Table 3.
Model predicting rapidly versus slowly progressive disease (annual change in eGFR less than or equal to or greater than −3.5 mL/min/1.73 m2; n = 152)
| Variable | Model 1 (multivariable) |
Model 2 (as model 1 + single biomarker) |
Model 3 (stepwise backward) |
|||
|---|---|---|---|---|---|---|
| OR [95% CI] | p value | OR [95% CI] | p value | OR [95% CI] | p value | |
| –2 log likelihood ratio | 189 | NA | 179** | |||
| Age (per 10 years) | 0.59 [0.36–0.98] | 0.04 | – | – | 0.81 [0.46–1.42] | 0.46 |
| Gender, female | 0.84 [0.54–2.16] | 0.84 | – | – | 1.37 [0.65–2.87] | 0.41 |
| eGFR (per 10 mL/min/1.73 m2) | 0.57 [0.41–0.80] | 0.001 | – | – | 0.62 [0.43–0.88] | 0.008 |
| Albumin (per SD) | 1.25 [0.86–2.81] | 0.24 | ||||
| IgG (per SD) | 0.92 [0.61–1.40] | 0.70 | ||||
| β2MG (per SD) | 1.61* [1.08–2.40] | 0.02 | 1.49 [0.99–2.23] | 0.055 | ||
| KIM-1 (per SD) | 1.46* [0.99–2.14] | 0.06 | ||||
| HFABP (per SD) | 1.64* [0.94–2.86] | 0.08 | ||||
| NGAL (per SD) | 1.61* [1.01–2.59] | 0.048 | ||||
| MCP-1 (per SD) | 1.63* [1.09–2.44] | 0.02 | 1.52 [1.01–2.28] | 0.047 | ||
–2 log likelihood ratio p < 0.05 compared to model 1.
–2 log likelihood ratio p = 0.007 compared to model 1 and p = 0.04 and p = 0.049 compared to model 2 with β2MG or MCP-1, respectively.
ORs and p values were calculated using logistic regression analysis. Dependent variable is rapid versus slow disease progression (annual change in eGFR less than or equal to −3.5 versus greater than −3.5 mL/min/1.73 m2).
Model 1: Age, female sex, and eGFR.
Model 2: Age, female sex, eGFR, and one of the urinary biomarkers.
Model 3: Age, female sex, eGFR, urinary β2MG, and MCP-1 excretion.
eGFR, estimated glomerular filtration rate; IgG, immunoglobulin G; β2MG, β2 microglobulin; KIM-1, kidney injury molecule 1; HFABP, heart-type fatty acid-binding protein; NGAL, neutrophil gelatinase-associated lipocalin; MCP-1, monocyte chemotactic protein 1.