Yu Yue, Chen Jun, Li Dingcheng, Wang Liwei, Wang Wei, Liu Hongfang
Department of Medical Informatics, School of Public Health, Jilin University, Changchun, Jilin 130021, China.
Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55901, USA.
Sci Rep. 2016 Apr 22;6:24955. doi: 10.1038/srep24955.
Increasing evidence has shown that sex differences exist in Adverse Drug Events (ADEs). Identifying those sex differences in ADEs could reduce the experience of ADEs for patients and could be conducive to the development of personalized medicine. In this study, we analyzed a normalized US Food and Drug Administration Adverse Event Reporting System (FAERS). Chi-squared test was conducted to discover which treatment regimens or drugs had sex differences in adverse events. Moreover, reporting odds ratio (ROR) and P value were calculated to quantify the signals of sex differences for specific drug-event combinations. Logistic regression was applied to remove the confounding effect from the baseline sex difference of the events. We detected among 668 drugs of the most frequent 20 treatment regimens in the United States, 307 drugs have sex differences in ADEs. In addition, we identified 736 unique drug-event combinations with significant sex differences. After removing the confounding effect from the baseline sex difference of the events, there are 266 combinations remained. Drug labels or previous studies verified some of them while others warrant further investigation.
越来越多的证据表明，药物不良事件（ADEs）存在性别差异。识别这些ADEs中的性别差异可以减少患者发生ADEs的情况，并有助于个性化医疗的发展。在本研究中，我们分析了美国食品药品监督管理局不良事件报告系统（FAERS）的标准化数据。进行卡方检验以发现哪些治疗方案或药物在不良事件方面存在性别差异。此外，计算报告比值比（ROR）和P值以量化特定药物 - 事件组合的性别差异信号。应用逻辑回归来消除事件基线性别差异的混杂效应。我们在美国最常用的20种治疗方案的668种药物中检测到，有307种药物在ADEs方面存在性别差异。此外，我们识别出736种具有显著性别差异的独特药物 - 事件组合。在消除事件基线性别差异的混杂效应后，仍有266种组合。药物标签或先前的研究证实了其中一些，而其他的则需要进一步研究。
