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

Abstract

Background and hypothesis The estimation of glomerular filtration rate (GFR) is one main 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. 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 51Cr-EDTA). The performance of the equations was assessed by calculating bias, precision (IQR) and P30 (percentage of eGFR-values within ± 30% of mGFR). Results In the whole population (n = 6 158), median [IQR] age was 61 [47;72] years, with 45.8% women. Mean mGFR was 60 [39;82] mL/min/1.73m². Compared to non-diabetic individuals (n = 5 124), diabetic patients (n = 1 034) were older, more frequently male, heavier, and had lower mGFR. The performance of the EKFCcys equation was similar to EKFCcrea, but the EKFCcrea+cys had better P30 than the single-biomarker equations. P30 values were substantially lower in diabetic patients than in non-diabetic 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 equation combining creatinine and cystatin C present a better performance. If accuracy of equations seems better in non-diabetic than in diabetic individuals, it is more due to differences in GFR levels than to the diabetic status.