School of Pharmacy and Institute of New Drug Development, Jeonbuk National University, Jeonju Republic of Korea.
College of Pharmacy, Daegu Catholic University, Gyeongbuk Republic of Korea.
Expert Opin Drug Saf. 2024 Sep;23(9):1183-1190. doi: 10.1080/14740338.2024.2309223. Epub 2024 Jan 25.
Through the use of FDA adverse event reporting system (FAERS) dataset, this study analyzes the pattern of time-to-event (TTE) for drugs and adverse events, and suggest ways to identify candidate late-onset events for monitoring.
The duration between administration date of the drug and the onset of adverse events was explored with using FAERS data from 2012-2021. The fold change of proportional reporting ratios or reporting odds ratios were calculated to identify enriched events in the later period and to suggest the late-onset events for further monitoring. To compare the findings, we used the claims database of the Korean National Health Insurance Service (NHIS).
A total of 1,426,781 reports were included. The median TTE was 10 days (interquartile range [IQR]: 0-98 days), with 11.5% ( = 164,093) reporting events that occurred at least one year after administration. TTE and fold change analysis captured historical cases of late-onset events, while generating an additional less-explored list of events. The results for tumor necrosis factor (TNF) inhibitors were compared using the NHIS dataset.
Our study provides a comprehensive analysis of the FAERS dataset, focusing on TTE data. Periodic summarization of reports would be helpful in monitoring the late-onset events.
本研究利用美国食品药品监督管理局不良事件报告系统(FAERS)数据集,分析药物和不良事件的时变(TTE)模式,并提出识别候选迟发事件进行监测的方法。
利用 2012-2021 年 FAERS 数据,探索药物管理日期与不良事件发生之间的持续时间。通过计算比例报告率或报告比值比的倍数变化,识别后期富集的事件,并提出进一步监测的迟发事件。为了比较研究结果,我们使用了韩国国家健康保险服务(NHIS)的索赔数据库。
共纳入 1,426,781 例报告。TTE 的中位数为 10 天(四分位距 [IQR]:0-98 天),有 11.5%( = 164,093)报告的事件发生在给药后至少一年。TTE 和倍数变化分析捕获了迟发事件的历史病例,同时生成了一个额外的、较少探索的事件列表。使用 NHIS 数据集比较了肿瘤坏死因子(TNF)抑制剂的结果。
本研究对 FAERS 数据集进行了全面的 TTE 数据分析,为监测迟发事件提供了有价值的信息。定期总结报告将有助于监测迟发事件。