ArticlePharmacoepidemiology and drug safety2017
vigiRank for statistical signal detection in pharmacovigilance: First results from prospective real-world use.
Article in Pharmacoepidemiology and drug safety, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 29 citations in OpenAlex.
- Design Principles for Interactive Dashboards in Drug Safety Surveillance: Design Science Research.JMIR medical informatics · 2026Article
- Orchestrating generative AI in pharmacovigilance: predicting and preempting the unpredictable.Therapeutic advances in drug safety · 2025Review
- A Comparison of Signals of Designated Medical Events and Non-designated Medical Events: Results from a Scoping Review.Drug safety · 2024Article
- Opportunities and challenges in application of artificial intelligence in pharmacology.Pharmacological reports : PR · 2023Review
- 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
- Smartphone-based mobile applications for adverse drug reactions reporting: global status and country experience.BMC medical informatics and decision making · 2022Article
- Random control selection for conducting high-throughput adverse drug events screening using large-scale longitudinal health data.CPT: pharmacometrics & systems pharmacology · 2021Article
- Second-Generation Cephalosporins-Associated Drug-Induced Liver Disease: A Study in VigiBase with a Focus on the Elderly.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Risk Factor Considerations in Statistical Signal Detection: Using Subgroup Disproportionality to Uncover Risk Groups for Adverse Drug Reactions in VigiBase.Drug safety · 2020Article
- A Feasibility Study of Drug-Drug Interaction Signal Detection in Regular Pharmacovigilance.Drug safety · 2020Article
- The quality assessment of the Japanese Adverse Drug Event Report database using vigiGrade.International journal of clinical pharmacy · 2020Article
- Towards Automating Adverse Event Review: A Prediction Model for Case Report Utility.Drug safety · 2020Article
- New Insights in Computational Methods for Pharmacovigilance:International journal of environmental research and public health · 2019Article
- Paediatric safety signals identified in VigiBase: Methods and results from Uppsala Monitoring Centre.Pharmacoepidemiology and drug safety · 2019Article
- E-Synthesis: A Bayesian Framework for Causal Assessment in Pharmacosurveillance.Frontiers in pharmacology · 2019Article
- First Conference on Big Data for Pharmacovigilance.Drug safety · 2018Review
- Learning predictive models of drug side-effect relationships from distributed representations of literature-derived semantic predications.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- vigiRank for statistical signal detection in pharmacovigilance: First results from prospective real-world use.Pharmacoepidemiology and drug safety · 2017Article
- Artificial intelligence in pharmacovigilance: Practical utility.Indian journal of pharmacologyArticle
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposevigiRank is a data-driven predictive model for emerging safety signals. In addition to disproportionate reporting patterns, it also accounts for the completeness, recency, and geographic spread of individual case reporting, as well as the availability of case narratives. Previous retrospective analysis suggested that vigiRank performed better than disproportionality analysis alone. The purpose of the present analysis was to evaluate its prospective performance.
methodsThe evaluation of vigiRank was based on real-world signal detection in VigiBase. In May 2014, vigiRank scores were computed for pairs of new drugs and WHO Adverse Reaction Terminology critical terms with at most 30 reports from at least 2 countries. Initial manual assessments were performed in order of descending score, selecting a subset of drug-adverse drug reaction pairs for in-depth expert assessment. The primary performance metric was the proportion of initial assessments that were decided signals during in-depth assessment. As comparator, the historical performance for disproportionality- guided signal detection in VigiBase was computed from a corresponding cohort of drug-adverse drug reaction pairs assessed between 2009 and 2013. During this period, the requirement for initial manual assessment was a positive lower endpoint of the 95% credibility interval of the Information Component measure of disproportionality, observed for the first time.
results194 initial assessments suggested by vigiRank's ordering eventually resulted in 6 (3.1%) signals. Disproportionality analysis yielded 19 signals from 1592 initial assessments (1.2%; P < .05).
conclusionsCombining multiple strength-of-evidence aspects as in vigiRank significantly outperformed disproportionality analysis alone in real-world pharmacovigilance signal detection, for VigiBase.
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