A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation

Background: Serum creatinine concentration is widely used as an index of re nal function, but this concentration is affected by factors other than glom erular filtration rate (GFR). Objective: To develop an equation to predict GFR from serum creatinine conc entration and other factors. Design: Cross-sectional study of GFR, creatinine clearance, serum creatinin e concentration, and demographic and clinical characteristics in patients w ith chronic renal disease. Patients: 1628 patients enrolled in the baseline period of the Modification of Diet in Renal Disease (MDRD) Study, of whom 1070 were randomly selected as the training sample; the remaining 558 patients constituted the validat ion sample. Methods: The prediction equation was developed by stepwise regression appli ed to the training sample. The equation was then tested and compared with o ther prediction equations in the validation sample. Results: To simplify prediction of GFR, the equation included only demograp hic and serum variables. Independent factors associated with a lower GFR in cluded a higher serum creatinine concentration, older age, female sex, nonb lack ethnicity, higher serum urea nitrogen levels, and lower serum albumin levels (P < 0.002 for all factors). The multiple regression model explained 90.3% of the variance in the logarithm of GFR in the validation sample. Me asured creatinine clearance overestimated GFR by 19%, and creatinine cleara nce predicted by the Cockcroft-Gault formula overestimated GFR by 16%. Afte r adjustment for this overestimation, the percentage of variance of the log arithm of GFR predicted by measured creatinine clearance or the Cockcroft-G ault formula was 86.6% and 84.2%, respectively. Conclusion: The equation developed from the MDRD Study provided a more accu rate estimate of GFR in our study group than measured creatinine clearance or other commonly used equations.