Table 5.

Prediction gain by DcR3 over a model of traditional cardiovascular risk factors

Multivariate Cox Hazards ModelHR (95% CI)P ValueAICaΔAICb
Cardiovascular mortality
 cardiovascular risk factors335.50.0
 + VCAM-1 (1 SD unit)1.8 (0.7−4.4)0.15346.711.2
 + albumin (1 g/L)0.9 (0.6−1.3)0.48345.09.5
 + hs-CRP (1 SD unit)1.6 (0.9−2.5)0.05341.45.9
 + IL-6 (1 SD unit)1.7 (1.1−2.7)0.01339.33.8
 + DcR3 (1 SD unit)1.5 (1.1−2.4)0.03341.56.0
All-cause mortality
 cardiovascular risk factors872.50.0
 + VCAM-1 (1 SD unit)1.7 (1.0−3.1)0.03889.617.1
 + albumin (1 g/dl)0.7 (0.5−0.9)0.01882.710.2
 + hs-CRP (1 SD unit)1.3 (0.9−1.7)0.05892.319.8
 + IL-6 (1 SD unit)1.6 (1.2−2.1)0.01885.412.9
 + DcR3 (1 SD unit)1.5 (1.2−2.0)<0.01884.011.5
  • DcR3, decoy receptor 3; HR, hazard ratio; 95% CI, 95% confidence interval; AIC, Akaike Information Criterion; VCAM-1, vascular cell adhesion molecule-1; hs-CRP, high-sensitive C-reactive protein.

  • a AIC (15) for a given model is a function of its maximized log-likelihood and the number of estimable parameters (K): AIC = −2 (maximized log-likelihood) + 2K. In the baseline Cox proportional hazards model, there were six traditional cardiovascular risk factors, including age, sex, smoking status, diabetes, total cholesterol, and systolic BP. VCAM-1, albumin, hs-CRP, IL-6, or DcR3 was added subsequently in order to assess the independent predictive contribution by DcR3.

  • b ΔAIC is the difference between the AIC of baseline model and the AIC of VCAM-1, albumin, hs-CRP, IL-6, or DcR3, respectively. Therefore, the lower the ΔAIC, the higher prediction gain of pertinent biomarker.