基于FAERS数据库的普拉替尼和塞普替尼不良事件信号挖掘与分析

Adverse event signals of pralsetinib and selpercatinib based on the FAERS database

摘要

目的: 挖掘并分析普拉替尼和塞普替尼上市后的药物不良事件(adverse drug event,ADE)信号,对两药相关的ADE进行对比,为临床在药物选择时作出更为全面和准确的判断。方法: 收集美国FDA不良事件报告系统(FAERS)数据库中2020年4月至2024年12月期间的普拉替尼和塞普替尼的ADE报告,采用报告比值比(reporting odds ratio, ROR)法进行数据挖掘与分析。结果: 通过挖掘分析,发现两药的不良事件(adverse events, AE)存在差异,如在累及系统中,虽然两药排序前3位的首选系统器官分类(system organ class,SOC)一致,但普拉替尼在胃肠系统疾病、呼吸系统胸及纵膈疾病、神经系统等系统中检测出了较多的风险信号,而塞普替尼在肝胆系统疾病、皮肤及皮下组织类疾病等系统中的相关不良反应比普拉替尼多。除发生频次的不同,两药在相同系统中可能发生的不良反应事件也存在一定的差异,如在心血管系统毒性中,普拉替尼表现为心肌坏死标志物增加,而塞普替尼则表现为心电图QT间期延长,这些不同在临床使用过程中值得关注。结论: 普拉替尼和塞普替尼在药品不良反应方面具有一定的共性和特性,临床在选用药物过程中应根据患者的具体情况及药物特点进行个体化选择,以使患者获益最大化。

Abstract

Objective: To identify and analyze post-marketing adverse drug event (ADE) signals associated with pralsetinib and selpercatinib, compare their respective adverse event profiles, and provide a more comprehensive evidence base to support clinical decision-making in drug selection. Methods: ADE reports for pralsetinib and selpercatinib were extracted from the U.S. FDA Adverse Event Reporting System (FAERS) database from April 2020 to December 2024. Disproportionality analysis was conducted using the reporting odds ratio (ROR) method. Results: The analysis revealed significant differences in the adverse event profiles of the two drugs. For instance, in the affected system, although the system organ class (SOC) distribution for the top three adverse events was similar between the two drugs, pratinib was associated with a higher frequency of risk signals in gastrointestinal disorders, respiratory/thoracic/mediastinal disorders, and nervous system disorders. In contrast, cepratinib exhibited a greater incidence of adverse reactions related to hepatobiliary disorders, skin and subcutaneous tissue disorders, and other system-specific effects compared to pratinib. Notably, even within the same SOC, the specific adverse reactions differed between the two drugs. For instance, in regard to cardiovascular toxicity, pralsetinib was linked to elevated myocardial necrosis markers, whereas selpercatinib was more frequently associated with QT interval prolongation. These distinctions highlight the need for drug-specific monitoring in clinical practice. Conclusion: While pralsetinib and selpercatinib share some overlapping adverse effects, their risk profiles exhibit distinct patterns. Individualized drug selection, guided by patient-specific factors and the unique toxicity profiles of each agent, is essential to optimize therapeutic outcomes.

关键词

普拉替尼 / 塞普替尼 / 药品不良事件 / 信号挖掘 / 美国FDA不良事件报告系统

Key words

pralsetinib / selpercatinib / adverse drug event / data mining / FAERS