American Journal of Kidney Diseases
Volume 56, Issue 4 , Pages 802-804, October 2010

Estimation of GFR: A Comparison of New and Established Equations

published online 01 September 2010.

Article Outline

 

To the Editor:

Estimating glomerular filtration rate (GFR) using the Cockcroft-Gault (CG) or Modification of Diet in Renal Disease (MDRD) Study equation is recommended for assessing kidney function.1 These equations include serum creatinine (Cr) together with variables such as age, sex, ethnicity, and body weight.1 The CG formula overestimates kidney function because it was designed for Cr clearance estimation on the basis of ideal weight.2, 3 The MDRD Study equation has low accuracy in healthy persons because it was developed in patients with kidney disease.4, 5 The quadratic6 and CKD Epidemiology Collaboration (CKD-EPI)7 equations were proposed to improve the accuracy of estimated GFR (eGFR) calculation. Here, we evaluate their performance over a wide range of GFRs, assessed using inulin clearance in adults with and without kidney disease. Because Cr generation is a major confounder of all Cr-based estimating equations,5 the equations' performance also was evaluated according to observed Cr excretion rate.

Inulin clearance was measured in the morning after an overnight fast. The test included urine collection using bladder catheterization, intravenous administration of inulin, 90-minute equilibration, and two 45-minute clearance periods that were averaged for calculation of measured GFR (mGFR). Serum samples were collected at the start of the test and frozen at −20°C; serum Cr is stable during long-term storage and after repeated thawing-refreezing.8 Serum Cr was measured using an automated biochemical analyzer (Bayer Express Plus; Bayer Diagnostics) using a kinetic alkaline picrate assay with isotope-dilution mass spectrometry (IDMS)-traceable standardization.8 Data collection included sex, age, type of kidney disease, weight and height for calculation of body mass index and body surface area, and 24-hour urinary Cr as an index of Cr generation. The CG, quadratic, and CKD-EPI equations were used as reported,2, 6, 7 and the IDMS-traceable 4-variable version of the MDRD Study equation was used.9

Performance was evaluated using bias (mGFR – eGFR) and absolute percentage of bias (absolute value of the bias expressed as percentage of mGFR). ANOVA and χ2 analysis were used for unpaired comparisons (numerical and categorical variables, respectively), and t test and McNemar test, for paired comparisons (numerical and categorical variables, respectively). Trends of linearity in ANOVA or χ2 analysis and regression analysis were used to investigate the relation of bias with Cr excretion.

The study cohort included 356 white persons (209 men) aged 18-88 years (mean, 47.0 ± 14.4 [SD] years); 174 individuals had kidney disease (142 with mGFR <60 mL/min). Nephropathy diagnoses included glomerular disease (40), nephroangiosclerosis (18), diabetic nephropathy (26), polycystic disease (15), pyelonephritis (6), and other/unknown (69). The 182 individuals without a diagnosis of kidney disease and with mGFR ≥60 mL/min included 137 patients with nonrenal diseases and 45 healthy volunteers or candidate kidney donors.

As listed in Table 1, mean bias was not different from zero using the CKD-EPI equation, but GFR was overestimated using the MDRD Study equation and underestimated using the CG and quadratic equations. Comparing those with mGFR <60 and ≥60 mL/min, mean bias was similar using the CKD-EPI equation (+1.0 vs +0.7 mL/min/1.73 m2; P = 0.8), but differed by 4 mL/min (+2.8 vs +6.8 mL/min/1.73 m2; P = 0.01) and ≥9 mL/min (P < 0.001) using the MDRD Study and CG/quadratic equations, respectively.

