High-signal drug assessment for drug-related aortic aneurysm and dissection rupture: Evidence from real-world databases and animal experiments

<p>Background: Aortic rupture represents the most critical complication of aortic aneurysm and dissection (AAD). Identifying and avoiding drugs associated with increased aortic rupture risk may provide immediate clinical benefits. Methods: Data from the FAERS and JADER databases (2004 Q1–2025 Q2) were analyzed. Clinical characteristics associated with adverse events of aortic rupture were summarized. Four disproportionality methods, reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were applied to detect adverse drug reaction signals. Drugs positive in all four methods were classified as high-signal. A time-to-onset analysis was conducted. Rivaroxaban was chosen as a representative drug for further investigation of its impact on aortic rupture risk in an AAD mouse model. Results: FAERS analysis identified 1,313 drug-associated AAD rupture reports involving 333 medications. Antithrombotic agents were most frequently implicated (247 cases, 18.8%), followed by Immunosuppressants (218 cases, 16.6%) and Antineoplastic agents (176 cases, 13.4%). Disproportionality analysis identified 40 drugs with high reporting signals for AAD rupture. Affected individuals were predominantly male (63.8%) and aged ≥65 years (74.0%). Reports and associated fatalities have increased in recent years, although overall mortality has declined. JADER provided 104 reports (17 drugs), consistent with FAERS findings except for the inclusion of SARS-CoV-2 mRNA vaccines. Animal experiments demonstrated that rivaroxaban did not increase AAD incidence but significantly elevated the aortic rupture risk. Conclusion: This study identified 40 high-signal drugs associated with AAD rupture, offering clinical references for safer drug usage. Further studies are necessary to clarify these risks.</p>