The additive value of multiple biomarkers in prediction of premature coronary artery disease

Abstract

OBJECTIVE:

The aim of this study was to determine the value of additional multiple biomarkers in the prediction of premature coronary artery disease (CAD).

METHODS AND RESULTS:

Data from 503 CAD patients and 503 healthy control patients with matching age and sex were collected. The patient group consisted of male (25 to 55 years) and female (30 to 60 years) patients with documented angiographic multi-vessel CAD. Baseline characteristics of conventional risk factors and biomarkers were collected. We compared the conventional risk factors model with the model with six additional biomarkers (hs-CRP, IL-6, RAGE, Lp-LPA2, adiponectin, and RANTES), which have shown significant association with premature CAD. We also evaluated the effects of adding each of the six biomarkers to the conventional laboratory data. The additional biomarkers model resulted in improvements in the C-statistic (0.953 vs. 0.937, P=0.0003) in comparison with the conventional risk factors model. Among the 6 biomarkers added to the patient group, hs-CRP and IL-6 had a significant discriminative power to predict the risk of premature CAD (hs-CRP; P = 0.0005, IL-6; P= 0.003).

CONCLUSIONS:

Although conventional risk factors were more strongly associated with premature CAD than were biomarkers, adding the 6 biomarkers (hs-CRP, IL-6, RAGE, Lp-LPA2, adiponectin, and RANTES) improved the prediction of premature CAD moderately. We found that hs-CRP and IL-6 had shown a significant contribution in the prediction of premature CAD.