A signal detection method for temporal variation of adverse effect with vaccine adverse event reporting system data

BMC Medical Informatics and Decision Making

Research

Jing Huang¹  Sean Hennessy¹  Susan S. Ellenberg¹  Yong Chen¹  Yi Cai²  Jingcheng Du³  Cui Tao³ 

[1] Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;Pieces Technology, 8435 N Stemmons Fwy #1150, Dallas, TX, USA;School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA;

关键词: Heterogeneity testing;    Signal detection;    Vaccine Adverse Event Reporting System (VAERS);   

DOI  :  10.1186/s12911-017-0472-y

来源: Springer

【 摘 要 】

BackgroundTo identify safety signals by manual review of individual report in large surveillance databases is time consuming; such an approach is very unlikely to reveal complex relationships between medications and adverse events. Since the late 1990s, efforts have been made to develop data mining tools to systematically and automatically search for safety signals in surveillance databases. Influenza vaccines present special challenges to safety surveillance because the vaccine changes every year in response to the influenza strains predicted to be prevalent that year. Therefore, it may be expected that reporting rates of adverse events following flu vaccines (number of reports for a specific vaccine-event combination/number of reports for all vaccine-event combinations) may vary substantially across reporting years. Current surveillance methods seldom consider these variations in signal detection, and reports from different years are typically collapsed together to conduct safety analyses. However, merging reports from different years ignores the potential heterogeneity of reporting rates across years and may miss important safety signals.MethodReports of adverse events between years 1990 to 2013 were extracted from the Vaccine Adverse Event Reporting System (VAERS) database and formatted into a three-dimensional data array with types of vaccine, groups of adverse events and reporting time as the three dimensions. We propose a random effects model to test the heterogeneity of reporting rates for a given vaccine-event combination across reporting years. The proposed method provides a rigorous statistical procedure to detect differences of reporting rates among years. We also introduce a new visualization tool to summarize the result of the proposed method when applied to multiple vaccine-adverse event combinations.ResultWe applied the proposed method to detect safety signals of FLU3, an influenza vaccine containing three flu strains, in the VAERS database. We showed that it had high statistical power to detect the variation in reporting rates across years. The identified vaccine-event combinations with significant different reporting rates over years suggested potential safety issues due to changes in vaccines which require further investigation.ConclusionWe developed a statistical model to detect safety signals arising from heterogeneity of reporting rates of a given vaccine-event combinations across reporting years. This method detects variation in reporting rates over years with high power. The temporal trend of reporting rate across years may reveal the impact of vaccine update on occurrence of adverse events and provide evidence for further investigations.

【 授权许可】

CC BY   
© The Author(s). 2017

【 图 表 】

12864_2017_4133_Article_IEq30.gif

12864_2017_3487_Article_IEq51.gif

12864_2017_3898_Article_IEq6.gif

12888_2017_1365_Article_IEq5.gif

12888_2017_1284_Article_IEq1.gif

12888_2017_1365_Article_IEq3.gif

12864_2017_3487_Article_IEq45.gif

12864_2017_3990_Article_IEq15.gif

12864_2017_3781_Article_IEq5.gif

12864_2017_3781_Article_IEq3.gif

12864_2017_3781_Article_IEq2.gif

12864_2017_3990_Article_IEq12.gif

12864_2016_3425_Article_IEq8.gif

12864_2015_2129_Article_IEq20.gif

12864_2017_4020_Article_IEq5.gif

12864_2016_3425_Article_IEq6.gif

12864_2017_4020_Article_IEq3.gif

12711_2017_331_Article_IEq22.gif

12864_2015_2129_Article_IEq18.gif

12906_2016_1517_Article_IEq4.gif

12864_2017_4071_Article_IEq4.gif

12864_2016_2580_Article_IEq1.gif

12864_2017_4132_Article_IEq22.gif

12864_2017_3683_Article_IEq1.gif

12864_2017_4132_Article_IEq20.gif

12864_2017_4132_Article_IEq18.gif

12864_2017_3487_Article_IEq28.gif

12864_2017_4004_Article_IEq23.gif

12864_2017_4030_Article_IEq35.gif

12864_2017_3487_Article_IEq25.gif

12864_2017_4132_Article_IEq14.gif

12864_2017_4132_Article_IEq11.gif

12880_2016_176_Article_IEq10.gif

12864_2017_3503_Article_IEq1.gif

12888_2016_877_Article_IEq6.gif

12888_2016_877_Article_IEq5.gif

12864_2015_2167_Article_IEq1.gif

12888_2016_877_Article_IEq4.gif

12906_2017_1593_Article_IEq25.gif

12888_2016_877_Article_IEq1.gif

12906_2017_1593_Article_IEq20.gif

12864_2017_4179_Article_IEq13.gif

12864_2017_3790_Article_IEq2.gif

12864_2016_2793_Article_IEq4.gif

12887_2016_742_Article_IEq17.gif

12864_2016_3440_Article_IEq45.gif

12864_2017_4186_Article_IEq12.gif