Pharmacogenetics of Drug–Drug Interaction and Drug–Drug–Gene Interaction: A Systematic Review on CYP2C9, CYP2C19 and CYP2D6

Bahar, Muh. Akbar; Setiawan, Dedy; Hak, Eelko; Wilffert, Bob

doi:10.2217/pgs-2017-0194

Cited by 119 publications

(107 citation statements)

References 132 publications

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“…The figures presented in this manuscript represent pharmacogenetic‐guided treatment algorithms to select the so‐called least genetically vulnerable drug, by avoiding known drug‐gene interactions based on presence of pharmacogenetic test results. Although not discussed in detail in this review, it is important to consider the role of pharmacogenomics in determining the magnitude of drug‐drug interactions and drug‐drug‐gene interactions—that is, polymorphisms in a metabolic pathway and inhibition or induction of the same or minor pathway . In fact, a cross‐sectional study involving 22,885 patients found that there were approximately 6,900 drug interactions, of which drug‐drug‐gene, drug‐gene, and drug‐drug interactions accounted for 22%, 25%, and 53%, respectively .…”

Section: Resultsmentioning

confidence: 99%

Value of Supportive Care Pharmacogenomics in Oncology Practice

et al. 2018

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Integration of palliative medicine into the cancer care continuum has resulted in increased quality of life and survival for patients with many cancer types. However, suboptimal management of symptoms such as pain, neuropathy, depression, and nausea and vomiting continues to place a heavy burden on patients with cancer. As demonstrated in this theoretical case, pharmacogenomics can have a major effect on clinical response to medications used to treat these conditions. Recognizing the value of supportive care pharmacogenomics in oncology and application into routine practice offers an objective choice for the safest and most effective treatment compared with the traditional trial and error method.

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Section: Resultsmentioning

confidence: 99%

Value of Supportive Care Pharmacogenomics in Oncology Practice

et al. 2018

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“…5–7 However, current clinical practice guidelines for pharmacogenetic testing account for drug-gene interactions but do not account for the complexity of patients’ medication regimens. 8 Polypharmacy, or the concurrent taking of multiple medications, may increase the potential for adverse drug effects or medication non-response as a result of known or unknown drug-drug-gene interactions. 9 For example, a person with a normal pharmacogenotype may not adequately metabolize a given medication if they are taking a concurrent medication that inhibits or induces the metabolic pathway for that given medication.…”

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confidence: 99%

CYP2D6 drug-gene and drug-drug-gene interactions among patients prescribed pharmacogenetically actionable opioids

Knisely

Carpenter

Draucker

et al. 2017

Applied Nursing Research

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Purpose When codeine and tramadol are used for pain management, it is imperative that nurses are able to assess for potential drug-gene and drug-drug-gene interactions that could adversely impact drug metabolism and ultimately pain relief. Both drugs are metabolized through the CYP2D6 metabolic pathway which can be affected by medications as well the patient’s own pharmacogenotype. The purpose of this brief report is to identify drug-gene and drug-drug-gene interactions in 30 adult patients prescribed codeine or tramadol for pain. Methods We used three data sources: (1) six months of electronic health record data on the number and types of medications prescribed to each patient; (2) each patient’s CYP2D6 pharmacogenotype, and (3) published data on known CYP2D6 gene-drug and drug-drug-gene interactions. Results Ten patients (33%) had possible drug-gene or drug-drug-gene interactions. Five patients had CYP2D6 drug-gene interactions indicating they were not good candidates for codeine or tramadol. In addition, five patients had potential CYP2D6 drug-drug-gene interactions with either codeine or tramadol. Conclusion Our findings from this exploratory study underscores the importance of assessing and accounting for drug-gene and drug-drug-gene interactions in patients prescribed codeine or tramadol.

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“…Firstly, metoprolol is mainly metabolized by CYP2D6 and secondarily metabolized by CYP3A4. The reduced function of CYP3A4 in the elderly leads to a more important role of CYP2D6 in metabolizing metoprolol as a form of compensatory mechanism . Therefore, the weak inhibition of CYP2D6 may increase the blood concentration of metoprolol further in the elderly population.…”

Section: Discussionmentioning

confidence: 99%

“…Fourth, there was no information about the patient specific genetic status of CYP2D6. This is important because individuals with different CYP2D6 genotypes may have a different response toward the interaction . Goryachkina et al reported that among 17 patients with acute myocardial infarction treated with the combination of metoprolol‐paroxetine, there were 2 patients experiencing dose adjustments due to hypotension and bradycardia.…”

Section: Discussionmentioning

confidence: 99%

Discontinuation and dose adjustment of metoprolol after metoprolol‐paroxetine/fluoxetine co‐prescription in Dutch elderly

Bahar

Wang

Bos

et al. 2018

Pharmacoepidemiology and Drug

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PurposeCo‐prescription of paroxetine/fluoxetine (a strong CYP2D6 inhibitor) in metoprolol (a CYP2D6 substrate) users is common, but data on the clinical consequences of this drug‐drug interaction are limited and inconclusive. Therefore, we assessed the effect of paroxetine/fluoxetine initiation on the existing treatment with metoprolol on the discontinuation and dose adjustment of metoprolol among elderly.MethodsWe performed a cohort study using the University of Groningen IADB.nl prescription database (www.IADB.nl). We selected all elderly (≥60 years) who had ever been prescribed metoprolol and had a first co‐prescription of paroxetine/fluoxetine, citalopram (weak CYP2D6 inhibitor), or mirtazapine (negative control) from 1994 to 2015. The exposure group was metoprolol and paroxetine/fluoxetine co‐prescription, and the other groups acted as controls. The outcomes were early discontinuation and dose adjustment of metoprolol. Logistic regression was applied to estimate adjusted odds ratios (OR) and 95% confidence intervals (CI).ResultsCombinations of metoprolol‐paroxetine/fluoxetine, metoprolol‐citalopram, and metoprolol‐mirtazapine were started in 528, 673, and 625 patients, respectively. Compared with metoprolol‐citalopram, metoprolol‐paroxetine/fluoxetine was not significantly associated with the early discontinuation and dose adjustment of metoprolol (OR = 1.07, 95% CI:0.77‐1.48; OR = 0.87, 95% CI:0.57‐1.33, respectively). In comparison with metoprolol‐mirtazapine, metoprolol‐paroxetine/fluoxetine was associated with a significant 43% relative increase in early discontinuation of metoprolol (OR = 1.43, 95% CI:1.01‐2.02) but no difference in the risk of dose adjustment. Stratified analysis by gender showed that women have a significantly high risk of metoprolol early discontinuation (OR = 1.62, 95% CI:1.03‐2.53).ConclusionParoxetine/fluoxetine initiation in metoprolol prescriptions, especially for female older patients, is associated with the risk of early discontinuation of metoprolol.

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Pharmacogenetics of Drug–Drug Interaction and Drug–Drug–Gene Interaction: A Systematic Review on CYP2C9, CYP2C19 and CYP2D6

Cited by 119 publications

References 132 publications

Value of Supportive Care Pharmacogenomics in Oncology Practice

Value of Supportive Care Pharmacogenomics in Oncology Practice

CYP2D6 drug-gene and drug-drug-gene interactions among patients prescribed pharmacogenetically actionable opioids

Discontinuation and dose adjustment of metoprolol after metoprolol‐paroxetine/fluoxetine co‐prescription in Dutch elderly

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