Background: Upadacitinib was approved to treat rheumatoid arthritis, psoriasis, ulcerative colitis, ankylosing spondylitis, and atopic dermatitis. This study assessed the adverse events (AEs) associated with upadacitinib by mining data from 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 upadacitinib-associated AEs.
Results: A total of 3,837,420 reports of AEs were collected from the FAERS database, of which 4494 reports were identified with upadacitinib as the "primary suspect (PS)". Upadacitinib-induced AEs occurrence targeted 27 system organ clases (SOCs). A total of 200 significant disproportionality PTs conforming to the four algorithms were simultaneously retained. Unexpected significant AEs, such as arthralgia, musculoskeletal stiffness, diverticulitis, and cataract might also occur. The median onset time of upadacitinib-associated AEs was 65 days (interquartile range [IQR] 21-182 days), and most of the onsets occurred within the first 1, 2, 3, and 4 months after initiation of upadacitinib.
Conclusion: This study found potential new AEs signals and might provide important support for clinical monitoring and risk identification of upadacitinib.
Keywords: FAERS; adverse events; data mining; pharmacovigilance; post-marketing surveillance; upadacitinib.