ArticleWorld journal of oncology2026
Strong Signals of Adverse Events in Tyrosine Kinase Inhibitor Therapy for Liver Cancer Treatment.
Article in World journal of oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Emerging Role of Ferroptosis in Chemotherapy-Associated Hepatorenal Toxicity: Mechanistic Insights and Toxicological Perspectives.ACS pharmacology & translational science · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study was to identify strong adverse event (AE) signals associated with four tyrosine kinase inhibitors (TKIs) (sorafenib, regorafenib, lenvatinib, and cabozantinib), and compare these signals with regulatory drug facts from multiple global agencies. Methods: Data from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS, 2007 - 2024) were analyzed. Each AE was treated as a binary variable, and logistic regression with robust error estimation was used to identify strong signals (odds ratio > 2, lower 95% confidence interval > 1). AE signals were compared with drug facts from the FDA (USA), European Medicines Agency (EMA, European Union), Pharmaceuticals and Medical Devices Agency (PMDA, Japan), and National Medical Products Administration (NMPA, China). Results: Among 33,801 identifiers (137,345 records), 816 strong AE signals were found. Sorafenib had the most (373), followed by regorafenib (207), lenvatinib (126), and cabozantinib (110). Notable AEs included pharyngeal hemorrhage (sorafenib), retinal artery occlusion (regorafenib), intracranial aneurysm (lenvatinib), and mood swings (cabozantinib). Thirty-two signals had a 100% likelihood of critical outcomes, with no overlap across drugs. AEs were more frequent in males and older populations. Significant discrepancies in AE profiles were observed among regulatory agencies, with low overlap between FAERS and agency data. Conclusions: This study provides a comprehensive analysis of AE signals for four TKIs in liver cancer, identifying associations rather than causal relationships. The findings highlight significant variation in AE profiles and discrepancies between clinical trial data and real-world evidence. These results are hypothesis-generating and emphasize the need for personalized treatments, enhanced monitoring and intervention, and improved global AE reporting, while acknowledging the inherent limitations of spontaneous reporting systems.
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Registered trials
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