Biopsychosocial Predictors of Health-Related Quality of Life in Patients with Established Coronary Artery Disease: A Systematic Review with Exploratory Meta-Analyses

Coronary artery disease (CAD) is associated with substantially impaired health-related quality of life (HRQoL). Although depression is the most consistently studied psychosocial predictor of HRQoL in CAD populations, the biopsychosocial model proposes a substantially broader predictor space encompassing social factors (social support, marital quality, stressful life events), biological factors (frailty, peripheral artery disease, cognitive function), and additional psychological constructs (personality, illness perception, coping, resilience, anhedonia, burnout, and posttraumatic stress). Existing systematic reviews have addressed components of this question in isolation but none has simultaneously integrated biological, psychological, and social predictors of HRQoL within a single established-CAD framework using a pre-specified adjusted-analysis inclusion criterion. This protocol specifies all methods for a systematic review with exploratory meta-analyses designed to identify, critically appraise, and synthesise multivariable-adjusted associations between biopsychosocial predictors and HRQoL in patients with established CAD. 2. Objectives The pre-specified objectives of this systematic review are: Systematically identify eligible published evidence on biopsychosocial predictors of HRQoL in established CAD from PubMed/MEDLINE and Europe PMC (January 2011 to 24 June 2026). Estimate the pooled association between PHQ-8 depressive symptoms (continuous, per 1-unit increase) and SAQ angina health status as the primary meta-analytic objective, chosen a priori because depression is the most extensively studied modifiable psychological predictor in CAD and the SAQ is the most widely used disease-specific HRQoL instrument in this population. Conduct pre-specified exploratory meta-analyses for (i) depression/anxiety predicting SF physical component score (PCS) and (ii) frailty (Fried Frailty Phenotype) predicting SF PCS, where sufficient poolable data exist. Synthesise all remaining biopsychosocial predictors through narrative methods using the SWiM reporting framework. Assign GRADE certainty ratings to all quantitative and narrative synthesis findings and identify priority evidence gaps.