High Throughput Pharmacovigilance Screening for Roflumilast Adverse
Effects in Real-World Settings: A Sequence Symmetry Analysis
Abstract
Background Roflumilast is an add-on therapy for COPD following
exacerbations, but real-world safety data in the U.S. is limited.
Objective This study aimed to identify safety signals
associated with roflumilast use through a high-throughput signal
detection algorithm. Methods Using sequence symmetry analysis
(SSA), we analyzed Marketscan databases for new roflumilast users
(2011–2021). We screened for adverse effects across 211 therapeutic
classes within 365 days of initiation. Sensitivity analyses were
conducted by sex, age, and observation period. Crude and adjusted
sequence ratios (cSR, aSR) were reported with 95% confidence intervals
(CIs). Results Among 11,091 patients (53% aged 65+, 52%
female), 19 safety signals were identified. Strong associations were
observed with anti-thyroid agents (aSR, 3.62; 95% CI: 1.44–10.36),
parathyroid hormones (aSR, 2.65; 95% CI: 1.33–5.51), and meglitinides
(aSR, 2.43; 95% CI: 1.15–5.35). While many signals aligned with prior
clinical trial data, novel associations with anti-thyroid and
parathyroid agents were discovered. Conclusion In our study, we
detected 19 safety signals for roflumilast, including notable
associations with anti-thyroid agents and parathyroid hormones. Future
investigations using more robust study designs are warranted to evaluate
those signals.