C-reactive protein modulates risk prediction based on the Framingham Score: implications for future risk assessment: results from a large cohort study in southern Germany.

  • Koenig W
  • Lowel H
  • Baumert J
 et al. 
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BACKGROUND: The Framingham Coronary Heart Disease (CHD) prediction score is recommended for global risk assessment in subjects prone to CHD. Recently, C-reactive protein (CRP) has emerged as an independent predictor of CHD. We sought to assess the potential of CRP measurements to enhance risk prediction based on the Framingham Risk Score (FRS) in a large cohort of middle-aged men from the general population. METHODS AND RESULTS: We measured CRP and traditional cardiovascular risk factors at baseline in 3435 white men of German nationality, 45 to 74 years of age. All men were drawn from 3 random samples of the general population in the Augsburg area located in Southern Germany in 1984 to 1985, 1989 to 1990, and 1994 to 1995 (response rate, 80%), and the FRS was calculated in all of them. Outcome was defined as nonfatal and fatal coronary events, including sudden cardiac death. During an average follow-up of 6.6 years, a total of 191 coronary events occurred. Cox regression showed a significant contribution of CRP to coronary event risk prediction independent of the FRS (P=0.0002). In stratified analysis for 5 categories of FRS, CRP significantly added prognostic information to the FRS in subjects in 2 intermediate risk categories (P=0.03 and P=0.02). CONCLUSIONS: Our results suggest that CRP enhances global coronary risk as assessed by the FRS, especially in intermediate risk groups. This might have implications for future risk assessment.

Author-supplied keywords

  • Adult
  • Aged
  • C-Reactive Protein
  • Cholesterol, HDL
  • Cohort Studies
  • Comorbidity
  • Coronary Disease
  • Cross-Sectional Studies
  • Death, Sudden, Cardiac
  • Female
  • Germany
  • Humans
  • Hypercholesterolemia
  • Incidence
  • Male
  • Middle Aged
  • Myocardial Infarction
  • Predictive Value of Tests
  • Prognosis
  • Proportional Hazards Models
  • Prospective Studies
  • Registries
  • Risk Assessment
  • Severity of Illness Index
  • analysis
  • blood
  • epidemiology
  • statistics & numerical data

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  • Wolfgang Koenig

  • Hannelore Lowel

  • Jens Baumert

  • Christa Meisinger

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