Trajectories of Health-Related Quality of Life in Coronary Artery Disease

BACKGROUND: Health-related quality of life (HRQOL) assessment is an important health outcome for measuring the efficacy of treatments and interventions for coronary artery disease (CAD). HRQOL is known to improve over the first year after interventions for CAD, but there is limited knowledge of the changes in HRQOL beyond 1 year. We investigated heterogeneity in long-term trajectories of HRQOL in patients with CAD. METHODS AND RESULTS: Data were obtained from 6226 patients identified from the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease with at least 1-vessel CAD who underwent their first catheterization between 2006 and 2009. HRQOL was assessed using the Seattle Angina Questionnaire, a 19-item disease-specific measure of HRQOL for patients with CAD. Group-based trajectory analysis was used to identify various subgroups of Seattle Angina Questionnaire trajectories over time while adjusting for missing data through a longitudinal multiple imputation model. Multinomial logistic regression was used to identify the predictors of differences among the identified subgroups. Our analysis revealed significant improvements in HRQOL across all the 5 domains of Seattle Angina Questionnaire overtime for the whole data. Multitrajectory analyses revealed 4 HRQOL trajectory subgroups including high (25.1%), largely increased (32.3%), largely decreased (25.0%), and low (17.6%) trajectories. Age, sex, body mass index, diabetes mellitus, previous history of myocardial infarction, smoking, depression, anxiety, type of treatment received, and perceived social support were significant predictors of differences among these trajectory subgroups. CONCLUSIONS: This study highlights variations in longitudinal trajectories of HRQOL in patients with CAD. Despite overall improvements in HRQOL, about a quarter of our cohort experienced a significant decline in their HRQOL over the 5-year period. Understanding these HRQOL trajectories may help personalize prognostic information, identify patients and HRQOL domains on which clinical interventions are most beneficial, and support treatment decisions for patients with CAD.