Pharmacokinetic Interactions of Clinical Interest Between Direct Oral Anticoagulants and Antiepileptic Drugs

Question What is the risk of major bleeding among patients with nonvalvular atrial fibrillation treated with non–vitamin K oral anticoagulants (NOACs) in combination with medications that share metabolic pathways? Findings Among 91 330 NOAC users in Taiwan, the risk of major bleeding was significantly increased with concurrent use of amiodarone, fluconazole, rifampin, or phenytoin compared with NOAC use alone. Meaning Physicians prescribing NOAC medications should consider the potential risks associated with concomitant use of other drugs. Importance Non–vitamin K oral anticoagulants (NOACs) are commonly prescribed with other medications that share metabolic pathways that may increase major bleeding risk. Objective To assess the association between use of NOACs with and without concurrent medications and risk of major bleeding in patients with nonvalvular atrial fibrillation. Design, Setting, and Participants Retrospective cohort study using data from the Taiwan National Health Insurance database and including 91 330 patients with nonvalvular atrial fibrillation who received at least 1 NOAC prescription of dabigatran, rivaroxaban, or apixaban from January 1, 2012, through December 31, 2016, with final follow-up on December 31, 2016. Exposures NOAC with or without concurrent use of atorvastatin; digoxin; verapamil; diltiazem; amiodarone; fluconazole; ketoconazole, itraconazole, voriconazole, or posaconazole; cyclosporine; erythromycin or clarithromycin; dronedarone; rifampin; or phenytoin. Main Outcomes and Measures Major bleeding, defined as hospitalization or emergency department visit with a primary diagnosis of intracranial hemorrhage or gastrointestinal, urogenital, or other bleeding. Adjusted incidence rate differences between person-quarters (exposure time for each person during each quarter of the calendar year) of NOAC with or without concurrent medications were estimated using Poisson regression and inverse probability of treatment weighting using the propensity score. Results Among 91 330 patients with nonvalvular atrial fibrillation (mean age, 74.7 years [SD, 10.8]; men, 55.8%; NOAC exposure: dabigatran, 45 347 patients; rivaroxaban, 54 006 patients; and apixaban, 12 886 patients), 4770 major bleeding events occurred during 447 037 person-quarters with NOAC prescriptions. The most common medications co-prescribed with NOACs over all person-quarters were atorvastatin (27.6%), diltiazem (22.7%), digoxin (22.5%), and amiodarone (21.1%). Concurrent use of amiodarone, fluconazole, rifampin, and phenytoin with NOACs had a significant increase in adjusted incidence rates per 1000 person-years of major bleeding than NOACs alone: 38.09 for NOAC use alone vs 52.04 for amiodarone (difference, 13.94 [99% CI, 9.76-18.13]); 102.77 for NOAC use alone vs 241.92 for fluconazole (difference, 138.46 [99% CI, 80.96-195.97]); 65.66 for NOAC use alone vs 103.14 for rifampin (difference, 36.90 [99% CI, 1.59-72.22); and 56.07 for NOAC use alone vs 108.52 for phenytoin (difference, 52.31 [99% CI, 32.18-72.44]; P  < .01 for all comparisons). Compared with NOAC use alone, the adjusted incidence rate for major bleeding was significantly lower for concurrent use of atorvastatin, digoxin, and erythromycin or clarithromycin and was not significantly different for concurrent use of verapamil; diltiazem; cyclosporine; ketoconazole, itraconazole, voriconazole, or posaconazole; and dronedarone. Conclusions and Relevance Among patients taking NOACs for nonvalvular atrial fibrillation, concurrent use of amiodarone, fluconazole, rifampin, and phenytoin compared with the use of NOACs alone, was associated with increased risk of major bleeding. Physicians prescribing NOAC medications should consider the potential risks associated with concomitant use of other drugs. This cohort study uses data from the Taiwan National Health Insurance database to assess the association between use of non–vitamin K oral anticoagulants with vs without concurrent medications and risk of major bleeding in patients with nonvalvular atrial fibrillation.

Much of the information on the Cytochrome P450 enzymes (CYPs) is spread across literature and the internet. Aggregating knowledge about CYPs into one database makes the search more efficient. Text mining on 57 CYPs and drugs led to a mass of papers, which were screened manually for facts about metabolism, SNPs and their effects on drug degradation. Information was put into a database, which enables the user not only to look up a particular CYP and all metabolized drugs, but also to check tolerability of drug-cocktails and to find alternative combinations, to use metabolic pathways more efficiently. The SuperCYP database contains 1170 drugs with more than 3800 interactions including references. Approximately 2000 SNPs and mutations are listed and ordered according to their effect on expression and/or activity. SuperCYP (http://bioinformatics.charite.de/supercyp) is a comprehensive resource focused on CYPs and drug metabolism. Homology-modeled structures of the CYPs can be downloaded in PDB format and related drugs are available as MOL-files. Within the resource, CYPs can be aligned with each other, drug-cocktails can be ‘mixed’, SNPs, protein point mutations, and their effects can be viewed and corresponding PubMed IDs are given. SuperCYP is meant to be a platform and a starting point for scientists and health professionals for furthering their research.

Pregabalin is a potent ligand for the alpha-2-delta subunit of voltage-gated calcium channels in the central nervous system that exhibits potent anticonvulsant, analgesic, and anxiolytic activity in a range of animal models. In addition, pregabalin has been shown to be a highly effective adjunctive therapy for partial seizures in clinical trials. Potent binding to the alpha-2-delta site reduces depolarization-induced calcium influx with a consequential modulation in excitatory neurotransmitter release. Pregabalin has no demonstrated effects on GABAergic mechanisms. Pregabalin demonstrates highly predictable and linear pharmacokinetics, a profile that makes it easy to use in clinical practice. Absorption is extensive, rapid, and proportional to dose. Time to maximal plasma concentration is approximately 1 h and steady state is achieved within 24-48 h. These characteristics reflect the observed onset of efficacy as early as day two in clinical trials. High bioavailability, a mean elimination half life (t(1/2)) of 6.3 h, and dose-proportional maximal plasma concentrations and total exposures predict a dose-response relationship in clinical practice and allow an effective starting dose of 150 mg/day in clinical practice without need for titration. Administration with food has no clinically relevant effect on the amount of pregabalin absorbed, providing for a dosing regimen uncomplicated by meals. Pregabalin does not bind to plasma proteins and is excreted virtually unchanged (<2% metabolism) by the kidneys. It is not subject to hepatic metabolism and does not induce or inhibit liver enzymes such as the cytochrome P450 system. Therefore, pregabalin is unlikely to cause, or be subject to, pharmacokinetic drug-drug interactions--an expectation that has been confirmed in clinical pharmacokinetic studies. However, dose adjustment may be necessary in patients with renal insufficiency. Thus, the pharmacological and pharmacokinetic profiles of pregabalin provide a predictable basis for its use in clinical practice.