New Table 3.
Predictive logistic models for ESKD according to baseline variables considered. Models were developed using 196 individuals selected for Macro-Albuminuria Study.
| Model #1 | Model #2 | Model #3 | Model #4* | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | P Value | OR | 95% CI | P Value | OR | 95% CI | P Value | OR | 95% CI | P Value | |
| eGFR | 0.98 | (0.96–0.99) | 0.0007 | 0.98 | (0.97–1.00) | 0.0545 | 0.98 | (0.97–1.00) | 0.0203 | 0.99 | (0.97–1.01) | 0.1696 |
| HbA1c | 1.57 | (1.26–1.96) | <.0001 | 1.60 | (1.28–2.00) | <.0001 | 1.60 | (1.28–2.00) | <.0001 | 1.50 | (1.19–1.89) | 0.0006 |
| ACR | 1.70 | (1.26–2.30) | 0.0005 | 1.62 | (1.20–2.20) | 0.0018 | 1.63 | (1.20–2.21) | 0.0016 | 1.66 | (1.20–2.30) | 0.0024 |
| TNF-R1A | – | – | – | 1.49 | (1.04–2.13) | 0.0279 | – | – | – | 1.24 | (0.69–2.22) | 0.4706 |
| TNF-R1B | – | – | – | – | – | – | 1.43 | (1.02–2.00) | 0.0373 | 0.73 | (0.40–1.36) | 0.3246 |
| TNF-R6B | – | – | – | – | – | – | – | – | – | 1.49 | (1.03–2.17) | 0.0357 |
| TNF-R11A | – | – | – | – | – | – | – | – | – | 1.73 | (1.08–2.76) | 0.0227 |
| C statistics | 0.774 | 0.788 | 0.784 | 0.815 | ||||||||
*
Model #4: This model was developed by including 5 markers (eGFR, ACR, HbA1c, TNF-R1A and –R1B) and adding the TNF receptors that were selected from remaining 11 TNF receptors using backward elimination (p-for-stay = 0.1).
The effects of eGFR and HbA1c on development of ESKD were estimated as 1 ml/min/1.73m2 increase and as 1% increase, respectively. The effects of ACR, TNF-R1A, TNF-R1B, TNF-R6B, and TNF-R11A on development of ESKD were estimated as one quartile increase. ESKD, end-stage kidney disease. OR, odds ratio