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KMID : 1011320200120010044
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Journal of Pharmacoepidemiology and Risk Management
2020 Volume.12 No. 1 p.44 ~ p.52
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Comparison of Signal Detection Methodologies Using the Korean Spontaneous Adverse Event Reports after Pneumococcal Vaccination
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You Seung-Hun
Kim Myo-Song
Lee Min-Taek
Kang Ye-Jin
Jung Sun-Young
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Abstract
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Objective: To compare vaccine signal detection methodologies using the Korea adverse events reporting system
(KAERS) database for vaccines.
Methods: Among the individual case safety reports (ICSRs) reported to KAERS database between 2005 and 2017, the vaccines of interest were pneumococcal conjugate vaccine (WHO-ATC, J07AL01) and pneumococcal polysaccharide vaccine (J07AL02). To derive safety signals, we applied disproportionality analysis and tree-based scan statistic (TBSS). The disproportionality analysis calculated three indices (proportional reporting ratio, reporting odds ratio, and information component) based on the reported preferred terms (WHO-ART, PT). TBSS calculated the log-likelihood ratio and was validated by Monte Carlo simulation based on the reported all hierarchical level term. Then we examined whether the safety signals were listed in the drug label.
Results: Among total of 29,270 vaccine ICSRs in KAERS database, the number of ICSRs of pneumococcal vaccines was 5,738. The disproportionality analysis yielded 26 PTs as safety signals and detected unlabeled 6 PTs including ‘medicine ineffectiveness’. The TBSS yielded 25 as hierarchy level statistical signals and detected for unlabeled 5 hierarchy level including ‘pneumonia’ and ‘medicine ineffectiveness’.
Conclusion: The number of adverse events (AEs) reporting on pneumococcal vaccines increased following introduction to the Korean national immunization program. The derived safety signals such as ‘medicine ineffective’ and ‘pneumonia’ may be due to comorbid conditions of vaccine recipients high-risk of infection, which warrants further study. Along with disproportionality analysis, TBSS could be used as a supplementary tool for signal detection with analyzing all-level hierarchical structural term AEs.
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KEYWORD
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Vaccines, Signal detection analyses, Data mining, Adverse drug eve
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