Lynda A. Szczech, MD, MSCE

Authors and Disclosures

Published: 05/28/2009
Physician Rating: 4.5 stars ( 30 Votes )
Rate This Article:

0 stars

* Print This Print This
* Email This Email this

processing....

Information from Industry
Assess clinically focused product information on Medscape.
Click Here for Product Infosites – Information from Industry.
A New Equation to Estimate Glomerular Filtration Rate

Ann Intern Med. 2009;150:604-612
Levey AS, Stevens LA, Schmid CH, et al
Summary

Creatinine has been, is now, and will be for the foreseeable future our easiest way to monitor kidney function. However, the inadequacies and limitations of creatinine as such a marker are well described. Due to the nonlinear relationship between creatinine and kidney function, as well as the effect of a patient's muscle mass on the association between absolute value of creatinine and kidney function, formulas to approximate kidney function using serum creatinine and proxies for muscle mass are essential.

The Cockcroft-Gault equation was the first widely used formula.[1] Although creatinine clearance using this equation is relatively simple to calculate, it was recognized to overestimate kidney function, and many have raised concerns on the basis of its limited generalizability. Investigators from the Modification of Diet in Renal Disease (MDRD) study subsequently derived a number of formulas to approximate kidney function using that study that performed better than the Cockcroft-Gault formula.[2,3] The formula has been widely applied in both clinical care and research since its publication, but clinicians continue to discuss whether it can be used for patients with clearance of greater than 60 mL/min and with diabetes mellitus.

Given these continued generalizability limitations, Levey and colleagues collaborated with multiple investigators to obtain data from studies in which the glomerular filtration rate (GFR) was measured using exogenous filtration markers and serum creatinine. Ten studies were available and were randomly divided into 2 groups for development of the new estimation equation and the internal validation of the new equation. At the Cleveland Clinical Laboratory, serum creatinine values were recalibrated to standardized creatinine measurements using the Roche enzymatic method. The equation was developed with potential clinical predictor variables of serum creatinine, age, race (black vs white and other), and sex. Additional variables available in some models include diabetes mellitus, previous organ transplantation, and weight.

The dataset used for development of the equation contained 5504 subjects. The mean serum creatinine was 1.65 mg/dL with a mean GFR measured at 68 mL/min, providing a robust representation of patients with milder kidney disease than was possible with the MDRD study. Approximately 29% of participants had diabetes mellitus and 32% were African American. The mean age was 47 years with limited representation of the elderly (9% between 66 and 70 years, and 3% > 71 years).

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula developed is represented as the equation below, in which the values of the constants of a, b, and c vary on the basis of race, sex, and serum creatinine.

GFR = a × (serum creatinine/b) c × (0.993)age

The variable a takes on the following values on the basis of race and sex:

* Black
o Women = 166
o Men = 163
* White/other
o Women = 144
o Men = 141

The variable b takes on the following values on the basis of sex:

* Women = 0.7
* Men = 0.9

The variable c takes on the following values on the basis of sex and creatinine measurement:

* Women
o Serum creatinine ≤ 0.7 mg/dL = -0.329
o Serum creatinine > 0.7 mg/dL = -1.209
* Men
o Serum creatinine ≤ 0.9 mg/dL = -0.411
o Serum creatinine > 0.9 mg/dL = -1.209

The investigators compared the abilities to identify patients with various degrees of kidney disease of the new CKD-EPI formula with the MDRD formula. Although both formulas performed similarly well, in which subjects were misclassified in terms of category of kidney disease, the CKD-EPI formula was more often correct (P < .001). In the separate subset of patients designated to validate the new formula, the CKD-EPI formula demonstrated less bias and improved precision and greater accuracy than the MDRD formula (P < .001), particularly for those patients with an estimated GFR > 60 mL/min. The median difference between measured and estimated GFR was 2.5 mL/min for the CKD-EPI formula and 5.5 mL/min for the MDRD formula (P < .001).

Because of the reduced error of overestimation of kidney function, the CKD-EPI equation yielded a lower estimated prevalence of kidney disease in the National Health and Nutrition Examination Survey (NHANES) dataset. Where the MDRD equation estimated the prevalence of kidney disease at 13.1%, the CKD-EPI formula estimated it slightly lower at a prevalence of 11.5%. This limited extent to which the equation overestimates GFR reflects the major advantage of this newer formula.
Viewpoint

The use of serum creatinine is a cheap and easy way to estimate kidney function. Although the manner in which to transform serum creatinine into an accurate measure of absolute kidney function remains a problem, this analysis takes use 1 step closer. Researchers anticipate that it will be quickly adopted in the clinical community to allow an even more accurate equation of kidney function.