ArticleFrontiers in pharmacology2026
Drug-drug interactions between sex hormones and analgesics linked to thromboembolic events: an FDA adverse event reporting system analysis.
Article in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Thromboembolic events, including venous thromboembolism (VTE) and arterial thromboembolism (ATE), are affected by numerous pharmacological factors. Although sex hormones and analgesics have been individually associated with thrombotic risk, the clinical relevance of potential drug-drug interactions (DDIs) between these agents remains unclear. This study examines how DDIs affect reports of thrombosis, including ATE and VTE, and compares them with existing epidemiological data. Methods: A total of 15.9 million reports from the Food and Drug Administration Adverse Event Reporting System (FAERS [JAPIC FAERS]) were evaluated to assess potential DDIs between sex hormones (female and male) and analgesics in relation to VTE and ATE. Disproportionality analyses were conducted using crude reporting odds ratios (cRORs) and DDI signal detection via four complementary statistical methods. Results: Among the cases reviewed, 162,846 patients experienced VTE, and 283,197 experienced ATE. Both sex hormones and analgesics demonstrated significant associations with increased reporting of VTE and ATE. Notably, in the DDI analysis between female hormones and analgesics, thirteen drug pairs were positive across all four algorithms for VTE, whereas only one pair met this criterion for ATE. No consistent DDI signals were identified for male hormones in either VTE or ATE cases. Discussion: Although spontaneous reporting systems have inherent limitations, this study's findings suggest sex-specific differences in the impact of concomitant analgesic use on thromboembolic events. The observed increase in VTE reporting with the combined use of female hormones and analgesics aligns with existing epidemiologic data and underscores the utility of FAERS-based approaches for identifying clinically relevant DDIs.
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