Hepatotoxicity of ALK/ROS1 tyrosine kinase inhibitors in non-small cell lung cancer patients: A pharmacovigilance study based on signal mining and analysis of the FDA adverse event reporting system database

ALK/ROS1酪氨酸激酶抑制剂在非小细胞肺癌患者中的肝毒性:一项基于信号挖掘和FDA不良事件报告系统数据库分析的药物警戒研究

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Abstract

ObjectiveThis study evaluated the hepatotoxicity risk of anaplastic lymphoma kinase (ALK)/ROS1- tyrosine kinase inhibitors (TKIs) in non-small cell lung cancer (NSCLC) using the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS).MethodsA retrospective analysis of 19,611 FAERS reports related to ALK/ROS1-TKIs (2011-2025) identified 1495 hepatotoxicity cases. Disproportionality analysis (reporting odds ratio, proportional reporting ratio, empirical Bayes geometric mean) assessed six ALK-TKIs and three ROS1-TKIs. Temporal trends, clinical outcomes, and differences across TKI generations were examined.ResultsSecond-generation ALK-TKIs (e.g. alectinib) showed the most favorable hepatic safety profile, with the lowest observed mortality (3.5%) and hospitalization (13.0%). First-generation TKIs (crizotinib, ceritinib) and newer agents (lorlatinib, entrectinib) were associated with higher fatality rates (12.0%-13.2%). Most hepatotoxic events (51.9%) occurred within one month; however, 8.37% developed after one year. Mechanistically, the lower risk with second-generation TKIs may reflect less CYP-dependent metabolism and greater target selectivity.ConclusionAnalysis of FAERS reports indicates substantial heterogeneity in hepatotoxicity risk among ALK inhibitors. Second-generation agents showed lower mortality and hospitalization than first- and third-generation counterparts. Crizotinib, ceritinib, and lorlatinib were associated with notably high fatality rates, warranting continuous hepatic monitoring. ROS1 inhibitors (e.g. entrectinib) may exhibit distinct hepatotoxicity profiles. These findings should be interpreted cautiously given inherent reporting biases. Future priorities include prospective studies, biomarker-integrated risk stratification, mechanistic investigation, and AI-enhanced monitoring to optimize the risk-benefit profile of ALK/ROS1-TKIs.

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