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...
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| Veröffentlicht in: | Biomedical informatics insights 2017, Vol.2017 (9), p.1178222617700627-1178222617700627 |
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| container_issue | 9 |
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| container_title | Biomedical informatics insights |
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| creator | Du, Jingcheng Cai, Yi Chen, Yong He, Yongqun Tao, Cui |
| description | 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. |
| doi_str_mv | 10.1177/1178222617700627 |
| format | Article |
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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.</description><identifier>ISSN: 1178-2226</identifier><identifier>EISSN: 1178-2226</identifier><identifier>DOI: 10.1177/1178222617700627</identifier><identifier>PMID: 28469434</identifier><language>eng</language><publisher>London, England: SAGE Publishing</publisher><subject>Age ; Immunization ; Influenza ; Original Research ; Pharmacology ; Pharmacovigilance ; Poisson density functions ; Regression analysis ; Sex ; Social networks ; Statistical analysis ; Studies ; Vaccination ; Vaccines</subject><ispartof>Biomedical informatics insights, 2017, Vol.2017 (9), p.1178222617700627-1178222617700627</ispartof><rights>The Author(s) 2017</rights><rights>2017. This work is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2017 2017 SAGE Publications Ltd unless otherwise noted. Manuscript content on this site is licensed under Creative Commons Licenses</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c447t-9aa4c1ce3ea9545fa81f3314e0be7ce077d29ee0defdf73c09a96a376d0ce9f73</citedby><cites>FETCH-LOGICAL-c447t-9aa4c1ce3ea9545fa81f3314e0be7ce077d29ee0defdf73c09a96a376d0ce9f73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5391193/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5391193/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,4022,27922,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28469434$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Du, Jingcheng</creatorcontrib><creatorcontrib>Cai, Yi</creatorcontrib><creatorcontrib>Chen, Yong</creatorcontrib><creatorcontrib>He, Yongqun</creatorcontrib><creatorcontrib>Tao, Cui</creatorcontrib><title>Analysis of Individual Differences in Vaccine Pharmacovigilance Using VAERS Data and MedDRA System Organ Classes: A Use Case Study With Trivalent Influenza Vaccine</title><title>Biomedical informatics insights</title><addtitle>Biomed Inform Insights</addtitle><description>Personalized and precision vaccination requires consideration of an individual’s sex and age. 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| ispartof | Biomedical informatics insights, 2017, Vol.2017 (9), p.1178222617700627-1178222617700627 |
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| source | PubMed (Medline); EZB Electronic Journals Library; PubMed Central Open Access |
| subjects | Age Immunization Influenza Original Research Pharmacology Pharmacovigilance Poisson density functions Regression analysis Sex Social networks Statistical analysis Studies Vaccination Vaccines |
| title | Analysis of Individual Differences in Vaccine Pharmacovigilance Using VAERS Data and MedDRA System Organ Classes: A Use Case Study With Trivalent Influenza Vaccine |
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