ArticleBMC pharmacology & toxicology2025
Risk of drug-induced pericardial effusion: a disproportionality analysis of the FAERS database.
Article in BMC pharmacology & toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Regulatory challenges and current policy for cardiotoxicity detection in oncology drug development.Journal of thrombosis and thrombolysis · 2026Article
- Hydralazine-Associated Pericardial Effusion Causing Cardiac Tamponade Without Hypotension.JACC. Case reports · 2026Article
- Safety signals of perfluorohexyloctane ophthalmic solution in patients with dry eye disease.Frontiers in medicine · 2026Article
- Evolving Trends and Drug Class Dynamics in Drug-Induced Myocarditis: A 2-Decade Comparative Analysis of Pharmacovigilance Data.Journal of the American Heart Association · 2025Article
- Adverse event profile differences between maribavir and valganciclovir: findings from the FDA adverse event reporting system.Frontiers in pharmacology · 2025Article
- Beyond the label: real-world gastrointestinal adverse events associated with vedolizumab - a decade of FAERS pharmacovigilance.Frontiers in pharmacology · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
objectiveBy using the FAERS database, we aim to identify and assess risk signals of adverse drug events (ADEs) potentially causing pericardial effusion, to inform clinical drug management and promote rational drug use.
methodsWe obtained reports of pericardial effusion events from the FAERS database spanning from the first quarter of 2004 to the second quarter of 2024, and identified the top 50 drugs ranked by report frequency or signal strength. Four algorithms, namely the reported odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were employed for signal detection of these drugs. Furthermore, for drugs with positive signals, we conducted sensitivity analyses and employed the Weibull shape parameter test to perform a time to onset (TTO) analysis.
resultsWe identified 20,057 ADEs related to pericardial effusion, involving 19,693 patients for analysis. The patient population comprised 10,187 males (51.7%) and 7,939 females (40.3%). Adults aged 18-65 years were the largest group (7,798 cases, 39.6%). Regarding clinical outcomes, 9,924 patients (50.4%) experienced hospitalization, and 2,770 cases (14.1%) resulted in death. Ranked by the ROR risk signal strength, the top 3 drugs were hydralazine [ROR (95% CI): 27.11 (22.28-33)], dasatinib [ROR (95% CI): 15.62 (14.07-17.33)], and mesalazine [ROR (95% CI): 8.99 (6.84-11.8)]. We conducted a TTO analysis for the 26 drugs with positive signals. The median TTO and interquartile range (IQR) for the top 3 drugs causing the earliest pericardial effusion were: cytarabine 14 (7.5,38), selexipag 14.5 (4.25, 157.75), dabigatran etexilate 29 (9, 229). Most drugs exhibited an early failure type.
conclusionThis study systematically compiled a list of drugs with potential risks of causing pericardial effusion. There is a significant association between pericardial effusion and the use of hydralazine, dasatinib, and mesalazine. Moreover, pericardial effusion is more common in patient groups receiving treatments with antineoplastic and immunomodulating agents.
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