ArticleFrontiers in pharmacology2024
Adverse event signal mining and severe adverse event influencing factor analysis of Lumateperone based on FAERS database.
Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comprehensive safety analysis of adverse events associated with eptinezumab in migraine treatment.Scientific reports · 2025Pooled it
- Heterogeneity in adverse events associated with lumateperone: a study on potential subgroup-specific differences.The international journal of neuropsychopharmacology · 2026Article
- Mining of Adverse Event Signals Associated with Fluticasone Furoate/Umeclidinium/Vilanterol Triple Therapy: A Post-Marketing Analysis Based on FAERS.Pharmacy (Basel, Switzerland) · 2025Article
- Mining and analysis of adverse event signals of isotretinoin based on the real-world data of FAERS database.Frontiers in medicine · 2025Article
- Safety evaluation of medroxyprogesterone acetate: a pharmacovigilance analysis using FDA adverse event reporting system data.Frontiers in pharmacology · 2024Article
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Authors and funding
7 authors.
Funding
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Abstract
Background: Lumateperone has been approved by the Food and Drug Administration (FDA) for the treatment of schizophrenia in adults since 2019, however, there is still a lack of data report on adverse reactions in real-world settings. Conducting data mining on adverse events (AEs) associated with Lumateperone and investigating the risk factors for serious AEs can provide valuable insights for its clinical practice. Methods: AE reports in the FDA Adverse Event Reporting System (FAERS) from 2019 Q4 (FDA approval of Lumateperone) to 2024 Q1 were collected and analyzed. Disproportionality in Lumateperone-associated AEs was evaluated using the following parameters: Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS). Univariate and multivariate logistic regression analyses were conducted to identify the risk factors for Lumateperone-induced severe AEs. Results: A total of 2,644 reports defined Lumateperone as the primary suspected drug was collected, including 739 reports classified as severe AEs and 1905 reports as non-severe AEs. The analysis revealed that 130 preferred terms (PTs) with significant disproportionality were based on the four algorithms, 67 (51.53%) of which were not included in the product labeling, affecting 6 systems and organs. In addition, dizziness (81 cases) was the most reported Lumateperone-associated severe AEs, and tardive dyskinesia showed the strongest signal (ROR = 186.24). Logistic regression analysis indicated that gender, bipolar II disorder, and concomitant drug use are independent risk factors for Lumateperone-associated severe AEs. Specifically, female patients had a 1.811-fold increased risk compared with male patients (OR = 1.811 [1.302, 2.519], Conclusion: Collectively, this study provides critical insights into the safety profile of Lumateperone. It highlights the need for cautious use in high-risk populations, such as females and individuals with bipolar II disorder, and emphasizes the importance of monitoring for AEs, including dizziness and tardive dyskinesia. Healthcare also should remain alert to potential AEs not listed in the prescribing information to ensure medical safety.
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