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Cardiac adverse events associated with quetiapine: Disproportionality analysis of FDA adverse event reporting system
Authors:Yamin Shu  Yiling Ding  Lulu Liu  Qilin Zhang
Affiliation:1. Department of Pharmacy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China;2. Graduate School of Pharmaceutical Sciences, University of Tokyo, Tokyo, Japan;3. School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China;4. Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Abstract:

Objective

Quetiapine, an atypical second-generation antipsychotic drug, is approved for treatment of schizophrenia, bipolar disorder, and depression. Due to the limitations of clinical trials, the association between quetiapine and rare cardiac adverse events (AEs) is still unclear. This study is to evaluate quetiapine-associated cardiac AEs through data mining of FDA Adverse Event Reporting System (FAERS).

Methods

Reporting odds ratio (ROR) was used to quantify the signals of quetiapine-related cardiac AEs from the first quarter (Q1) of 2018–2022 Q1. Serious and nonserious cases were compared, and signals were prioritized using a rating scale.

Results

A total of 1004 cases of quetiapine-associated cardiac AEs were identified, with 31 signals being detected, among which 13 AEs were identified as new and unexpected signals. Besides, nine and 22 cardiac AEs were identified as moderate and weak clinical priority. The median TTO for moderate and weak clinical priority signals were 0 and 4 days, respectively. All of the cardiac AEs had early failure type characteristics, suggesting that most of the patients developed cardiac AEs in a few days after quetiapine treatment, and that the risk of cardiac AEs occurrence would be gradually decreased over time.

Conclusion

Our study provided valuable evidence for health-care professionals to mitigate the risk of quetiapine-associated cardiac AEs based on an extensive analysis of a real-world, large-sample FAERS database, and prioritize cardiac AE signals.
Keywords:cardiac adverse events  data mining  disproportionality analysis  FAERS  pharmacovigilance  quetiapine
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