difference Relevant?

Overview
Journal BMC Nephrol
Publisher Biomed Central
Specialty Nephrology
Date 2010 Jun 3
PMID 20515483
Citations 17
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Prevalence of stage 3 chronic kidney disease (CKD) is increasing according to the NHANES study. Prevalence has been calculated using the MDRD study equation for estimating glomerular filtration rate (GFR). Recently, a new estimator based on creatinine, the CKD-EPI equation, has been proposed which is presumed to better perform in normal GFR ranges. The aim of the study was to measure the difference in prevalence of stage 3 CKD in a population using either the MDRD or the CKD-EPI study equations.

Methods: CKD screening is organized in the Province of Liège, Belgium. On a voluntary basis, people aged between 45 and 75 years are invited to be screened. GFR is estimated by the MDRD study equation and by the "new" CKD-EPI equations.

Results: The population screened consisted in 1992 people (47% of men). Mean serum creatinine was 0.86 +/- 0.20 mg/dL. The prevalence of stage 3 CKD in this population using the MDRD or the CKD-EPI equations was 11.04 and 7.98%, respectively. The prevalence of stage 3 CKD is significantly higher with the MDRD study equation (p < 0,0012).

Conclusions: Prevalence of stage 3 CKD varies strongly following the method used for estimating GFR, MDRD or CKD-EPI study equations. Such discrepancies are of importance and must be confirmed and explained by additional studies using GFR measured with a reference method.

Citing Articles

Accuracy of the New Creatinine-based Equations for Estimating Glomerular Filtration Rate in Koreans.

Jeong T, Hong J, Lee W, Chun S, Min W Ann Lab Med. 2022; 43(3):244-252.

PMID: 36544336 PMC: 9791020. DOI: 10.3343/alm.2023.43.3.244.


Prevalence of impaired renal function and determinants in the southwest of Iran.

Alvand S, Abolnezhadian F, Alatab S, Mohammadi Z, Hayati F, Noori M BMC Nephrol. 2021; 22(1):276.

PMID: 34376157 PMC: 8353841. DOI: 10.1186/s12882-021-02484-x.


Effect of Underlying Renal Disease on Nutritional and Metabolic Profile of Older Adults with Reduced Renal Function.

Lai S, Amabile M, Altieri S, Mastroluca D, Lai C, Aceto P Front Nutr. 2017; 4:4.

PMID: 28367435 PMC: 5355471. DOI: 10.3389/fnut.2017.00004.


Methodology used in studies reporting chronic kidney disease prevalence: a systematic literature review.

Bruck K, Jager K, Dounousi E, Kainz A, Nitsch D, Arnlov J Nephrol Dial Transplant. 2015; 30 Suppl 4:iv6-16.

PMID: 26209739 PMC: 4514069. DOI: 10.1093/ndt/gfv131.


Presence of early CKD-related metabolic complications predict progression of stage 3 CKD: a case-controlled study.

Chase H, Hirsch J, Mohan S, Rao M, Radhakrishnan J BMC Nephrol. 2014; 15:187.

PMID: 25431293 PMC: 4258953. DOI: 10.1186/1471-2369-15-187.


References
1.
Mazzachi B, Peake M, Ehrhardt V . Reference range and method comparison studies for enzymatic and Jaffé creatinine assays in plasma and serum and early morning urine. Clin Lab. 2000; 46(1-2):53-5. View

2.
Hallan S, Coresh J, Astor B, Asberg A, Powe N, Romundstad S . International comparison of the relationship of chronic kidney disease prevalence and ESRD risk. J Am Soc Nephrol. 2006; 17(8):2275-84. DOI: 10.1681/ASN.2005121273. View

3.
Froissart M, Rossert J, Jacquot C, Paillard M, Houillier P . Predictive performance of the modification of diet in renal disease and Cockcroft-Gault equations for estimating renal function. J Am Soc Nephrol. 2005; 16(3):763-73. DOI: 10.1681/ASN.2004070549. View

4.
Perrone R, Madias N, Levey A . Serum creatinine as an index of renal function: new insights into old concepts. Clin Chem. 1992; 38(10):1933-53. View

5.
Lamb E, Webb M, ORiordan S . Using the modification of diet in renal disease (MDRD) and Cockcroft and Gault equations to estimate glomerular filtration rate (GFR) in older people. Age Ageing. 2007; 36(6):689-92. DOI: 10.1093/ageing/afm121. View