[Comparison of coronary risk estimates derived using the Framingham and REGICOR equations]

Rev Esp Cardiol. 2005 Aug;58(8):910-5.
[Article in Spanish]

Abstract

Introduction and objectives: To compare two equations for evaluating coronary risk, the Framingham-Wilson equation and the Framingham equation adjusted for the Spanish population (REGICOR), in a group of dyslipidemic patients in our healthcare area. In addition, the therapeutic implications of using the 2 methods were also evaluated.

Patients and method: The study included 815 dyslipidemic patients, aged 35-74 years, from our healthcare area. Coronary risk was determined using the 2 equations and subjects were categorized as either low-risk (0%-9%), moderate-risk (10%-19%), or high-risk (> or =20%). To compare the application of the 2 equations, we evaluated differences in derived scores, coronary risk category, and the number of patients regarded as potentially treatable with hypolipidemic drugs.

Results: The best correlation observed between the 2 methods was for quantitative scores (r=0.983; P<.001). The correlation was poorer when coronary risk categories were compared (r=0.489; P<.001). Overall, the concordance was poor (kappa=0.06), and was only acceptable for low-risk patients (kappa=0.53). The coronary risk estimates derived from the Wilson table were 2.4 times higher than those obtained using REGICOR. The main differences were for moderate and high-risk patients. In addition, the number of patients regarded as potentially treatable with hypolipidemic drugs was five times higher when the Wilson equation was used.

Conclusions: The overestimate of coronary risk obtained using the Framingham-Wilson equation leads to a greater number of patients being regarded as candidates for hypolipidemic treatment. Our data show the importance of using tables adjusted for the Spanish population.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Adult
  • Aged
  • Cardiovascular Diseases / epidemiology*
  • Cardiovascular Diseases / prevention & control*
  • Data Interpretation, Statistical
  • Female
  • Humans
  • Hypercholesterolemia / complications
  • Hypercholesterolemia / drug therapy*
  • Hypolipidemic Agents / therapeutic use*
  • Male
  • Middle Aged
  • Risk Assessment
  • Risk Factors
  • Spain / epidemiology

Substances

  • Hypolipidemic Agents