Article ; Online: Impact of the vaccination against SARS-CoV-2 campaign on disproportionality indicator from the WHO pharmacovigilance database: A competition bias study from case/non-case analysis.
2024
Abstract: Introduction: The coronavirus disease 2019 (COVID-19) vaccination campaign has resulted in numerous pharmacovigilance's safety reports which were recorded in the World Health Organization (WHO) pharmacovigilance database (VigiBase) and represent in July ...
| Abstract | Introduction: The coronavirus disease 2019 (COVID-19) vaccination campaign has resulted in numerous pharmacovigilance's safety reports which were recorded in the World Health Organization (WHO) pharmacovigilance database (VigiBase) and represent in July 2022 more than 10% of cases recorded. The information component (IC) is a statistical disproportionality measure based on the observed and expected numbers of case reports. A positive value of the lower endpoint of a 95% credibility interval for the information component (IC Methods: We arbitrarily selected 21 adverse drug reactions using Medical Dictionary for Regulatory Activities (MedDRA) preferred terms (PTs), divided in two types: PTs known to be related to COVID-19 vaccines ("expected") and others (type "unexpected"). Data were extracted from VigiLyze. We created two groups: V+ (the full database, including COVID-19 vaccines reports) and V- (the same extraction without COVID-19 vaccine reports). IC Results: The number of positive potential signals was significantly different in the groups V+ and V- for IC Discussion: This study is one of the first to evaluate the effect of COVID-19 vaccines reporting on Automated Signal Detection of Pharmacovigilance. In this study, we observed that a wave of pharmacovigilance reporting can affect disproportionality estimators such as IC Conclusion: We show that a health crisis involving a change in drug use can affect adverse drug reactions reporting and pharmacovigilance databases, leading to competition bias and a change in the disproportionality analyses. For health professionals who use quantitative disproportionality analysis, it is important not only to use the crude values of indicators but also the kind of PTs and the evolution of the signal over time (take into account major events such as crises). |
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| Language | English |
| Publishing date | 2024-03-28 |
| Publishing country | France |
| Document type | Journal Article |
| ZDB-ID | 603474-3 |
| ISSN | 1958-5578 ; 0040-5957 |
| ISSN (online) | 1958-5578 |
| ISSN | 0040-5957 |
| DOI | 10.1016/j.therap.2024.03.002 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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