title: The effect of including C-reactive protein in cardiovascular risk prediction models for women.
abstract: 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.
  
  
  METHODS
  Observational cohort study.
  
  
  METHODS
  U.S. female health professionals.
  
  
  METHODS
  Initially healthy nondiabetic women age 45 years and older participating in the Women's Health Study and followed an average of 10 years.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02215, USA. ncook@rics.bwh.harvard.edu
authors.forename: Nancy R
authors.initials: NR
authors.lastname: Cook
authors.forename: Julie E
authors.initials: JE
authors.lastname: Buring
authors.forename: Paul M
authors.initials: PM
authors.lastname: Ridker
mesh_terms: D000367:Age Factors; D015415:Biomarkers / Q000097:blood; D001794:Blood Pressure; D002097:C-Reactive Protein / Q000378:metabolism*; D002318:Cardiovascular Diseases / Q000097:blood* / Q000453:epidemiology*; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008055:Lipids / Q000097:blood; D008875:Middle Aged; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods*; D012907:Smoking / Q000009:adverse effects; D014481:United States / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D008055:Lipids; D002097:C-Reactive Protein