A model for estimating future risk of fatal coronary heart disease for global populations (USA)

Introduction: Ischemic heart disease is the most important cause of disease burden globally. There is an urgent need to monitor cardiovascular risk in global populations to measure success of preventive interventions and efficiently allocate resources. We used an innovative approach to build a model for predicting risk of fatal coronary heart disease (CHD) which, unlike existing models, is easy to recalibrate, relaxes the assumptions of uniform age effects across populations, allows age-specific effects and can accommodate competing risks.

Methods: We fit sex-specific stratified Cox models for fatal CHD to pooled data from 9 cohorts in the US using age as the time scale. We included interactions between risk factors and age at risk. We included systolic blood pressure, total cholesterol, smoking, and diabetes, and tested body mass index (BMI) for inclusion. For risk prediction, observed hazards of fatal CHD at each age were combined with the predicted individuals' age specific hazard ratios and the resulting hazards were converted to survival probabilities to estimate the 10-year risk of fatal CHD.

Results: After applying exclusion criteria, 39762 men and 21198 women were enrolled in the study, with 1438 and 445 fatal CHDs over a median follow-up of 12 years. BMI was included in the final model as it improved prediction (continuous NRIs: men=0.036, women=0.172). The models had Harrell's C=0.69(95% CI 0.68-0.71) for men, and 0.83(0.80-0.86) for women. Mean 10-year risk of CHD death was 2.3% in men (median 1.2, IQR 0.5-2.6) and 1.3 % in women (median 0.4, IQR 0.1-1.2). Average risks for ages 50-65 and 65+ were 2.4% and 6.3% in men, and 1.0% and 3.1% in women.

Conclusions: The new models had good discrimination, can be recalibrated for different populations using their CHD mortality rates, do not assume the same effect of aging across populations, and can incorporate competing risks.