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


METHODS
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.
Cristóbal
Joan
J
Centro de Salud de Sárdoma, Vigo, Pontevedra, Spain. sbd@vagusgruppe.com
Lago
Fernando
F
de la Fuente
Javier
J
González-Juanatey
José R
JR
Vázquez-Bellés
Pilar
P
Vila
María
M
D000328:Adult; D000368:Aged; D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000517:prevention & control*; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D006937:Hypercholesterolemia / Q000150:complications / Q000188:drug therapy*; D000960:Hypolipidemic Agents / Q000627:therapeutic use*; D008297:Male; D008875:Middle Aged; D018570:Risk Assessment; D012307:Risk Factors; D013030:Spain / Q000453:epidemiology
D000960:Hypolipidemic Agents