Comparison of the Framingham risk function-based coronary chart with risk function from an Italian population study

Area of Science:

• Cardiology
• Public Health
• Epidemiology

Background:

• Cardiovascular disease prevention relies on accurate coronary risk assessment.
• Existing risk charts, like the European Task Force's, are often based on population-specific data, such as the Framingham Heart Study.
• The applicability of these charts to diverse populations with varying coronary event incidence requires validation.

Purpose of the Study:

• To compare the coronary risk predictions of the European Task Force's chart (using a Framingham risk function) with a novel risk function derived from an Italian population study.
• To evaluate potential overestimation or underestimation of absolute coronary risk by the Framingham-based chart in an Italian context.

Main Methods:

• A longitudinal study followed 1656 middle-aged Italian men for 25 years.
• Coronary risk was calculated using a log-linear accelerated time failure model, similar to the Framingham equation, incorporating age, systolic blood pressure, total cholesterol, and smoking habits.
• Risk predictions were compared for men aged 40, 50, and 60 years using both the European chart and the Italian-derived risk function over a 10-year follow-up period.

Main Results:

• The Italian risk function yielded statistically significant coefficients for all four assessed risk factors.
• The European coronary risk chart identified 44 out of 120 risk cells (20% or higher 10-year risk), while the Italian function identified only four such cells (P<0.001).
• The Italian risk function substantially underestimated the risk levels predicted by the European chart.

Conclusions:

• The Framingham risk function-based coronary risk chart tends to overestimate absolute coronary risk in populations with lower coronary event incidence, such as Italy.
• Caution is advised when applying the European coronary risk chart in regions with different epidemiological profiles.
• Population-specific risk functions may offer more accurate cardiovascular risk stratification.