A real-world disproportionality analysis of ospemifene: data mining of the public version of FDA adverse event reporting system

Abstract

ABSTRACT Background Ospemifene has been authorized for the treatment of vulvovaginal atrophy (VVA). This study wasto evaluate adverse events (AEs) associated with ospemifene by data mining the US Food and Drug Administration Adverse Event Reporting System (FAERS). Methods The signals of AEs linked to ospemifene were measured using disproportionality analyses, such as the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multi-item gamma Poisson shrinker (MGPS) algorithms. Results There were 2283 events of ospemifene being the ’primary suspected (PS)’ AE out of the 12,692,824 reports from the FAERS database. Ospemifene-induced AEs hit 25 organ systems. There were 726 severely disproportional preferred terms (PTs) that complied with the four algorithms. The investigation turned up a number of anticipated adverse drug reactions (ADRs), and significant unanticipated ADRs linked to eye and renal problems were found, indicating potential side effects not yet included in the prescription instructions. Conclusion We detected novel AEs signals for ospemifene, and the results of our investigation were compatible with clinical observations. This suggests that further prospective clinical trials are required to confirm these findings and demonstrate their link. Our findings might be useful supporting data for ospemifene safety research in the future.