Bacillus Calmette–Guérin (BCG) vaccine safety surveillance in the Korea Adverse Event Reporting System using the tree-based scan statistic and conventional disproportionality-based algorithms. Issue 21 (6th May 2020)

• Record Type: Journal Article
• Authors: Kim, Ju Hwan; Lee, Hyesung; Shin, Ju-Young
• Is Part Of: Vaccine. Volume 38:Issue 21(2020)
• Page Start: 3702
• Page End: 3710
• Publication Date: 2020-05-06
• Subjects: BCG vaccine -- Vaccine safety -- Tree-based scan statistic -- Data mining -- Signal detection; BCG bacillus Calmette–Guérin -- BCG-ID BCG vaccine for intradermal injection -- BCG-PC BCG vaccine for percutaneous injection -- BCPNN Bayesian confidence propagation neural network -- KAERS Korea Adverse Event Reporting System -- KIDS-KD Korea Institute of Drug Safety and Risk Management KAERS Database -- MFDS Ministry of Food and Drug Safety -- MLCCS Multi-Level Clinical Classifications Software -- TSS tree-based scan statistic -- WHO-ART World Health Organization Adverse Reactions Terminology; Vaccines -- Periodicals; 615.372
• DOI: 10.1016/j.vaccine.2020.04.007
• Languages: English
• ISSNs: 0264-410X

Abstract

Abstract: Background: Substantial variations in the safety profiles of different formulations of the bacillus Calmette–Guérin (BCG) vaccine exist. Therefore, we aimed to detect safety signals of BCG vaccine for intradermal injection (BCG-ID) and percutaneous injection (BCG-PC) in the Korea Adverse Event Reporting System (KAERS). Methods: We conducted a vaccine safety surveillance study from the adverse events (AEs) reported following BCG vaccine in the Korea Institute of Drug Safety and Risk Management KAERS Database (KIDS-KD) between 2005 and 2017. We used the tree-based scan statistic (TSS) and four disproportionality-based algorithms for signal detection: empirical Bayesian geometric mean; proportional reporting ratio; reporting odds ratio; and information component. The detected signals from each algorithm was compared with the known AEs of BCG vaccine (reference standard) to present positive predictive value (PPV) and area under the receiver operating curve (AUC). Results: From the total of 52, 191 vaccine-related AE pairs, 963 AE pairs were reported following the BCG vaccine, in which BCG-ID and –PC accounted for 71.1% and 28.9%, respectively. Overall, 97.2% of AE reports were non-serious; lymphadenopathy (583/963; 50.3%) and injection site discharge (193/963; 20.0%) were the most commonly reported AEs detected by all algorithms. Tuberculous osteitis was reported solely from BCG-PC (15/279; 5.4%), while most of the AEs from BCG-ID were related to injection site complications. The TSS demonstrated the best balance of the performance measures, with PPV and AUC of 66.7% and 63.1%, respectively. Conclusions: TSS was successfully applied in the KAERS to detect safety signals of BCG vaccine. In addition, difference in the safety profiles of BCG-ID and BCG-PC warrants further investigation to confirm our findings. Although TSS performed the best in our study, caution should be taken when interpreting the results owing to the lack of a robust "gold standard" and the relatively small number of reports for data mining.