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Mining and analysis of adverse event signals of Cariprazine based on the real-world data of FAERS database
Haohao Zhu1, Yucai Qu1, Zhiqiang Du1
1Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi, Jiangsu, China.
Objective:
This study aims to analyze the adverse events (AEs) of Cariprazine based on the FAERS database, providing evidence for its safety surveillance.
Methods:
For signal quantification of Cariprazine-related AEs, we used disproportionality analysis including the Ratio of Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS) algorithms.
Results:
We selected Cariprazine-related AE reports from the FAERS database from the fourth quarter of 2015 to the first quarter of 2023, and performed a detailed data analysis. Out of a total of 12,278,580 case reports, 3659 were found to be directly related to Cariprazine. We identified 140 Preferred Terms (PT) to describe these AEs, finding that they involved 27 organ systems. Specifically, AEs related to eye disorders such as Cataract cortical, Cataract nuclear, Accommodation disorder, Lenticular opacities, Oculogyric crisis, Dyschromatopsia were not explicitly mentioned in the drug's leaflet, indicating the presence of new ADR signals.
Conclusion:
Analysis of the FAERS database identified AEs associated with Cariprazine, notably in eye disorders not previously documented in the drug's official leaflet. These findings emphasize the need for continuous post-market surveillance and awareness among healthcare professionals regarding potential new ADR signals.
