Dataset Information

CYP2C19 drug-drug and drug-gene interactions in ED patients.

ABSTRACT:

Background

CYP450 polymorphisms result in variable rates of drug metabolism. CYP drug-drug interactions can contribute to altered drug effectiveness and safety.

Study objectives

The primary objective was to determine the percentage of emergency department (ED) patients with cytochrome 2C19 (CYP2C19) drug-drug interactions. The secondary objective was to determine the prevalence of CYP2C19 polymorphisms in a US ED population.

Methods

We conducted a prospective observational study in an urban academic ED with 72,000 annual visits. Drug ingestion histories for the 48 hours preceding ED visit were obtained; each drug was coded as CYP2C19 substrate, inhibitor, inducer, or not CYP2C19 dependent. Ten percent of patients were randomized to undergo CYP2C19 genotyping using the Roche Amplichip.

Results

A total of 502 patients were included; 61% were female, 65% were white, and median age was 39 years (interquartile range, 22-53). One hundred thirty-one (26.1%) patients had taken at least 1 CYP2C19-dependent home drug. Eighteen (13.7%) patients who were already taking a CYP2C19-dependent drug were given or prescribed a CYP2C19-dependent drug while in the ED. Among the 53 patients genotyped, 52 (98%) were extensive metabolizers and 1 was a poor metabolizer.

Conclusions

In a population of ED patients, more than a quarter had taken a CYP2C19-dependent drug in the preceding 48 hours, but few were given or prescribed another CYP2C19-dependent drug in the ED. On genotyping analysis, CYP2C19 polymorphisms were uncommon in our cohort. We conclude that changing prescribing practice due to CYP2C19 drug-drug interaction or genotype is unlikely to be useful in most US ED populations.

SUBMITTER: Flaten HK

PROVIDER: S-EPMC4878122 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

CYP2C19 drug-drug and drug-gene interactions in ED patients.

Flaten Hanna K HK Kim Howard S HS Campbell Jenny J Hamilton Lisa L Monte Andrew A AA

The American journal of emergency medicine 20151109 2

<h4>Background</h4>CYP450 polymorphisms result in variable rates of drug metabolism. CYP drug-drug interactions can contribute to altered drug effectiveness and safety.<h4>Study objectives</h4>The primary objective was to determine the percentage of emergency department (ED) patients with cytochrome 2C19 (CYP2C19) drug-drug interactions. The secondary objective was to determine the prevalence of CYP2C19 polymorphisms in a US ED population.<h4>Methods</h4>We conducted a prospective observational ...[more]

PMID: 26639454

Similar Datasets

Project description:BackgroundOlder patients with coronary artery disease (CAD) are particularly vulnerable to the efficacy and adverse drug reactions, and may therefore particularly benefit from personalized medication. Drug-gene interactions (DGIs) occur when an individual's genotype affects the pharmacokinetics and/or pharmacodynamics of a victim drug.ObjectivesThis study aimed to investigate the impact of cardiovascular-related DGIs on the clinical efficacy and safety outcomes in older patients with CAD.MethodsHospitalized older patients (≥ 65 years old) with CAD were consecutively recruited from August 2018 to May 2022. Eligible patients were genotyped for the actionable pharmacogenetic variants of CYP2C9, CYP2C19, CYP2D6, CYP3A5, and SLCO1B1, which had clinical annotations or implementation guidelines for cardiovascular drugs. Allele frequencies and DGIs were determined in the cohort for the 5 actionable PGx genes and the prescribed cardiovascular drugs. All patients were followed up for at least 1 year. The influence of DGIs on the cardiovascular drug-related efficacy outcomes (all-cause mortality and/or major cardiovascular events, MACEs) and drug response phenotypes of "drug-stop" and "dose-decrease" were evaluated.ResultsA total of 1,017 eligible older patients with CAD were included, among whom 63.2% were male, with an average age of 80.8 years old, and 87.6% were administrated with polypharmacy (≥ 5 medications). After genotyping, we found that 96.0% of the older patients with CAD patients had at least one allele of the 5 pharmacogenes associated with a therapeutic change, indicating a need for a therapeutic change in a mean of 1.32 drugs of the 19 cardiovascular-related drugs. We also identified that 79.5% of the patients had at least one DGI (range 0-6). The median follow-up interval was 39 months. Independent of age, negative association could be found between the number of DGIs and all-cause mortality (adjusted HR: 0.84, 95% CI: 0.73-0.96, P = 0.008), and MACEs (adjusted HR: 0.84, 95% CI: 0.72-0.98, P = 0.023), but positive association could be found between the number of DGIs and drug response phenotypes (adjusted OR: 1.24, 95% CI: 1.05-1.45, P = 0.011) in the elderly patients with CAD.ConclusionsThe association between cardiovascular DGIs and the clinical outcomes emphasized the necessity for the integration of genetic and clinical data to enhance the optimization of cardiovascular polypharmacy in older patients with CAD. The causal relationship between DGIs and the clinical outcomes should be established in the large scale prospectively designed cohort study.

Project description:Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Dataset Information

CYP2C19 drug-drug and drug-gene interactions in ED patients.

Background

Study objectives

Methods

Results

Conclusions

Publications

CYP2C19 drug-drug and drug-gene interactions in ED patients.

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