Research Appraisalobservational

Drug-associated insomnia: A pharmacovigilance study based on FDA adverse event reporting system.

MedicineHuang, Xinyao, Chen, Yingying, Li, Song et al.17 Apr 2026DOI

Clinical Snapshot

50CEBM
Evidence: Weakobservational

PICO Framework

P — PopulationPatients reporting adverse events to FAERS database (2004-2024) with insomnia as outcome
I — InterventionVarious medications identified as primary suspects
C — ComparatorImplicit comparison to expected reporting rates in FAERS database
O — OutcomesInsomnia adverse event reports; signal strength using disproportionality analysis

Bottom Line

This pharmacovigilance study analyzed 20 years of FAERS data to identify medications associated with insomnia reports. While the large dataset and systematic approach provide valuable signal detection, the study has significant limitations inherent to passive surveillance systems. The inability to control for confounders, establish causality, or validate exposures and outcomes limits clinical interpretation. The predominance of nervous system medications among top signals is biologically plausible but requires prospective validation. Clinicians should interpret these findings as hypothesis-generating rather than definitive evidence of causal relationships. The study highlights the importance of monitoring sleep disturbances in patients prescribed identified medications, particularly mefloquine, viloxazine, and flibanserin. However, clinical decision-making should incorporate individual patient factors and established evidence rather than relying solely on pharmacovigilance signals.

Evidence: Weak

Key Findings

  • P Value: Not reported in abstract

  • Effect Size: Signal strength varies by medication (specific values not provided in abstract)

  • Primary Outcome: 179,697 insomnia adverse event reports identified

  • Nnt Or Sensitivity: Top 3 medications by reporting frequency: mefloquine, viloxazine, flibanserin

  • Confidence Interval: Not reported in abstract

Clinical Application

Signal detection useful for hypothesis generation but requires clinical validation Limited applicability as FAERS reflects US prescribing patterns. Australian TGA adverse event data would be more relevant for local practice Patients prescribed medications with potential insomnia risk, particularly nervous system drugs

Abstract

Insomnia has become an increasingly serious public health issue with complex causes, among which medications act as a significant factor. This study aims to systematically detect and evaluate drug adverse event signals associated with insomnia risk using the Food and Drug Administration Adverse Event Reporting System (FAERS) database. The analysis utilized data from the FAERS database covering January 2004 to December 2024. Disproportionality analysis was conducted using 4 algorithms: reporting odds ratio, proportional reporting ratio, information component (IC), and empirical Bayes geometric mean. Potential risk signals were deemed significant only when all 4 algorithms simultaneously met their thresholds. Subgroup analyses were further performed, stratified by age and sex, to assess the robustness of signals across different populations. From 2004 to 2024, there were 179,697 adverse event reports of insomnia in FAERS in which one or more medications were designated as the primary suspect. The top 30 medications with the strongest signal strength were predominantly nervous system medicines (18 types, 60%), followed by respiratory system medicines (3 types, 10%), and genitourinary system and sex hormones (3 types, 10%). The top 3 medications with the highest reporting frequency were mefloquine, viloxazine, and flibanserin. Subgroup analyses revealed distinct drug signal profiles across age groups and genders, with pediatric cases dominated by nervous system and anti-infective agents, adults and the elderly showing additional endocrine or hormonal signals, and sex specific signals such as finasteride in males and flibanserin in females. This pharmacovigilance study identifies insomnia risk signals across multiple drug classes, underscoring the need for clinical vigilance regarding drug-related sleep disturbances. Further prospective research is required to confirm these associations.

References

  1. 1.Huang, X., Chen, Y., Li, S., Wen, Y., Liu, H., & Cao, G. (2026). Drug-associated insomnia: A pharmacovigilance study based on FDA adverse event reporting system. Medicine, 105(16), e48160. https://doi.org/10.1097/MD.0000000000048160
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