Delanaye Pierre, Björk Jonas, Vidal-Petiot Emmanuelle, Flamant Martin, Ebert Natalie, Schaeffner Elke, Grubb Anders, Christensson Anders, Nyman Ulf, Stehlé Thomas, Pottel Hans
Department of Nephrology, Dialysis, Transplantation, University of Liège, Centre Hospitalier Universitaire Sart Tilman, Liège, Belgium.
Department of Nephrology, Dialysis, Apheresis, Hôpital Universitaire Carémeau, Nîmes, France.
Nephrol Dial Transplant. 2025 Feb 28;40(3):516-523. doi: 10.1093/ndt/gfae161.
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.
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).
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.
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.
肾小球滤过率（GFR）的估算为检测肾脏疾病的一种手段。最常用的生物标志物仍是血清肌酐，且欧洲肾功能联盟（EKFCcrea）方程在欧洲是经过最充分验证的。最近，胱抑素C已被提议作为一种生物标志物。我们根据受试者的糖尿病状态，在一大群受试者中研究了EKFC方程的性能。
回顾性分析了EKFC数据集中四个队列，这些队列中可获取糖尿病状态信息。通过血浆清除率（mGFR；碘海醇或铬51-乙二胺四乙酸）测量GFR。通过计算偏差、精密度[四分位间距（IQR）]和P30（估算肾小球滤过率（eGFR）值在mGFR的±30%范围内的百分比）来评估方程的性能。
在整个人群（N = 6158）中，年龄中位数为61岁（IQR 47 - 72），女性占45.8%。平均mGFR为60 ml/min/1.73 m²（IQR 39 - 82）。与非糖尿病个体（n = 5124）相比，糖尿病患者（n = 1034）年龄更大，男性更常见，体重更重且mGFR更低。EKFCcys方程的性能与EKFCcrea方程相似，但EKFCcrea + cys方程的P30优于单一生物标志物方程。糖尿病患者的P30值显著低于非糖尿病患者，但根据匹配分析，这主要是由两个人群之间的GFR水平差异解释的，而非糖尿病状态。
我们表明，结合肌酐和胱抑素C的方程性能更好。如果方程在非糖尿病个体中的准确性似乎优于糖尿病个体，更可能是由于GFR水平的差异而非糖尿病状态。
