Meng Zhuda, Song Liying, Wang Shuang, Duan Guosheng
Department of Thyroid Surgery, Changzhi People's Hospital, Changzhi, People's Republic of China.
Department of Thyroid Surgery, First Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Clin Epidemiol. 2025 Feb 17;17:87-104. doi: 10.2147/CLEP.S494215. eCollection 2025.
This study aims to investigate the potential association between non-selective RET kinase inhibitors and thyroid dysfunction (TD) by conducting a pharmacovigilance analysis using data from the US FDA Adverse Event Reporting System (FAERS).
Data for non-selective RET MKIs were obtained from the FAERS database, spanning the first quarter of 2015 to the fourth quarter of 2023. Disproportionality analysis was used to quantify the AE signals associated with non-selective RET MKIs and to identify TD AEs. Subgroup analyses and multivariate logistic regressions were used to assess the factors influencing the occurrence of TD AEs. Time-to-onset (TTO) analysis and the Weibull Shape Parameter (WSP) test were also performed.
Descriptive analysis revealed an increasing trend in TD adverse events linked to non-selective RET MKIs, with a notable proportion of serious reactions reported. Disproportionality analysis using ROR, PRR, BCPNN, and EBGM algorithms consistently demonstrated a positive association between Sunitinib, Cabozantinib, and Lenvatinib with TD adverse events. Subgroup analyses highlighted differential susceptibility to TD based on age, gender, and weight, with varying patterns observed for each inhibitor. Logistic regression analyses identified factors independently influencing the occurrence of TD adverse events, emphasizing the importance of age, gender, and weight in patient stratification. Time-to-onset analysis indicated early manifestation of TD adverse events following treatment with non-selective RET MKIs, with a decreasing risk over time.
The results of our study indicate a correlation between the use of non-selective RET MKIs and the occurrence of TD AEs. This may provide support for the clinical monitoring and risk identification of non-selective RET MKIs. Nevertheless, further clinical studies are required to substantiate the findings of this study.
本研究旨在通过使用美国食品药品监督管理局不良事件报告系统（FAERS）的数据进行药物警戒分析，调查非选择性RET激酶抑制剂与甲状腺功能障碍（TD）之间的潜在关联。
从FAERS数据库获取2015年第一季度至2023年第四季度非选择性RET MKIs的数据。采用不成比例分析来量化与非选择性RET MKIs相关的不良事件信号，并识别TD不良事件。进行亚组分析和多因素逻辑回归以评估影响TD不良事件发生的因素。还进行了发病时间（TTO）分析和威布尔形状参数（WSP）检验。
描述性分析显示，与非选择性RET MKIs相关的TD不良事件呈上升趋势，报告了相当比例的严重反应。使用ROR、PRR、BCPNN和EBGM算法进行的不成比例分析一致表明，舒尼替尼、卡博替尼和乐伐替尼与TD不良事件之间存在正相关。亚组分析强调了基于年龄、性别和体重对TD的不同易感性，每种抑制剂观察到不同模式。逻辑回归分析确定了独立影响TD不良事件发生的因素，强调了年龄、性别和体重在患者分层中的重要性。发病时间分析表明，非选择性RET MKIs治疗后TD不良事件早期出现，风险随时间降低。
我们的研究结果表明非选择性RET MKIs的使用与TD不良事件的发生之间存在相关性。这可能为非选择性RET MKIs的临床监测和风险识别提供支持。然而，需要进一步的临床研究来证实本研究的结果。
