Detection of Clinically Significant Drug-Drug Interactions in Fatal Torasdes de Pointes: A Multiple Real-world Data, Retrospective, Pharmacovigilance Study (Preprint)

BACKGROUND Torsades de Pointes (TdP) is a rare yet potentially fatal cardiac arrhythmia, and that is often drug-induced. Drug-drug interactions (DDIs) is a major risk factor for TdP development, while the specific drug combinations that increase this risk have not been extensively studied. OBJECTIVE The primary objective of this study was to identify clinically significant DDIs to minimize the risk of TdP, without unnecessary treatment discontinuations or alterations. METHODS Four frequency statistical models: the Ω shrinkage measure, combination risk ratio, chi-square statistics, and additive models were employed to detect DDIs signals using the FDA Adverse Event Reporting System (FAERS) database. 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 DDIs signals were identified and evaluated using the Lexicomp® and Drugs.com® databases, supplemented with real-world data from literature evidence. RESULTS Of the 4,313 TdP cases, 721 drugs and 4,230 drug combinations reported in at least 3 cases. The Ω shrinkage measure model demonstrated the most conservative in signal detection, whereas the chi-square statistic model exhibited the closest similarity in signal detection tendency to the Ω shrinkage measure model. 2,158 combinations were detected by the four 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, voriconazole, etc. The most common combinations were citalopram & quetiapine, amiodarone & ciprofloxacin, amiodarone & escitalopram, amiodarone & fluoxetine, ciprofloxacin & sotalol, amiodarone & citalopram. While 38 DDIs indexed by Drugs.com® and Lexicomp®, but not detected by any of the four models. CONCLUSIONS Clinical evidence on DDIs is limited, and not all combinations of 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, delineateing both clinically significant DDIs and negative DDIs, providing valuable insights into the safety profiles of various drugs and informing the optimization of clinical practice.