Cardiovascular
Characterization of the Course of Heart Disease in a Large Cohort Study Ming Ding* Ming Ding Feng-Chang Lin Michelle Meyer
Background. In cardiovascular epidemiology, studies have largely focused on the prevention and prediction of a single endpoint (e.g., hypertension). However, the development of heart disease is a long-term process that involves multiple endpoints, which are biologically inseparable. Limited studies have considered the entire disease course.
Method. We modeled the course of heart disease in five states: healthy, at metabolic risk, coronary heart disease (CHD), heart failure, and mortality. We characterized the disease course using two novel estimates: disease path and Multimorbidity-adjusted Life Year (MALY). Both estimates were derived from a new multi-state modeling method that we developed (Ding et al. BMC Medical Research Methodology. 2025). We used the Atherosclerosis Risk in Communities (ARIC) study data obtained through NHLBI BioLINCC.
Results. In this mid- to old-age population, participants’ course of heart disease is shown in the Figure. The projected MALY was 24.13 years (95% CI: 16.55, 32.06) and the corresponding multimorbidity-adjusted life expectancy was 78.23 years (95% CI: 75.95, 80.96). For healthy participants at baseline, the most likely disease paths were: “Healthy → at metabolic risk → mortality” (37%), “Healthy → mortality” (21%), followed by “Healthy → at metabolic risk → heart failure → mortality” (19%). The MALY was higher among women than men and higher among Whites than Blacks. The distribution of disease paths was similar across sex and race subgroups.
Impact. This study characterized the course of heart disease at the population level. For future research, MALY can be used to compare the effect of intervention regimes over the disease course to identify personalized optimal intervention; and disease path enables us to predict a person’s entire disease course, rather than just the risk of a single endpoint. These two summary estimates have potential applications in precision prevention and prediction of heart disease.
