利用VAERS数据和MedDRA系统器官分类分析疫苗药物警戒的个体差异:三价流感疫苗的用例研究

Biomedical informatics insights Pub Date : 2017-04-11 eCollection Date: 2017-01-01 DOI:10.1177/1178222617700627
Jingcheng Du, Yi Cai, Yong Chen, Yongqun He, Cui Tao
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引用次数: 8

摘要

个性化和精确的疫苗接种需要考虑个人的性别和年龄。本文提出了系统的方法来研究疫苗接种后不良反应的个体差异,并以三价流感疫苗为例。数据来自1990年至2014年的疫苗不良事件报告系统。我们首先将症状归类到医学词典中的调节活动系统器官分类(soc)。然后,我们应用零截断泊松回归和逻辑回归来确定不同个体群体在soc上的报告差异。之后,我们进一步研究了4个选定的soc的详细症状。总的来说,26个社会责任类别中的19个和4个选定社会责任类别下434种症状中的17种在报告中显示出基于性别和/或年龄的显著差异。除了检测先前报道的性别、年龄组和症状之间的关联外,我们的方法还可以检测新的关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Analysis of Individual Differences in Vaccine Pharmacovigilance Using VAERS Data and MedDRA System Organ Classes: A Use Case Study With Trivalent Influenza Vaccine.

Analysis of Individual Differences in Vaccine Pharmacovigilance Using VAERS Data and MedDRA System Organ Classes: A Use Case Study With Trivalent Influenza Vaccine.

Analysis of Individual Differences in Vaccine Pharmacovigilance Using VAERS Data and MedDRA System Organ Classes: A Use Case Study With Trivalent Influenza Vaccine.

Analysis of Individual Differences in Vaccine Pharmacovigilance Using VAERS Data and MedDRA System Organ Classes: A Use Case Study With Trivalent Influenza Vaccine.

Personalized and precision vaccination requires consideration of an individual's sex and age. This article proposed systematic methods to study individual differences in adverse reactions following vaccination and chose trivalent influenza vaccine as a use case. Data were extracted from the Vaccine Adverse Event Reporting System from years 1990 to 2014. We first grouped symptoms into the Medical Dictionary for Regulatory Activities System Organ Classes (SOCs). We then applied zero-truncated Poisson regression and logistic regression to identify reporting differences among different individual groups over the SOCs. After that, we further studied detailed symptoms of 4 selected SOCs. In all, 19 of the 26 SOCs and 17 of the 434 symptoms under the 4 selected SOCs show significant reporting differences based on sex and/or age. In addition to detecting previously reported associations among sex, age group, and symptoms, our approach also enabled the detection of new associations.

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