title: Effects of additional blood pressure and lipid measurements on the prediction of cardiovascular risk.
abstract: BACKGROUND
  Current guidelines recommend that decisions to start preventative therapy for cardiovascular disease (CVD) should be based on absolute risk; however, current risk equations are based on single measurements of risk factors. We aimed to assess whether two measurements of blood pressure and lipids improves the prediction of cardiovascular risk compared to one measurement.
  
  
  RESULTS
  We used sex-specific Cox proportional hazards models to evaluate the risk of first CVD event in 2385 participants of the Framingham Offspring Study attending both the second and third visits. We estimated the effects on risk prediction of using the average of two measurements of blood pressure, total cholesterol, and HDL cholesterol compared to using one measurement of the risk factors. We found that these risk factors were each markedly more predictive of CVD when the average of two measurements was used rather than one measurement and age was less predictive of CVD. There were small improvements in the overall model fit, discrimination, and calibration. Reclassification also showed small improvements across the risk spectrum (net reclassification information, NRI, for women 3.0%, 95% CI -0.9 to 24.8%; NRI for men 4.0%, 95% CI -2.2 to 14.1%) and possibly greater improvements for intermediate-risk individuals (NRI for women 32.3%, 95% CI -21.9 to 46.8%; NRI for men 16.0%, 95% CI -3.3 to 43%).
  
  
  CONCLUSIONS
  Averaging two measurements of blood pressure and lipids results in marked increases in the predictiveness of these risk factors and smaller improvements in the overall prediction of cardiovascular risk including reclassification.
authors.affiliation: Screening and Test Evaluation Program (STEP), School of Public Health, University of Sydney, NSW 2006, Australia. katy.bell@sydney.edu.au
authors.forename: Katy
authors.initials: K
authors.lastname: Bell
authors.forename: Andrew
authors.initials: A
authors.lastname: Hayen
authors.forename: Kevin
authors.initials: K
authors.lastname: McGeechan
authors.forename: Bruce
authors.initials: B
authors.lastname: Neal
authors.forename: Les
authors.initials: L
authors.lastname: Irwig
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D015415:Biomarkers / Q000097:blood; D001794:Blood Pressure; D001795:Blood Pressure Determination; D002318:Cardiovascular Diseases / Q000097:blood* / Q000453:epidemiology / Q000503:physiopathology*; D002784:Cholesterol / Q000097:blood*; D008076:Cholesterol, HDL / Q000097:blood; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008297:Male; D008404:Massachusetts / Q000453:epidemiology; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors
chemical_list: D015415:Biomarkers; D008076:Cholesterol, HDL; D002784:Cholesterol