Abstract
OBJECTIVE: Efgartigimod alfa is an important novel drug for the treatment of myasthenia gravis. However, postmarketing safety data for this drug is limited, underscoring the need for comprehensive safety evaluations in real-world populations. DESIGN AND SETTING: This study aims to identify adverse event (AE) signals associated with efgartigimod alfa using the Food and Drug Administration Adverse Event Reporting System (FAERS) database, with a focus on evaluating unexpected AEs not previously observed in clinical trials. AE reports with efgartigimod alfa as the primary suspect from the first quarter of 2022 to the fourth quarter of 2023 were extracted. OUTCOME MEASURES: Signal strength was assessed using Reporting Odds Ratio, Proportional Reporting Ratio, Empirical Bayes Geometric Mean and Bayesian Confidence Propagation Neural Network methods at the Preferred Term level. RESULTS: A total of 1403 valid cases were retrieved. Urinary tract infection was the most reported AE, while procedural headache demonstrated the strongest signal across all four algorithms. Sepsis, atrial fibrillation and transient ischaemic attack were significant unexpected AEs. The median onset time for AEs was 57.00 days, with cumulative incidence of AEs reaching 37.31% at 30 days and 64.25% at 100 days post-treatment initiation. CONCLUSIONS: Our analysis of real-world data from the FAERS database revealed that most significant AEs were consistent with clinical trials, but some unexpected AEs were additionally identified, warranting further investigation.