Table 3

Comparison of multivariable logistic regression models with regard to the prediction of fast early renal decline in patients with type 2 diabetes during 6–12 years of follow-up

Model 1 (reference)Model 2Model 3
Baseline variablesOR(95% CI)OR(95% CI)OR(95% CI)
eGFR 0.91 (0.82–1.02) 1.08 (0.96–1.22) 1.19 (1.03–1.37) 
Systolic BP 1.34 (1.13–1.57) 1.37 (1.15–1.62) 1.38 (1.16–1.64) 
ACR 1.83 (1.54–2.19) 1.50 (1.25–1.81) 1.27 (1.04–1.56) 
HbA1c 1.19 (1.08–1.32) 1.20 (1.08–1.34) 1.14 (1.02–1.27) 
Fibrosis index   1.98 (1.60–2.43) 1.63 (1.30–2.04) 
TNF-R1     1.15 (0.91–1.44) 
KIM-1     1.36 (1.12–1.64) 
EGF–to–MCP-1 ratio     0.68 (0.56–0.83) 
C statistic 0.725 0.766 0.791 
∆C statistic compared  with model 1 0.041 (0.011–0.071) 0.066 (0.031–0.100) 
Nagelkerke R2 0.144 0.208 0.250 
Model 1 (reference)Model 2Model 3
Baseline variablesOR(95% CI)OR(95% CI)OR(95% CI)
eGFR 0.91 (0.82–1.02) 1.08 (0.96–1.22) 1.19 (1.03–1.37) 
Systolic BP 1.34 (1.13–1.57) 1.37 (1.15–1.62) 1.38 (1.16–1.64) 
ACR 1.83 (1.54–2.19) 1.50 (1.25–1.81) 1.27 (1.04–1.56) 
HbA1c 1.19 (1.08–1.32) 1.20 (1.08–1.34) 1.14 (1.02–1.27) 
Fibrosis index   1.98 (1.60–2.43) 1.63 (1.30–2.04) 
TNF-R1     1.15 (0.91–1.44) 
KIM-1     1.36 (1.12–1.64) 
EGF–to–MCP-1 ratio     0.68 (0.56–0.83) 
C statistic 0.725 0.766 0.791 
∆C statistic compared  with model 1 0.041 (0.011–0.071) 0.066 (0.031–0.100) 
Nagelkerke R2 0.144 0.208 0.250 

Model 1: reference; model 2: model 1 + fibrosis index; model 3: model 2 + other biomarkers (plasma TNF-R1, plasma KIM-1, and urinary EGF–to–MCP-1 ratio).

The effects of eGFR and systolic BP on fast renal decline were estimated per 10 mL/min/1.73 m2 and per 10 mmHg increase, respectively. The effect of HbA1c was estimated per 1% increase. The effects of ACR, the fibrosis index, plasma TNF-R1, plasma KIM-1, and the urinary EGF–to–MCP-1 ratio were estimated per one quartile increase.

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