Comparative real-world safety profiles of selective β1-adrenergic receptor blockers: A multi-database...

Selective β1-blockers are fundamental in managing hypertension, coronary artery disease, and heart failure. Yet, despite their widespread use, practical guidance on safe and individualized prescribing remains limited. Existing evidence is largely derived from controlled clinical trials, which may not fully capture drug-specific adverse events, sex-related susceptibility, or early-onset risks observed in routine clinical practice. To generate real-world, evidence-based recommendations for the safe use of selective β1-blockers, we compared the adverse event profiles of metoprolol, bisoprolol, and atenolol using 2 large pharmacovigilance systems. Adverse drug events reported for the 3 agents between 2004 and Q2 2025 were retrieved from the US Food and Drug Administration Adverse Event Reporting System, a spontaneous-reporting system, and compared with reports from the Canadian Vigilance Adverse Reaction Online Database. Disproportionality analyses, preferred term mapping, exploratory sex-stratified comparisons, and time-to-onset modeling were conducted to characterize shared reporting patterns, drug-specific signals, and potential patient-level modifiers. Across all 3 agents, disproportionate reporting was observed for a common cardiovascular spectrum that included bradycardia, conduction abnormalities, heart failure, and blood pressure instability. Metoprolol showed prominent reporting signals for BRASH syndrome and neuropsychiatric and suicide-related events. Bisoprolol showed signals for bradyarrhythmia, hyperkalemia, and acute kidney injury. Atenolol showed reporting patterns involving blood pressure perturbations, electrolyte imbalance, and interaction-related events. Exploratory sex-stratified analyses identified differences in the reporting distributions of several PT = preferred terms for metoprolol and atenolol, whereas bisoprolol showed a more balanced distribution. All 3 agents displayed early-failure time-to-onset patterns, supporting closer monitoring after treatment initiation. This real-world pharmacovigilance assessment identifies drug-specific patterns of disproportionate reporting that may inform hypothesis generation and individualized monitoring. Because spontaneous-reporting data cannot establish incidence or causality, the findings should complement, rather than replace, clinical judgment and confirmation in controlled or longitudinal data sources.