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Risk of QT prolongation and torsade de pointes associated with exposure to hydroxyzine: re-evaluation of an established drug.

ABSTRACT: Several noncardiac drugs have been linked to cardiac safety concerns, highlighting the importance of post-marketing surveillance and continued evaluation of the benefit-risk of long-established drugs. Here, we examine the risk of QT prolongation and/or torsade de pointes (TdP) associated with the use of hydroxyzine, a first generation sedating antihistamine. We have used a combined methodological approach to re-evaluate the cardiac safety profile of hydroxyzine, including: (1) a full review of the sponsor pharmacovigilance safety database to examine real-world data on the risk of QT prolongation and/or TdP associated with hydroxyzine use and (2) nonclinical electrophysiological studies to examine concentration-dependent effects of hydroxyzine on a range of human cardiac ion channels. Based on a review of pharmacovigilance data between 14th December 1955 and 1st August 2016, we identified 59 reports of QT prolongation and/or TdP potentially linked to hydroxyzine use. Aside from intentional overdose, all cases involved underlying medical conditions or concomitant medications that constituted at least 1 additional risk factor for such events. The combination of cardiovascular disorders plus concomitant treatment of drugs known to induce arrhythmia was identified as the greatest combined risk factor. Parallel patch-clamp studies demonstrated hydroxyzine concentration-dependent inhibition of several human cardiac ion channels, including the ether-a-go-go-related gene (hERG) potassium ion channels. Results from this analysis support the listing of hydroxyzine as a drug with "conditional risk of TdP" and are in line with recommendations to limit hydroxyzine use in patients with known underlying risk factors for QT prolongation and/or TdP.

SUBMITTER: Schlit AF

PROVIDER: S-EPMC5415947 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundDrug-induced QT interval prolongation, a risk factor for life-threatening ventricular arrhythmias, is a potential side effect of many marketed and withdrawn medications. The contribution of common genetic variants previously associated with baseline QT interval to drug-induced QT prolongation and arrhythmias is not known.MethodsWe tested the hypothesis that a weighted combination of common genetic variants contributing to QT interval at baseline, identified through genome-wide association studies, can predict individual response to multiple QT-prolonging drugs. Genetic analysis of 22 subjects was performed in a secondary analysis of a randomized, double-blind, placebo-controlled, crossover trial of 3 QT-prolonging drugs with 15 time-matched QT and plasma drug concentration measurements. Subjects received single doses of dofetilide, quinidine, ranolazine, and placebo. The outcome was the correlation between a genetic QT score comprising 61 common genetic variants and the slope of an individual subject's drug-induced increase in heart rate-corrected QT (QTc) versus drug concentration.ResultsThe genetic QT score was correlated with drug-induced QTc prolongation. Among white subjects, genetic QT score explained 30% of the variability in response to dofetilide (r=0.55; 95% confidence interval, 0.09-0.81; P=0.02), 23% in response to quinidine (r=0.48; 95% confidence interval, -0.03 to 0.79; P=0.06), and 27% in response to ranolazine (r=0.52; 95% confidence interval, 0.05-0.80; P=0.03). Furthermore, the genetic QT score was a significant predictor of drug-induced torsade de pointes in an independent sample of 216 cases compared with 771 controls (r2=12%, P=1×10-7).ConclusionsWe demonstrate that a genetic QT score comprising 61 common genetic variants explains a significant proportion of the variability in drug-induced QT prolongation and is a significant predictor of drug-induced torsade de pointes. These findings highlight an opportunity for recent genetic discoveries to improve individualized risk-benefit assessment for pharmacological therapies. Replication of these findings in larger samples is needed to more precisely estimate variance explained and to establish the individual variants that drive these effects.Clinical trial registrationURL: http://www.clinicaltrials.gov. Unique identifier: NCT01873950.

Project description:BACKGROUND:Blockage of some ion channels and in particular, the hERG (human Ether-a'-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrhythmia known as Torsade de Pointes (TdP). Therefore recognizing drugs with TdP risk is essential. Candidate drugs that are determined not to cause cardiac ion channel blockage are more likely to pass successfully through clinical phases II and III trials (and preclinical work) and not be withdrawn even later from the marketplace due to cardiotoxic effects. The objective of the present study is to develop an SAR (Structure-Activity Relationship) model that can be used as an early screen for torsadogenic (causing TdP arrhythmias) potential in drug candidates. The method is performed using descriptors comprised of atomic NMR chemical shifts (13C and 15N NMR) and corresponding interatomic distances which are combined into a 3D abstract space matrix. The method is called 3D-SDAR (3-dimensional spectral data-activity relationship) and can be interrogated to identify molecular features responsible for the activity, which can in turn yield simplified hERG toxicophores. A dataset of 55 hERG potassium channel inhibitors collected from Kramer et al. consisting of 32 drugs with TdP risk and 23 with no TdP risk was used for training the 3D-SDAR model. RESULTS:An artificial neural network (ANN) with multilayer perceptron was used to define collinearities among the independent 3D-SDAR features. A composite model from 200 random iterations with 25% of the molecules in each case yielded the following figures of merit: training, 99.2%; internal test sets, 66.7%; external (blind validation) test set, 68.4%. In the external test set, 70.3% of positive TdP drugs were correctly predicted. Moreover, toxicophores were generated from TdP drugs. CONCLUSION:A 3D-SDAR was successfully used to build a predictive model for drug-induced torsadogenic and non-torsadogenic drugs based on 55 compounds. The model was tested in 38 external drugs.

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Risk of QT prolongation and torsade de pointes associated with exposure to hydroxyzine: re-evaluation of an established drug.

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