| アブストラクト | PURPOSE: Three licensed human papillomavirus (HPV) vaccines (Cervarix, Gardasil, and Gardasil 9) have been effectively used to prevent infection with oncogenic HPV types; however, many adverse events (AEs) have also been reported following their vaccinations. We assessed AE profiles after receiving the HPV vaccines based on the reported data from Vaccine Adverse Event Reporting System (VAERS). METHODS: The AE data associated with Cervarix, Gardasil, and Gardasil 9 were retrieved from VAERS database respectively. The combinatorial biomedical statistical methods were used to identify the statistically significant AEs. The Gamma-Poisson Shrinker (GPS) model with gender/age stratification was applied to ascertain the serious adverse events (SAEs) related to the three licensed HPV vaccines. The AE profiles were classified and represented by the Ontology of Adverse Events (OAE) for further analysis. RESULTS: As of July 31, 2020, VAERS recorded 3,112, 31,606, and 6,872 AE case reports for Cervarix, Gardasil, and Gardasil 9, respectively. Our Frequentist statistical methods identified 135 Cervarix-enriched AEs, 55 Gardasil-enriched AEs, and 17 Gardasil 9-enriched AEs. Based on the OAE hierarchical classification, these AEs were clustered in the AEs related to behavioral and neurological conditions, immune system, nervous system, and reproductive system. Combined with GPS modeling, 46 unique statistically significant SAEs were founded to be associated with at least one of the three vaccines. CONCLUSIONS: Our study led to the better understanding of the AEs associated with the licensed HPV vaccines. The hypotheses on the cause and effect relationships between the HPV vaccination and specific AEs deserve further epidemiological investigations as well as clinical trial studies. |
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| 組織名 | Chongqing Engineering Research Center of Medical Electronics and Information;Technology, School of Bioinformatics, Chongqing University of Posts and;Telecommunications, Chongqing, China.;Unit of Laboratory Animal Medicine, Development of Microbiology and Immunology,;Center of Computational Medicine and Bioinformatics, University of Michigan;Medical School, Ann Arbor, Michigan, United States. |
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