Mining and analysis of adverse event signals of Mometasone furoate based on real-world data from the FAERS database

Abstract

Abstract Background Mometasone furoate (MF) is a steroidal active pharmaceutical ingredient (API) that has been approved for the treatment of atopic dermatitis, eczema, allergic rhinitis, and chronic rhinosinusitis by the FDA. The aim of the present study was to assess real-world MF-related adverse events (AEs) through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS). Methods Disproportionality analyses, including 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, were employed to quantify the signals of MF-associated AEs. Results Out of 49,659,292 reports collected from the FAERS database, 11,510 reports of MF-associated AEs were identified. A total of 185 significant preferred terms (PTs) conforming to the four algorithms were retained. The most common AEs included epistaxis, nasal dryness, burning, stinging, blood-tinged secretions, pharyngeal inflammation, skin weeping and pruritis allergic reactions, which corresponded to those reported in the specification and clinical trials. Unexpected significant AEs, such as chorioretinopathy, retinal edema, ageusia, anosmia, otorrhea, ear pruritus, auricular swelling and limb reduction defects, might also occur. Conclusion The results of our study were consistent with clinical observations, and we also found potential new and unexpected AEs associated with MF. Prospective clinical studies are needed to confirm these results and determine their relationship. Our results could provide valuable evidence for further safety studies of MF.