Including hsCRP in cardiovascular risk prediction models improved risk classification, reclassifying 21% and 19% of women initially at 5% to <10% and 10% to <20% risk into more accurate categories.
Cohort
Does the inclusion of hsCRP in global cardiovascular risk prediction models improve risk classification in initially healthy nondiabetic women?
Incorporating hsCRP into cardiovascular risk prediction models improves risk classification in women, particularly for those at intermediate (5-20%) 10-year risk.
BACKGROUND: While high-sensitivity C-reactive protein (hsCRP) is an independent predictor of cardiovascular risk, global risk prediction models incorporating hsCRP have not been developed for clinical use. OBJECTIVE: To develop and compare global cardiovascular risk prediction models with and without hsCRP. DESIGN: Observational cohort study. SETTING: U.S. female health professionals. PARTICIPANTS: Initially healthy nondiabetic women age 45 years and older participating in the Women's Health Study and followed an average of 10 years. MEASUREMENTS: Incident cardiovascular events (myocardial infarction, stroke, coronary revascularization, and cardiovascular death). RESULTS: High-sensitivity CRP made a relative contribution to global risk at least as large as that provided by total, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) cholesterol individually, but less than that provided by age, smoking, and blood pressure. All global measures of fit improved when hsCRP was included, with likelihood-based measures demonstrating strong preference for models that include hsCRP. With use of 10-year risk categories of 0% to less than 5%, 5% to less than 10%, 10% to less than 20%, and 20% or greater, risk prediction was more accurate in models that included hsCRP, particularly for risk between 5% and 20%. Among women initially classified with risks of 5% to less than 10% and 10% to less than 20% according to the Adult Treatment Panel III covariables, 21% and 19%, respectively, were reclassified into more accurate risk categories. Although addition of hsCRP had minimal effect on the c-statistic (a measure of model discrimination) once age, smoking, and blood pressure were accounted for, the effect was nonetheless greater than that of total, LDL, or HDL cholesterol, suggesting that the c-statistic may be insensitive in evaluating risk prediction models. LIMITATIONS: Data were available only for women. CONCLUSIONS: A global risk prediction model that includes hsCRP improves cardiovascular risk classification in women, particularly among those with a 10-year risk of 5% to 20%. In models that include age, blood pressure, and smoking status, hsCRP improves prediction at least as much as do lipid measures.
Cook et al. (2006) conducted a cohort in Cardiovascular risk. Cardiovascular risk prediction models including hsCRP vs. Cardiovascular risk prediction models without hsCRP was evaluated on Incident cardiovascular events (myocardial infarction, stroke, coronary revascularization, and cardiovascular death). Including hsCRP in cardiovascular risk prediction models improved risk classification, reclassifying 21% and 19% of women initially at 5% to <10% and 10% to <20% risk into more accurate categories.
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