Diabetic status and the performances of creatinine- and cystatin C-based eGFR equations.

BACKGROUND

The estimation of glomerular filtration rate (GFR) is one tool to detect renal disease. The most used biomarker remains serum creatinine and the European Kidney Function Consortium (EKFCcrea) equation is the most validated in Europe. More recently, cystatin C has been proposed as a biomarker. We studied the performances of the EKFC equations in a large cohort of subjects according to their diabetic status.

METHODS

Four cohorts from the EKFC dataset were retrospectively considered in which the diabetic status was available. GFR was measured by plasma clearances (mGFR; iohexol or chromium 51-ethylenediaminetetraacetic acid). The performance of the equations was assessed by calculating bias, precision [interquartile range (IQR)] and P30 (percentage of eGFR values within ±30% of mGFR).

RESULTS

In the whole population (N = 6158), the median age was 61 years (IQR 47-72) and 45.8% were women. The mean mGFR was 60 ml/min/1.73 m2 (IQR 39-82). Compared with non-diabetic individuals (n = 5124), diabetic patients (n = 1034) were older, more frequently male, heavier and had lower mGFR. The performance of the EKFCcys equation was similar to that of the EKFCcrea equation, but the EKFCcrea+cys equation had a better P30 than the single-biomarker equations. P30 values were substantially lower in diabetic patients than in non-diabetic patients, but according to a matched analysis, this is mainly explained by the difference in GFR levels between the two populations, not by diabetic status.

CONCLUSION

We showed that the equation combining creatinine and cystatin C performed better. If the accuracy of equations seems better in non-diabetic than in diabetic individuals, it is more likely due to differences in GFR levels rather than diabetic status.