Evidence map›Paper›PMID 41704657›Full record

ArticleFrontiers in neurology2025

Real-world analysis of gender differences in drug-induced insomnia: evidence from FAERS and CVARDD databases.

Yuntai Wang, Shengjie Wang, Fuxing Liu

Abstract read
In one paragraph

Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yuntai Wang *Department of Rehabilitation Medicine, Hubei Provincial Hospital of Integrated Chinese and Western Medicine, Wuhan City, Hubei Province, China.
Shengjie Wang *Department of Rehabilitation Medicine, Hubei Provincial Hospital of Integrated Chinese and Western Medicine, Wuhan City, Hubei Province, China.
Fuxing LiuDepartment of Rehabilitation Medicine, Hubei Provincial Hospital of Integrated Chinese and Western Medicine, Wuhan City, Hubei Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Insomnia 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. Objective: To 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. Methods: We 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. Results: A 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. Conclusion: This 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.

Indexed as

disproportionality analysisdrug-induced insomniaFAERS databasegender differencesmedication safetyreal-world data

Identifiers

PMID41704657
PMCPMC12907211

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