Du Jingcheng, Cai Yi, Chen Yong, He Yongqun, Tao Cui
School of Biomedical Informatics, The University of Texas, Houston, TX, USA.
Pieces Technology, Dallas, TX, USA.
Biomed Inform Insights. 2017 Apr 11;9:1178222617700627. doi: 10.1177/1178222617700627. eCollection 2017.
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.
个性化和精准接种疫苗需要考虑个体的性别和年龄。本文提出了系统的方法来研究接种疫苗后不良反应的个体差异,并选择三价流感疫苗作为一个应用案例。数据取自1990年至2014年的疫苗不良事件报告系统。我们首先将症状分组到用于监管活动的医学词典系统器官分类(SOCs)中。然后,我们应用零截断泊松回归和逻辑回归来识别不同个体组在SOCs上的报告差异。之后,我们进一步研究了4个选定SOCs的详细症状。总体而言,26个SOCs中的19个以及4个选定SOCs下434个症状中的17个显示出基于性别和/或年龄的显著报告差异。除了检测先前报告的性别、年龄组和症状之间的关联外,我们的方法还能够检测新的关联。