ArticleFrontiers in pharmacology2024
Mining and evaluation of adverse event signals for capmatinib based on the 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 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Signal Detection and Pharmacovigilance Analysis of Tamoxifen, Clomiphene, and Letrozole in Polycystic Ovarian Syndrome: A FAERS Database Study.International journal of women's health · 2026Article
- Adverse Events Associated with Tirzepatide: Updated Pharmacovigilance Analysis Using FAERS (2022 Q1-2025 Q1) with an Adapted Time-to-Onset Method.Drug, healthcare and patient safety · 2026Article
- Safety evaluation of medroxyprogesterone acetate: a pharmacovigilance analysis using FDA adverse event reporting system data.Frontiers in pharmacology · 2024Article
- Analysis signals of disproportionate reporting associated with donanemab: A retrospective pharmacovigilance study using the FAERS database.Science progressArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To conduct a comprehensive data analysis based on the FDA's Adverse Event Reporting System (FAERS) to mine possible adverse event (AE) signals of Capmatinib, providing valuable references for its clinical application. Methods: Capmatinib was the primary suspected drug in the search of FAERS database from the second quarter of 2020 to the fourth quarter of 2023. Data processing, screening, and classification were performed using methods such as the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS). Results: A total of 1,991 AE reports directly related to Capmatinib were screened, identifying 269 Preferred Terms (PTs) involving 26 System Organ Classes (SOCs). Besides the AEs recorded in the drug label (such as edema, nausea, fatigue, and dyspnea), the study unearthed other high-risk AEs not listed in the label, including Renal and urinary disorders, Vocal cord paralysis, and Ear and labyrinth disorders. Among these, renal and urinary disorders, and ear and labyrinth disorders had a higher frequency and intensity of signals, suggesting that their mechanisms of occurrence could be a future research direction. Conclusion: This study uncovered new potential AEs of Capmatinib based on the FAERS database, providing reference for its safe clinical use. Special attention should be given to the occurrence of ear and labyrinth disorders and renal and urinary disorders, primarily presenting as pseudo-acute kidney injury, during treatment.
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