A Validation Study on eGFR Equations in Chinese Patients With Diabetic or Non-diabetic CKD.

Danshu Xie,Hong Ren,Hongrui Wang,Ying Ding,Weiming Wang,Nan Chen,Bing Chen,Wen Zhang,Yifan Wu,Liyan Ni,Yimin Lu,Hao Shi,Jingyuan Xie,Na Liu

doi:10.3389/fendo.2019.00581

Abstract

Aims: It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with diabetes.Materials and Methods: Two hundred and fifteen diabetic CKD patients and 192 non-diabetic CKD patients were enrolled in this study. Iohexol GFR, serum creatinine (SCr), and Cystatin C(CysC) were measured simultaneously for each patient. SCr- and CysC-based estimated GFR (eGFR) were calculated through eight equations, including three CKD-EPI equations, Revised Lund-Malmö study equation (RLM), CAPA equation, and three Full Age Spectrum (FAS) equations. Bias, precision, and accuracy were compared among eGFR equations with iohexol-GFR serving as measured GFR (mGFR). Independent predictive factors of accuracy were explored using multivariate logistic regression analysis.Results: In the diabetic group, CKD-EPISCr−CysC showed the best performance among three CKD-EPI equations (interquartile range of 13.88 ml/min/1.73 m2 and 30% accuracy of 72.56%). Compared to CKD-EPISCr−CysC, the other five equations did not significantly improve the performance of GFR estimates. Mostly, eGFR equations were less accurate in diabetic group than in non-diabetic group. Significant differences were found in different mGFR range (P < 0.001). The multivariate logistic regression analysis identified that BMI, mGFR, and diabetic kidney disease (DKD) status were independent predictors of accuracy of three equations in diabetic group. HbA1c was a predictor of accuracy of CKD-EPISCr and CKD-EPICysC in diabetic group.Conclusions: This study showed that eGFR equations were less accurate in the diabetic group than in the non-diabetic group. CKD-EPIScr−CysC had the best performance among CKD-EPI equations in Chinese diabetic CKD patients. The other five equations did not significantly improve the performance of GFR estimates. BMI, mGFR, DKD status, and HbA1c were independent factors associated with accuracy in eGFR equations.

Highlights

The estimated overall prevalence of type 2 diabetes in China was 10.9% in 2013 according to a national survey [1]
We explored which eGFR equations based on filtration markers–serum creatinine (SCr), Cystatin C (CysC), alone or combined, would better represent glomerular filtration rate (GFR) with less bias and more accuracy in Chinese diabetic chronic kidney disease (CKD) patients
Our study showed that compared to the non-diabetic group, the bias and interquartile range (IQR) were higher and P30 and P10 of eGFR equations were lower in diabetic group, which means the eGFR equations were more biased, less accurate and precise in the diabetic group

Summary

Introduction

The estimated overall prevalence of type 2 diabetes in China was 10.9% in 2013 according to a national survey [1] This may result in a proportional increase of chronic kidney disease (CKD) related to diabetes mellitus [2]. More equations were developed and were reported for better performance across different age groups, including Revised Lund-Malmö study equation (RLM) [10], CAPA equation [11] and three Full Age Spectrum (FAS) equations [12, 13] Application of these eGFR equations in diabetic patients remains controversial due to affected levels of SCr and CysC in diabetic status [14]

Methods

Results

Discussion

Conclusion