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• W3199479985 abstract "Passive surveillance systems are susceptible to the under-reporting of adverse events (AE) and a lack of information pertaining to vaccinated populations. Conventional active surveillance focuses on predefined AEs. Advanced data mining tools could be used to identify unusual clusters of potential AEs after vaccination.To assess the feasibility of a novel tree-based statistical approach to the identification of AE clustering following the implementation of a varicella vaccination program among one-year-olds.This nationwide safety surveillance was based on data from the Taiwan National Health Insurance database and National Immunization Information System for the period 2004 through 2014. The study population was children aged 12-35 months who received the varicella vaccine.First-dose varicella vaccine.All incident ICD-9-CM diagnoses (emergency or inpatient departments) occurring 1-56 days after the varicella vaccination were classified within a hierarchical system of diagnosis categories using Multi-Level Clinical Classifications Software. A self-controlled tree-temporal data mining tool was then used to explore the incidence of AE clustering with a variety of potential risk intervals. The comparison interval consisted of days in the 56-day follow-up period that fell outside the risk interval.Among 1,194,189 varicella vaccinees with no other same-day vaccinations, nine diagnoses with clustering features were categorized into four safety signals: fever on days 1-6 (attributable risk [AR] 38.5 per 100,000, p < 0.001), gastritis and duodenitis on days 1-2 (AR 5.9 per 100,000, p < 0.001), acute upper respiratory infection on days 1-5 (AR 11.0 per 100,000, p = 0.006), and varicella infection on days 1-9 (AR 2.7 per 100,000, p < 0.001). These safety profiles and their corresponding risk intervals have been identified in previous safety surveillance studies.Unexpected clusters of AEs were not detected after the mass administration of childhood varicella vaccines in Taiwan. The tree-temporal statistical method is a feasible approach to the safety surveillance of vaccines in populations of young children." @default.
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• W3199479985 date "2021-10-01" @default.
• W3199479985 modified "2023-10-16" @default.
• W3199479985 title "Safety surveillance of varicella vaccine using tree-temporal scan analysis" @default.
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• W3199479985 doi "https://doi.org/10.1016/j.vaccine.2021.09.035" @default.
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