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Detection of Clinically Significant Drug-Drug Interactions in Fatal Torsades de Pointes: Disproportionality Analysis of the Food and Drug Administration Adverse Event Reporting System

Huanhuan Ji, Meiling Gong, Li Gong, Ni Zhang, Ruiou Zhou, Dongmei Deng, Ya Yang, Lin Song, Yuntao Jia

2025Journal of Medical Internet Research7 citationsDOIOpen Access PDF

Abstract

BACKGROUND: Torsades 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. OBJECTIVE: This 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. METHODS: We 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. RESULTS: values were 0.987 and 0.985, respectively. We detected 2158 combinations using the 4 frequency statistical models, of which 241 combinations were indexed by Drugs.com or Lexicomp and 105 were indexed by both. The most commonly interacting drugs were amiodarone, citalopram, quetiapine, ondansetron, ciprofloxacin, methadone, escitalopram, sotalol, and voriconazole. The most common combinations were citalopram and quetiapine, amiodarone and ciprofloxacin, amiodarone and escitalopram, amiodarone and fluoxetine, ciprofloxacin and sotalol, and amiodarone and citalopram. Although 38 DDIs were indexed by Drugs.com and Lexicomp, they were not detected by any of the 4 models. CONCLUSIONS: Clinical 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.

Topics & Concepts

Adverse Event Reporting SystemMedicineTorsades de pointesAdverse effectDrugPharmacovigilanceStatisticPharmacologyFood and drug administrationInternal medicineQT intervalStatisticsMathematicsPharmacovigilance and Adverse Drug ReactionsCardiac electrophysiology and arrhythmiasAtrial Fibrillation Management and Outcomes
Detection of Clinically Significant Drug-Drug Interactions in Fatal Torsades de Pointes: Disproportionality Analysis of the Food and Drug Administration Adverse Event Reporting System | Litcius