ArticleJournal of medical Internet research2025
Detection of Clinically Significant Drug-Drug Interactions in Fatal Torsades de Pointes: Disproportionality Analysis of the Food and Drug Administration Adverse Event Reporting System.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Avoidance of cardiac toxicity during the application of immune checkpoint inhibitors: a safety systematic review combining network meta-analysis and pharmacovigilance study.Frontiers in immunology · 2026Pooled it
- Possible clinical drug interactions between ticagrelor and concomitant medications: for adverse drug event monitoring in real-world.Cardiovascular drugs and therapy · 2026Article
- Case Report: Amiodarone-triggered refractory ventricular fibrillation storm in septic cardiomyopathy with pre-existing QT prolongation: termination using lidocaine and anisodamine.Frontiers in medicine · 2026Article
- Drug combination choices of 5α-reductase inhibitors and α-blockers in patients with benign prostatic hyperplasia: a study based on the FAERS database.Frontiers in medicine · 2026Article
- Drug-drug interactions between sex hormones and analgesics linked to thromboembolic events: an FDA adverse event reporting system analysis.Frontiers in pharmacology · 2026Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTorsades de pointes (TdP) is a rare yet potentially fatal cardiac arrhythmia that is often drug-induced. Drug-drug interactions (DDIs) are a major risk factor for TdP development, but the specific drug combinations that increase this risk have not been extensively studied.
objectiveThis study aims to identify clinically significant, high-priority DDIs to provide a foundation to minimize the risk of TdP and effectively manage DDI risks in the future.
methodsWe used the following 4 frequency statistical models to detect DDI signals using the Food and Drug Administration Adverse Event Reporting System (FAERS) database: Ω shrinkage measure, combination risk ratio, chi-square statistic, and additive model. The adverse event of interest was TdP, and the drugs targeted were all registered and classified as "suspect," "interacting," or "concomitant drugs" in FAERS. The DDI signals were identified and evaluated using the Lexicomp and Drugs.com databases, supplemented with real-world data from the literature.
resultsAs of September 2023, this study included 4313 TdP cases, with 721 drugs and 4230 drug combinations that were reported for at least 3 cases. The Ω shrinkage measure model demonstrated the most conservative signal detection, whereas the chi-square statistic model exhibited the closest similarity in signal detection tendency to the Ω shrinkage measure model. The κ value was 0.972 (95% CI 0.942-1.002), and the P
conclusionsClinical evidence on DDIs is limited, and not all combinations of heart rate-corrected QT interval (QTc)-prolonging drugs result in TdP, even when involving high-risk drugs or those with known risk of TdP. This study provides a comprehensive real-world overview of drug-induced TdP, delimiting both clinically significant DDIs and negative DDIs, providing valuable insights into the safety profiles of various drugs, and informing the optimization of clinical practice.
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