ArticleLife (Basel, Switzerland)2020
Comparison of Data Mining Methods for the Signal Detection of Adverse Drug Events with a Hierarchical Structure in Postmarketing Surveillance.
Article in Life (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed, 61 citations in OpenAlex.
- Pharmacovigilance of carmustine: distinct neurotoxic and systemic safety signals identified in FAERS.BMC cancer · 2026Article
- Pharmacovigilance evaluation of somatrogon-associated adverse events in real-world databases.Endocrine connections · 2026Article
- Neoplasm Adverse Events Associated With Anti-Type 2 Biologics: An FAERS Database Pharmacovigilance Analysis Study.Cancer medicine · 2026Article
- Immune checkpoint inhibitor-related myotoxicity in lung cancer: a decade-long real-world pharmacovigilance analysis of the FAERS database.Frontiers in pharmacology · 2026Article
- Generative Transformers for Pharmacovigilance Signal Detection using Electronic Health Records.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
- Article
- Signal mining and safety profile analysis of lapatinib: a pharmacovigilance analysis of the FDA Adverse Event Reporting System (FAERS) database.Journal of pharmaceutical policy and practice · 2026Article
- Mapping the applications and methodological characteristics of the TreeScan method in pharmacovigilance and beyond: a scoping review of 44 studies.Frontiers in pharmacology · 2026Article
- National Pharmacovigilance Assessment of Oral Adverse Events Following COVID-19 Vaccination in Germany (2020-2023).International dental journal · 2025Article
- Adverse Event Signals Associated with Beta-Lactamase Inhibitors: Disproportionality Analysis of USFDA Adverse Event Reporting System.Journal of xenobiotics · 2025Article
- Immune checkpoint inhibitor-associated myocarditis and pericarditis: a pharmacovigilance study based on the FAERS database.BMC cancer · 2025Article
- Disproportionality analysis from World Health Organization data on migraine-specific medications and cerebrovascular diseases.European journal of clinical pharmacology · 2025Article
- Article
- Disproportionality analysis of satralizumab in FDA adverse event reporting system and Japanese adverse drug event report: a pharmacovigilance study.Frontiers in immunology · 2025Article
- A real-world disproportionality analysis of FDA adverse event reporting system (FAERS) events for lecanemab.Frontiers in pharmacology · 2025Article
- Pharmacovigilance study of famciclovir in the Food and Drug administration adverse event reporting system database.Scientific reports · 2024Article
- Adverse Event Profile of First-line Drugs for Treating Patent Ductus Arteriosus in Neonates: A Disproportionality Analysis Study of USFDA Adverse Event Reporting System.Paediatric drugs · 2024Article
- Stratified analysis of the association between anti-obesity medications and digestive adverse events: a real-world study based on the FDA adverse event reporting system database.BMC pharmacology & toxicology · 2024Article
- Toxicity profiles of immune checkpoint inhibitors in nervous system cancer: a comprehensive disproportionality analysis using FDA adverse event reporting system.Clinical and experimental medicine · 2024Article
- Adverse event reporting of the IGF-1R monoclonal antibody teprotumumab: a real-world study based on the US food and drug administration adverse event reporting system.Frontiers in pharmacology · 2024Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
There are several different proposed data mining methods for the postmarketing surveillance of drug safety. Adverse events are often classified into a hierarchical structure. Our objective was to compare the performance of several of these different data mining methods for adverse drug events data with a hierarchical structure. We generated datasets based on the World Health Organization's Adverse Reaction Terminology (WHO-ART) hierarchical structure. We evaluated different data mining methods for signal detection, including several frequentist methods such as reporting odds ratio (ROR), proportional reporting ratio (PRR), information component (IC), the likelihood ratio test-based method (LRT), and Bayesian methods such as gamma Poisson shrinker (GPS), Bayesian confidence propagating neural network (BCPNN), the new IC method, and the simplified Bayesian method (sB), as well as the tree-based scan statistic through an extensive simulation study. We also applied the methods to real data on two diabetes drugs, voglibose and acarbose, from the Korea Adverse event reporting system. Only the tree-based scan statistic method maintained the type I error rate at the desired level. Likelihood ratio test-based methods and Bayesian methods tended to be more conservative than other methods in the simulation study and detected fewer signals in the real data example. No method was superior to the others in terms of the statistical power and sensitivity of detecting true signals. It is recommended that those conducting drug‒adverse event surveillance use not just one method, but make a decision based on several methods.
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