Abstract
Background: Canakinumab, a humanized anti-IL-1β monoclonal antibody, is known for its ability to suppress IL-1β-mediated inflammation. However, continuous monitoring of its safety remains essential. Thus, we comprehensively evaluated the safety signals of canakinumab by data mining from FAERS. Methods: We used a disproportionate analysis to quantify canakinumab-related adverse events (AEs) using four algorithms. Clinical prioritization of the detected signals was assessed with a semiquantitative score method. Serious and non-serious outcomes were compared by statistical methods. Additionally, a stratification analysis of serious infections was conducted at the system organ class (SOC) level. Results: A total of 28,496 canakinumab-related AEs were collected, and 71 suspicious signals detected. Among these, 19 preferred terms (PTs) were identified as unexpected signals, including deafness, appendicitis, brain oedema, cushingoid, cellulitis, and papilledema. Of the AEs, 16 were more likely reported as serious outcomes, such as pneumonia, abdominal pain, deafness, and infection. Based on clinical priority score, 44 PTs were classified as weak, 27 as moderate, and none as strong. Furthermore, 30 PTs demonstrated a high level of evidence, primarily derived from FDA prescribing information, randomized controlled trials, and systematic reviews. Stratification analysis of infections and infestations (serious outcomes) revealed a stronger association of severe infections with canakinumab in older or heavier individuals. All positive signals followed an early failure pattern, with the incidence of canakinumab-associated AEs decreasing over time. Conclusions: We found that most of the suspicious signals were associated with infections. More attention should be paid to serious infections, particularly in males, individuals aged ≥60 years, or those weighing >100 kg, who demonstrated the highest risk of serious infections.