Real-world pharmacovigilance study of drug-induced autoimmune hepatitis from the FAERS database

Abstract This study aims to identify and evaluate the most common drugs associated with the risks of autoimmune hepatitis (AIH) using the FDA Adverse Event Reporting System (FAERS) database. Adverse drug events (ADEs) associated with drug-induced AIH (DI-AIH) were retrieved from the FAERS database (...

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Bibliographic Details
Main Authors: Bu-kun Zhu, Si-ying Chen, Xiang Li, Shu-yun Huang, Zhan-yang Luo, Wei Zhang
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-89272-x
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Summary:Abstract This study aims to identify and evaluate the most common drugs associated with the risks of autoimmune hepatitis (AIH) using the FDA Adverse Event Reporting System (FAERS) database. Adverse drug events (ADEs) associated with drug-induced AIH (DI-AIH) were retrieved from the FAERS database (January 2004–June 2024). Disproportionality analysis was performed to identify drugs significantly linked to DI-AIH, and time-to-onset (TTO) analyses were conducted to evaluate the timing and risk profiles of DI-AIH adverse reactions. Our study identified 2,511 ADEs linked to autoimmune hepatitis. Disproportionality analysis identified 22 drugs significantly associated with AIH risk, including 4 antibiotics, 3 antivirals, 4 cardiovascular drugs, 5 antitumor agents, 2 immunomodulators, 2 nonsteroidal anti-inflammatory drugs, and 1 drug each from the respiratory and nervous system categories. The highest DI-AIH risks were observed with minocycline (ROR = 53.97), nitrofurantoin (ROR = 57.02), and doxycycline (ROR = 16.12). Antitumor drugs had the shortest median TTO (77.00 days), whereas cardiovascular drugs exhibited the longest (668.30 days). Through a comprehensive analysis of the FAERS database, our study identified drugs strongly associated with AIH. Preventing DI-AIH requires careful drug selection and monitoring. This study provides evidence-based insights into implicated drugs, aiming to optimize clinical management and mitigate risks.
ISSN:2045-2322