Comparing the GFR estimation equations using both creatinine and cystatin c to predict the long-term renal outcome in type 2 diabetic nephropathy patients.
This study aimed to determine whether eGFRcre-cys and its slope could improve the prediction of the long-term renal outcome in patients with type 2 diabetic nephropathy (DN).



The cross-sectional and longitudinal analyses included 501 type 2DN patients from 2003 to 2009. GFR was estimated using either eGFRcre-cys or the serum creatinine-based equation (eGFRcre) or the cystatin C-based equation (eGFRcys), and was classified into 3 categories (≥90, 60-90, ≤60ml/min per 1.73m2). The proportion of patients was evaluated in each creatinine-calculated eGFR category for which the category was reclassified based on either cystatin C or the combined measurement. Long-term changes in eGFRcre-cys, eGFRcys and eGFRcre were estimated using linear mixed effect models. The receiver operating characteristic (ROC) curves was applied to study the sensitivity and specificity of different eGFR slopes for predicting the renal endpoint.



In the cross-sectional analyses, eGFRcre was overestimated compared to eGFRcre-cys [median bias -8.5 (95% CI: -25.01, 1.21)]. The reclassification of eGFRcre to a higher value was associated with an increased risk of ESRD [OR: 4.01 (95% CI: 2.36 to 6.82)]. In the longitudinal analyses for predicting end-stage renal disease (ERSD), the ROC curves for eGFRcre-cys (AUC=0.86±0.03) over 24months were increased compared with the ROC curves for eGFRcre and eGFRcys (p<0.05).



The study suggests that the eGFRcre-cys equation may be more precise and sensitive for predicting the renal outcome in T2DN patients. Tracking renal decline using eGFRcre-cys may be used as a surrogate for determining the renal endpoint in a clinical setting.
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine.
Yu
Y
Pan
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine.
Song
S
Jiang
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine.
Dandan
D
Qiu
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine.
Jingsong
J
Shi
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine.
Minlin
M
Zhou
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine.
Yu
Y
An
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine.
Yongchun
Y
Ge
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine.
Honglang
H
Xie
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine. Electronic address: liuzhihong@nju.edu.cn.
Zhihong
Z
Liu
D000328:Adult; D015415:Biomarkers / Q000097:blood; D003404:Creatinine / Q000097:blood*; D003430:Cross-Sectional Studies; D055316:Cystatin C / Q000097:blood*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000150:complications; D003928:Diabetic Nephropathies / Q000097:blood / Q000175:diagnosis*; D005919:Glomerular Filtration Rate; D006801:Humans; D008137:Longitudinal Studies; D008875:Middle Aged; D011379:Prognosis
D015415:Biomarkers; D055316:Cystatin C; D003404:Creatinine
Cystatin C; Estimating equations; Renal outcome; Type 2 diabetic nephropathy; eGFR slopes