ArticlePharmaceutics2020
Subset Analysis for Screening Drug-Drug Interaction Signal Using Pharmacovigilance Database.
Article in Pharmaceutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 15 citations in OpenAlex.
- Pharmacovigilance analysis of myopathy associated with azoles and nonstatins interactions based on US FAERS database.Scientific reports · 2025Article
- A Science-Based Methodology Framework for the Assessment of Combination Safety Risks in Clinical Trials.Pharmaceutical medicine · 2023Article
- Verification of the "Upward Variation in the Reporting Odds Ratio Scores" to Detect the Signals of Drug-Drug Interactions.Pharmaceutics · 2021Article
- Evaluation of the Expression Profile of Irinotecan-Induced Diarrhea in Patients with Colorectal Cancer.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Improved Detection Criteria for Detecting Drug-Drug Interaction Signals Using the Proportional Reporting Ratio.Pharmaceuticals (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Many patients require multi-drug combinations, and adverse event profiles reflect not only the effects of individual drugs but also drug-drug interactions. Although there are several algorithms for detecting drug-drug interaction signals, a simple analysis model is required for early detection of adverse events. Recently, there have been reports of detecting signals of drug-drug interactions using subset analysis, but appropriate detection criterion may not have been used. In this study, we presented and verified an appropriate criterion. The data source used was the Japanese Adverse Drug Event Report (JADER) database; "hypothetical" true data were generated through a combination of signals detected by three detection algorithms. The accuracy of the signal detection of the analytic model under investigation was verified using indicators used in machine learning. The newly proposed subset analysis confirmed that the signal detection was improved, compared with signal detection in the previous subset analysis, on the basis of the indicators of
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.