Table 1_Real-world analysis of gender differences in drug-induced insomnia: evidence from FAERS and CVARDD databases.docx

BackgroundInsomnia is a common sleep disorder that substantially impairs quality of life. Drug-induced insomnia (DII), an important cause of secondary insomnia, is often underrecognized, and many potential signals are not yet documented in drug labels. Evidence regarding sex-specific differences in DII remains limited, hindering the development of tailored safety strategies.
ObjectiveTo identify drug–insomnia associations, assess sex-specific differences, validate signals in an independent database, and characterize the time-to-onset (TTO) of high-risk drugs using large-scale real-world pharmacovigilance data.
MethodsWe conducted a retrospective observational pharmacovigilance study using insomnia-related reports from FAERS (2004Q1–2025Q2). Disproportionality analyses (ROR, PRR, BCPNN, MGPS) were performed, and sex-stratified associations were compared using Wald chi-square tests. Signals were externally validated in the Canadian Vigilance Adverse Reaction Database (CVARDD). Weibull models were applied to evaluate TTO for the drugs with the highest insomnia report counts.
ResultsA total of 266,429 insomnia-related reports were identified, with more reports from females (60.1%) than males (32.0%). A total of 237 drugs demonstrated significant disproportionality signals, including several without labeled insomnia risk. Among the 20 most frequently implicated drugs, 15 showed significant sex–drug interactions. Duloxetine exhibited a stronger association in males, whereas niraparib and levothyroxine showed higher risks in females. External validation confirmed 124 overlapping drugs with consistent signals. TTO analyses revealed an early-failure pattern (Weibull β < 1) for all five high-reporting drugs, with median onset ranging from 3 to 211.5 days.
ConclusionThis study identified multiple drug–insomnia signals, quantified sex-specific differences, and validated findings in an independent database. These results underscore the importance of recognizing DII and monitoring sex-related variability in clinical practice.