Resource Efficient Screening for Primary Prevention of Coronary Heart Disease: A Proof-of-Concept Test in the MESA...

Area of Science:

• Cardiology
• Preventive Medicine
• Medical Imaging

Background:

• Current guidelines for preventive coronary heart disease (CHD) treatment rely on the pooled cohort equation and computed tomography (CT) for coronary artery calcification (CAC) assessment.
• The optimal use of cardiac imaging in guiding preventive CHD treatment remains a subject of debate.

Purpose of the Study:

• To evaluate a simplified approach to preventive CHD treatment using a self-report risk algorithm instead of the pooled cohort equation.
• To assess the resource efficiency and discriminative ability of a self-report based strategy compared to current guidelines.

Main Methods:

• A gradient boosting machine model was developed using self-reported factors to predict the probability of a high CAC score (≥100).
• A 3-step self-report based CHD preventive strategy was tested: 1. Predict high CAC probability. 2. Perform CT for high-risk individuals. 3. Assign treatment eligibility based on CAC score.
• The strategy was validated using the MESA cohort (n=4564) and compared against guideline-recommended CAC scanning for intermediate-risk individuals.

Main Results:

• The pooled cohort equation identified 33% for CAC scans and 19% for treatment, capturing 48% of CHD events.
• The self-report strategy identified 56% of CHD events (P=0.02) using the same number of CAC scans and treatments.
• The self-report strategy required healthcare visits for only 33% of the population, indicating improved resource efficiency.

Conclusions:

• A self-report screening strategy combined with CAC scoring is more resource-efficient than current guidelines.
• This self-report approach better identifies high-risk individuals eligible for lipid-lowering therapy.
• The findings suggest a potential simplification in guiding preventive CHD treatment.