C-Reactive Protein and Parental History Improve Global Cardiovascular Risk Prediction

Abstract Recent investigations of atherosclerosis have focused on inflammation, providing new insight into mechanisms of disease. Inflammatory cytokines involved in vascular inflammation stimulate the generation of endothelial adhesion molecules, proteases, and other mediators, which may enter the circulation in soluble form. These primary cytokines also induce production of the messenger cytokine interleukin-6, which stimulates the liver to increase production of acute-phase reactants such as C-reactive protein. In addition, platelets and adipose tissue can generate inflammatory mediators relevant to atherothrombosis. Despite the irreplaceable utility of plasma lipid profiles in assessment of atherosclerotic risk, these profiles provide an incomplete picture. Indeed, many cardiovascular events occur in individuals with plasma cholesterol concentrations below the National Cholesterol Education Program thresholds of 200 mg/dL for total cholesterol and 130 mg/dL for low-density lipoprotein (LDL) cholesterol. The concept of the involvement of inflammation in atherosclerosis has spurred the discovery and adoption of inflammatory biomarkers for cardiovascular risk prediction. C-reactive protein is currently the best validated inflammatory biomarker; in addition, soluble CD40 ligand, adiponectin, interleukin 18, and matrix metalloproteinase 9 may provide additional information for cardiovascular risk stratification and prediction. This review retraces the biology of atherothrombosis and the evidence supporting the role of inflammatory biomarkers in predicting primary cardiovascular events in this biologic context.

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Abstract 5100: C-Reactive Protein and Parental History Improve Global Cardiovascular Risk Prediction: The Reynolds Risk Score for Men

Circulation ◽

10.1161/circ.118.suppl_18.s_1145-b ◽

2008 ◽

Vol 118 (suppl_18) ◽

Author(s):

Paul M Ridker ◽

Nina P Paynter ◽

Nader Rifai ◽

Michael Gaziano ◽

Nancy R Cook

Keyword(s):

Cardiovascular Risk ◽

Risk Prediction ◽

Risk Score ◽

Cardiovascular Events ◽

Prediction Models ◽

Prediction Algorithm ◽

Parental History ◽

Cardiovascular Risk Prediction ◽

Study Population ◽

Reynolds Risk Score

Background. CRP and family history independently associate with future cardiovascular events and have been incorporated into risk prediction models for women (the Reynolds Risk Score for women). However, no cardiovascular risk prediction algorithm incorporating these variables currently exists for men. Methods. Among 10,724 initially healthy American non-diabetic men who were followed prospectively for incident cardiovascular events over a median period of 10.8 years, we developed a cardiovascular risk prediction model that included hsCRP and parental history of myocardial infarction before age 60 years, and compared model fit, discrimination, and reclassification to prediction models limited to age, blood pressure, smoking, total cholesterol, and high-density lipoprotein cholesterol. Results. 1,294 cardiovascular events accrued during study follow-up. Predictive models incorporating hsCRP and parental history (the Reynolds Risk Score for men) had better global fit (P<0.001), a superior (lower) Bayes Information Criterion (BIC)(23008 vs 23048), and larger C-indexes (0.708 vs 0.699, P < 0.001) than did predictive models without these variables. For the endpoint of all cardiovascular events, the Reynolds Risk Score for men reclassified 17.8 percent of the study population into higher- or lower-risk categories with markedly improved accuracy among those reclassified. In models based on the ATP-III preferred endpoint of coronary heart disease and limited to men not taking lipid-lowering therapy, 16.7 percent of the study population were reclassified to higher- or lower-risk groups, again with significantly improved global fit (P<0.001), smaller BIC (13870 vs 13891), larger C-index (0.714 vs 0.704, P < 0.001), and almost perfect accuracy among those reclassified (99.9 percent). For this model, NRI was 8.4 percent and CNRI 15.8 percent (both P-values < 0.001). Conclusion. We developed an improved global risk prediction algorithm for men incorporating hsCRP and parental history that should allow better targeting of preventive therapies to maximize benefit while minimizing toxicity and cost.

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