Evolving Trends and Drug Class Dynamics in Drug‐Induced Myocarditis: A 2‐Decade Comparative Analysis of Pharmacovigilance Data
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Drug-induced myocarditis has emerged as an increasingly significant concern with both established and novel medications. This study aimed to identify temporal trends and high-risk populations in drug-induced myocarditis through cross-regulatory pharmacovigilance analysis. METHODS: Data from the US Food and Drug Administration Adverse Event Reporting System and the Japanese Adverse Drug Event Report databases were analyzed from 2004 to 2023. Drugs associated with myocarditis were identified and classified by therapeutic class, with trends evaluated using linear regression, stratified by age and sex. RESULTS: Drug-induced myocarditis was reported in 9983 cases in the US Food and Drug Administration Adverse Event Reporting System (increasing from 114 to 1819) and 3718 cases in the Japanese Adverse Drug Event Report database (rising from 18 to 655) from 2004 to 2023. Monoclonal antibodies and antipsychotics were the fastest-growing risk categories, a trend led by monoclonal antibodies in the US Food and Drug Administration Adverse Event Reporting System (+26.82 cases/year) and corroborated in the Japanese Adverse Drug Event Report database (+13.88 cases per year). Clozapine was the most frequently reported single drug in the US Food and Drug Administration Adverse Event Reporting System (12.79% of all cases, +6.96 cases per year). These trends showed consistent patterns across population subgroups; age-stratified analysis revealed that the increase in monoclonal antibodies was concentrated in the older group, whereas the trend for antipsychotics was most prominent in adults. Gender-specific analysis showed that trends for monoclonal antibodies and antipsychotics were more pronounced in men, whereas chemotherapy agents increased more in women. CONCLUSIONS: Integrated analysis of multinational pharmacovigilance data enhances real-time risk detection and underscores the need for precision surveillance strategies targeting high-risk therapies and vulnerable populations.
Authors: Linping Si, Haoyang Xiang, Qingyuan Zhang, Shengyang Xiao, Haitao Yuan
Language: English
Subfield: Toxicology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,810
OpenAlex ID: W4416947788