ArticlePharmaceutics2021
Verification of the "Upward Variation in the Reporting Odds Ratio Scores" to Detect the Signals of Drug-Drug Interactions.
Article in Pharmaceutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Incretin-Based Drugs for Obesity: Common and Drug-Specific Reporting Patterns of Adverse Drug Reactions-A Comparative Disproportionality Analysis Using EudraVigilance Reports Integrating SmPC Data.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Inner ear signs and symptoms induced by antidepressants: a disproportionality analysis based on the FAERS database.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Safety assessment for ibuprofen using disproportionality analysis: a decade of data from the Romanian national pharmacovigilance system.Frontiers in pharmacology · 2026Article
- Pharmacovigilance analysis of central nervous system adverse events associated with sevoflurane and drug interactions: a disproportionality study based on the FDA adverse event reporting system (FAERS) database.Frontiers in pharmacology · 2026Article
- Drug-related retinal detachment pharmacovigilance signals in the real world: evidence from the FDA Adverse Event Reporting System.Eye (London, England) · 2025Article
- Is it appropriate to conduct a disproportionality analysis using a spontaneous reporting database to investigate whether drug-related adverse events are dose-dependent?Frontiers in pharmacology · 2025Article
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- Examining the safety of mirabegron: an analysis of real-world pharmacovigilance data from the US FDA adverse event reporting system (FAERS) database.Frontiers in pharmacology · 2024Article
- Drug Repurposing Using FDA Adverse Event Reporting System (FAERS) Database.Current drug targets · 2024Review
- Comment on: "A Disproportionality Analysis of Drug-Drug Interactions of Tizanidine and CYP1A2 Inhibitors from the FDA Adverse Event Reporting System (FAERS)".Drug safety · 2022Article
- Article
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Authors and funding
6 authors.
Funding
Abstract
The reporting odds ratio (ROR) is easy to calculate, and there have been several examples of its use because of its potential to speed up the detection of drug-drug interaction signals by using the "upward variation of ROR score". However, since the validity of the detection method is unknown, this study followed previous studies to investigate the detection trend. The statistics models (the Ω shrinkage measure and the "upward variation of ROR score") were compared using the verification dataset created from the Japanese Adverse Drug Event Report database (JADER). The drugs registered as "suspect drugs" in the verification dataset were considered as the drugs to be investigated, and the target adverse event in this study was Stevens-Johnson syndrome (SJS), as in previous studies. Of 3924 pairs that reported SJS, the number of positive signals detected by the Ω shrinkage measure and the "upward variation of ROR score" (Model 1, the Susuta Model, and Model 2) was 712, 2112, 1758, and 637, respectively. Furthermore, 1239 positive signals were detected when the Haldane-Anscombe 1/2 correction was applied to Model 2, the statistical model that showed the most conservative detection trend. This result indicated the instability of the positive signal detected in Model 2. The ROR scores based on the frequency-based statistics are easily inflated; thus, the use of the "upward variation of ROR scores" to search for drug-drug interaction signals increases the likelihood of false-positive signal detection. Consequently, the active use of the "upward variation of ROR scores" is not recommended, despite the existence of the Ω shrinkage measure, which shows a conservative detection trend.
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