Do apolipoproteins improve coronary risk prediction in subjects with metabolic syndrome?

Objective. We assess predictive abilities among subjects with metabolic syndrome (MetS) of CVD risk algorithms including ApoB and ApoAI. Methods. Three independent population-based cohorts (3677 35-74 years old men and women, free of CVD and diabetes at baseline) were enrolled in Northern Italy, adopting standardized MONICA procedures. Through Cox models, we assessed the associations between lipid measures and first coronary events, as well as the changes in discrimination and reclassification (NRI) when standard lipids or apolipoproteins were added to the CVD risk score algorithm including non-lipids risk factors. Finally, the best models including lipids or apolipoproteins were compared. Models were fit on the full population and also on the MetS subgroup. Results. During the 14.5 years median follow-up time, 196 coronary events were validated. All measures showed statistically significant associations with the endpoint. Models including HDL-C plus TC and ApoB plus ApoAI for lipids and apolipoproteins, respectively, showed the best predictive values. When ApoB plus ApoAI replaced TC plus HDL-C, NRI values improved in subjects with MetS (13.8; CI95%:-5.1, 53.1), significantly in those previously classified at intermediate risk (44.5, CI95% 13.8-129.6; no case was moved downward). The result was mainly driven by ApoAI.. Conclusions. ApoB and ApoAI could be cost-effective in CVD risk prediction when used as second level biomarkers in subjects with MetS classified at intermediate CVD risk.