Real-world safety profile of elexacaftor/tezacaftor/ivacaftor: a disproportionality analysis using the U.S. FDA adverse event reporting system

Background Elexacaftor/Tezacaftor/Ivacaftor (ETI) has demonstrated significant efficacy in enhancing clinical outcomes for patients with cystic fibrosis (CF). Despite this, comprehensive post-marketing assessments of its adverse drug events (ADEs) remain insufficient. This study aims to analyze the ADEs associated with ETI using the U.S. FDA Adverse Event Reporting System (FAERS). Methods We conducted a pharmacovigilance analysis utilizing FAERS data from Q4 2019 to Q3 2024. Reports of ADEs related to ETI were extracted, and disproportionality analyses—including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS)—were employed to evaluate signal strength. Additionally, a time-to-onset (TTO) analysis was performed. Results A total of 28,366 ETI-related ADEs were identified, spanning 27 organ systems. We identified 322 positive signals, with signals consistent with the drug label including headache (702 cases, ROR 2.75), infective pulmonary exacerbation of CF (691 cases, ROR 384.24), rash (538 cases, ROR 2.72), and cough (507 cases, ROR 3.79). Unexpected signals were also noted, such as anxiety (494 cases, ROR 4.16), depression (364 cases, ROR 4.59), insomnia (281 cases ROR 2.83), nephrolithiasis (79 cases, ROR 3.63) and perinatal depression (4 cases, ROR 13.59). The TTO analysis indicated that the median onset of ADEs was 70 days, with 37.08% occurring within the first month. Subgroup analyses revealed that females exhibited a higher reporting rank for mental disorder and constipation, whereas in males, they were insomnia, abdominal pain, and nasopharyngitis. Conclusion This study highlights both recognized and unexpected ADEs associated with ETI, underscoring the necessity for ongoing monitoring, particularly concerning psychiatric conditions. The subgroup analysis suggests a need for personalized treatment strategies to optimize patient care.