Thromboembolic events associated with angiogenesis inhibitors: a real-world study of data from the food and drug administration adverse event reporting system (FAERS) database.

Background: Angiogenesis inhibitors are vital in cancer treatment but are increasingly linked to thromboembolic events (TEEs), impacting patient outcomes. Despite extensive clinical trials, real-world data on TEEs associated with these agents remain limited. This study examines real-world TEEs patterns using the FDA Adverse Event Reporting System (FAERS).

Method: A retrospective pharmacovigilance analysis was conducted using FAERS data spanning from 2014 to 2024. Reporting odds ratio (ROR) and Bayesian confidence propagation neural network (BCPNN) was applied to identify significant safety signals. A signal was considered present when the lower limit of the 95% confidence interval for ROR (ROR025) > 1 and that for information component (IC025) > 0, with a minimum requirement of three or more reported cases.

Results: A total of 13,897 TEEs were identified, with 34.9% classified as arterial thromboembolism events (ATEs), 26.5% as venous thromboembolism events (VTEs), and 38.6% as TEEs of unknown origin (other TEEs). Our findings indicate a significant correlation between the use of angiogenesis inhibitors and an increased reporting frequency of TEEs. The disproportionality analysis revealed strong signals for several agents, with the top five drugs being cediranib, aflibercept, ramucirumab, cabozantinib, and sunitinib. The median time-to-onset (TTO) was 32 days (IQR: 6-141), with 48.5% of cases occurring within the first month and 12% persisting beyond one year. Temporal analysis demonstrated a declining incidence pattern, confirmed by Weibull distribution (shape parameter β = 0.63, indicating early failure type). The most frequently reported outcomes of TEEs associated with angiogenesis inhibitors were hospitalization and other serious events.

Conclusion: This study provides a real-world assessment of TEES risk associated with angiogenesis inhibitors. Identifying high-risk agents and temporal patterns underscores the need for early monitoring and highlights their contribution to TEEs in clinical practice.