Table 1. Comparison of Performance Among the 4 GFR Estimating Equations in the Entire Cohort
CGMDRD StudyQuadraticCKD-EPI
eGFR (mL/min/1.73 m2)83.9±45.166.3±34.882.1±43.270.6±36.3
Bias (mL/min/1.73 m2)−12.4±22.7a+5.2±14.9b−10.7±17.5a+0.9±13.2c
Absolute percent bias28.3±24.317.3±11.322.9±16.715.8±11.5d
Prevalence with
P10 (%)24.230.928.437.1e
P20 (%)44.460.450.067.1f
P30 (%)64.387.468.888.2g

Note: mGFR ranged from 8-159 mL/min/1.73 m2 (mean ± SD, 71.5 ± 36.3).

Abbreviations and definitions: CG, Cockcroft-Gault; CI, confidence interval; CKD-EPI, CKD Epidemiology Collaboration; eGFR, estimated glomerular filtration rate; MDRD, Modification of Diet in Renal Disease; mGFR, measured glomerular filtration rate; Pn, eGFR within n% of mGFR; absolute percent bias is the absolute value of the bias as a percent of mGFR.

aSignificant overestimate (95% CI of bias is −14.8 to −10.0 for the CG equation and −12.5 to −8.9 for the quadratic equation).

bSignificant underestimate (95% CI of bias is +4.1 to +7.1).

cNot significantly different from zero (95% CI of bias is −0.5 to +2.3).

dP < 0.001 vs CG, MDRD Study, and quadratic equations.

eP < 0.001 vs CG, P = 0.03 vs MDRD Study, and P = 0.009 vs quadratic equation.

fP < 0.001 vs CG, P = 0.009 vs MDRD Study, and P < 0.001 vs quadratic equation.

gP < 0.001 vs CG and quadratic equations; nonsignificant (P = 0.7) vs MDRD Study equation.

Mean absolute percentage of bias was lower with the CKD-EPI than the other equations (Table 1). When eGFRCG was corrected for mean bias found in this cohort, mean absolute percentage of bias of the CG formula was 26.4%, a value higher than the CKD-EPI equation (P < 0.001). Mean absolute percentage of bias of measured Cr clearance was 30.5% (P < 0.001 vs equations). Estimates with absolute percentage of bias <10%, <20%, and <30% were more prevalent using the CKD-EPI than the other equations (Table 1).

Quartiles of 24-hour urinary Cr were defined for sex and decade of age to have subgroups with similar sex and age distribution (Fig 1). From quartile 1 to 4, there was an increase in body mass and mean bias using the MDRD Study and CKD-EPI equations, but not using the CG and quadratic formulas. In sex- and age-controlled regression, a difference of 0.4 mg/min in urinary Cr (equal to the SD in population-based data10) was associated with a difference in the bias of the MDRD Study (9.4 mL/min; 95% CI, 6.5-12.3) and CKD-EPI (7.0 mL/min; 95% CI, 4.3-9.7) equations, but not the CG and quadratic formulas (not shown).

  • View full-size image.
  • Figure 1. 

    Mean bias by quartile of 24-hour urinary creatinine (Cr) excretion using the Cockcroft-Gault (CG), Modification of Diet in Renal Disease (MDRD) Study, quadratic, and CKD Epidemiology Collaboration (CKD-EPI) equations. The broken line is the identity line (no difference between mGFR and eGFR). Table shows urinary Cr excretion, sex, age, weight, and height (mean or prevalence) by quartile. Definition of quartiles was done separately for sex and age decade.

These data suggest that the CKD-EPI equation improves eGFR calculation by reducing the inaccuracy of estimates in the normal-high range. The accuracy of the CKD-EPI equation varies according to level of Cr excretion, and in our sample was less accurate at higher Cr excretion.

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Acknowledgements 

The corresponding author, Massimo Cirillo, may be contacted at massimo.cirillo@unina2.it.

Support: None.

Financial Disclosure: The authors declare that they have no relevant financial interests.

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References 

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 Originally published online as doi:10.1053/j.ajkd.2010.07.002 on September 1, 2010.

PII: S0272-6386(10)01076-0

doi:10.1053/j.ajkd.2010.07.002

American Journal of Kidney Diseases
Volume 56, Issue 4 , Pages 802-804, October 2010

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