ArticleDrug safety2020
Contribution of Causality Assessment for an Automated Detection of Safety Signals: An Example Using the French Pharmacovigilance Database.
Article in Drug safety, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cannabinoid-Related Acute Pancreatitis: An Update from International Literature and Individual Case Safety Reports.Drug safety · 2022Pooled it
- Charting and Sidestepping the Pitfalls of Disproportionality Analysis.Drug safety · 2026Review
- Natural language processing for automated triage and prioritization of individual case safety reports for case-by-case assessment.Frontiers in drug safety and regulation · 2023Article
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9 authors.
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Abstract
introductionQualitative approaches based on drug causality assessment estimate the causal link between a drug and the occurrence of an adverse event from individual case safety reports. Quantitative approaches based on disproportionality analyses were developed subsequently to allow automated statistical signal detection from pharmacovigilance databases. This study assessed the potential value of causality assessment for automated safety signal detection.
methodsAll drug-serious adverse event pairs with a positive rechallenge and a semiology suggestive of drug causality were identified in the French pharmacovigilance database (BNPV) from 2011 to 2017. The results were compared with those obtained from automated disproportionality analyses of the BNPV/World Health Organization (WHO) VigiBase
resultsOf the 155 pairs of interest, 115 (74.2%) were also identified by another source of information. Since the individual case reporting in the BNPV, 23 (14.8%) of the adverse events (AEs) have been added to the SmPC, seven of which were not identified by disproportionality. Finally, 40 pairs were not identified by any other source of information, 13 of which were considered as potential new safety signals after analysis of case reports by pharmacovigilance experts. The signals identified by causality assessment involved antineoplastic and immunomodulatory drugs especially, in comparison with signals identified by WHO-UMC or by disproportionality within the BNPV.
conclusionThe approach therefore appears useful as an additional tool for safety signal detection, especially for antineoplastic and immunomodulating agents.
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