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DOI 10.1038/s41598-025-24262-7

Медицинская библиотека · Scientific reports · 2025

Identifying high-risk drugs and demographic patterns in drug-induced liver injury from FAERS and CVARD analyses.

He Yun, Chen Xiao-Dong, Wu Shi-Nan, Zhou Chao-Bing, Wang Peng-He, Tang Shi-Hang, Sun Yan-Shuo, Zhang Chen-Yu, Wang Bo-Zhao, Gao Chun-Hong, Zhu Guang-Ping, Wu Hui-Zhong

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Аннотация

Drug-induced liver injury (DILI) is a major cause of acute liver failure, yet identifying associated drugs has been limited by the lack of large-scale analyses. This study addresses this gap by analyzing adverse event reports from the FDA Adverse Event Reporting System (FAERS) and the Canada Vigilance Adverse Reaction Database (CVARD) from 2012 to 2023. FAERS served as the primary database, while CVARD provided validation for the findings. We employed disproportionality analyses (ROR, PRR, BCPNN, MGPS) to identify drugs linked to DILI. Our analysis of 21,738 cases from FAERS identified 172 drugs with significant DILI signals, including high-risk drugs such as dapsone, isoniazid, and nitrofurantoin, which showed the strongest associations (BCPNN > 3). The most frequently implicated drug classes included antineoplastics, antibacterials, and direct-acting antivirals. Time-to-onset of DILI varied significantly across drug classes, with antibacterials exhibiting the shortest median onset (54 days) and immunosuppressants the longest (297 days). Gender and age were also found to be important risk factors, with higher DILI rates observed in females and older adults. Systemic drug administration, particularly through oral and intravenous routes, was most commonly associated with DILI, with serious outcomes reported in 55.9% of cases, including 30.8% requiring hospitalization. While these findings provide valuable insights into drug safety and clinical decision-making, the study's limitations, including potential biases from the spontaneous reporting nature of FAERS and CVARD, should be acknowledged. Overall, the findings highlight the importance of personalized monitoring and risk stratification to enhance medication safety and improve patient outcomes.

Для цитирования: He Yun, Chen Xiao-Dong, Wu Shi-Nan, Zhou Chao-Bing, Wang Peng-He, Tang Shi-Hang, Sun Yan-Shuo, Zhang Chen-Yu, Wang Bo-Zhao, Gao Chun-Hong, Zhu Guang-Ping, Wu Hui-Zhong. Identifying high-risk drugs and demographic patterns in drug-induced liver injury from FAERS and CVARD analyses.. Scientific reports. 2025. DOI: 10.1038/s41598-025-24262-7.

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