Not always a good night's sleep: A global pharmacovigilance risk profiling of drug-induced sleep disorders.

Authors

Mohan Zhang, Jinglin Li, Shasha Huang, Hongyuan You, Wen Li, Shurong Gong, Ling Wang

Published in

Sleep medicine. Volume 147. Pages 109161. Jul 28, 2026. Epub Jul 28, 2026.

Abstract

Sleep disorders and disturbances affect more than one-third of the global population. Although certain drugs have been implicated, the real-world breadth and strength of these signals across therapeutic classes remain poorly characterised. This study aimed to systematically profile drug-induced sleep disorders and disturbances using large-scale pharmacovigilance data and to identify drugs with disproportionate reporting, including those not previously well recognised.
We analyzed 21 years of post-marketing surveillance data using four disproportionality algorithms (Reporting Odds Ratio [ROR], Proportional Reporting Ratio [PRR] with χ², Bayesian Confidence Propagation Neural Network [BCPNN], and Multi-item Gamma Poisson Shrinker [MGPS]), leveraging their complementary strengths in sensitivity, bias reduction, stability, and rare-event detection. Positive signals were defined as meeting pre-specified thresholds for all four algorithms simultaneously.
Among over 22 million reports, 411,736 involved sleep disorders (58.9% female). Overall, 131 drugs showed disproportionate signals; 24 (18.3%) lacked FDA-labelled warnings. Varenicline accounted for the most reports (n = 16,200), whereas montelukast showed the strongest signal (ROR 11.78, 95% CI 11.40-12.18). Median time to onset was 36 days (IQR: 6-260), with an early failure-type profile (Weibull β = 0.449, 95% CI 0.447-0.452). Among therapeutic classes, antineoplastic and immunomodulating agents (ATC L01) showed the highest disproportionality (ROR 9.19, 95% CI 8.86-9.53).
Multiple drug classes show disproportionate reporting for sleep disorders and disturbances with an early-onset risk profile, supporting monitoring at treatment initiation. Approximately one in five of these drugs lack US labelling warnings, highlighting the need for clinical awareness and mechanistic studies.

PMID:
42551056
Bibliographic data and abstract were imported from PubMed on 05 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.