Hospitalization for Hemorrhage Among Warfarin Recipients Prescribed Amiodarone

Lam, Jason; Gomes, Tara; Juurlink, David N.; Mamdani, Muhammad; Pullenayegum, Eleanor; Kearon, Clive; Spencer, Frederick A.; Paterson, Michael; Zheng, Hong; Holbrook, Anne

doi:10.1016/j.amjcard.2013.03.051

Cited by 23 publications

(18 citation statements)

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“…The primary safety end point was the occurrence of a major bleeding event using primary hospital discharge diagnosis codes including intracranial hemorrhage, major gastrointestinal bleeding, and other major bleeding events (). Defining major bleeding events based on inpatient claims was previously found to have a PPV between 89% and 98% . The secondary study outcome was the occurrence of minor bleeding events presenting on outpatient encounter claims using a primary or secondary diagnosis (i.e., those not requiring hospitalization).…”

Section: Methodsmentioning

confidence: 99%

Comparative Effectiveness and Safety of Ticagrelor versus Prasugrel in Patients with Acute Coronary Syndrome: A Retrospective Cohort Analysis

et al. 2019

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STUDY OBJECTIVE To compare the effectiveness and safety of ticagrelor versus prasugrel in preventing recurrent cardiovascular disease (CVD) and major bleeding events in patients with acute coronary syndrome (ACS). DESIGN Retrospective cohort analysis. DATA SOURCE Truven Commercial and Medicare Supplemental claims database (2011)(2012)(2013)(2014)(2015)(2016). PATIENTS Study consisted of adults with ACS who newly initiated ticagrelor or prasugrel within 7 days of their first ACS diagnosis and had no prior use for at least 12 months; after propensity score matching, 10,073 patients were in each group. METHODS The primary study outcomes, first occurrence of a recurrent nonfatal CVD event (composite of myocardial infarction and stroke) and occurrence of a major bleeding event, were compared between the ticagrelor and prasugrel groups. Secondary outcomes included occurrence of minor bleeding events, defined based on the presence of bleeding events in outpatient claims. Cox proportional hazards models after propensity score matching were used to obtain the hazard ratio (HR) and 95% confidence interval (CI). In the Cox proportional hazards model, the use of ticagrelor was associated with a decreased risk of recurrent nonfatal CVD events (HR 0.80, 95% CI 0.70-0.92) and major bleeding events (HR 0.54, 95% CI 0.41-0.70) compared with prasugrel. Additionally, the use of ticagrelor was associated with a lower risk of minor bleeding events compared with prasugrel (HR 0.71, 95% CI 0.65-0.78). CONCLUSION In this population-based cohort of incident ACS patients, ticagrelor was associated with a reduced rate of recurrent nonfatal CVD events, major and minor bleeding events compared with prasugrel. KEY WORDS acute coronary syndrome, ticagrelor, prasugrel, effectiveness. (Pharmacotherapy 2019;39(9):912-920)

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Section: Methodsmentioning

confidence: 99%

Comparative Effectiveness and Safety of Ticagrelor versus Prasugrel in Patients with Acute Coronary Syndrome: A Retrospective Cohort Analysis

et al. 2019

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“…While it is acknowledged that not all interacting drugs induce a DME phenoconversion, many of these nonphenoconverting drugs have a pharmacodynamic effect on the clinical outcome of interest (bleeding in the case of warfarin), thereby further prejudicing the conclusions from association studies. Amiodarone inhibits CYP2C9, and Lam et al [80] reported that overall, 56 (0.8%) amiodarone recipients and 23 (0.3%) control patients receiving warfarin were hospitalized for haemorrhage within 30 days of initiating amiodarone (adjusted hazard ratio 2.45, 95% CI 1.49-4.02). Seven of 56 (12.5%) patients hospitalized for a haemorrhage after starting amiodarone died in hospital.…”

Section: Genotype-dependent Susceptibility To Phenoconversionmentioning

confidence: 99%

Addressing phenoconversion: the Achilles' heel of personalized medicine

Shah

Smith

2015

Brit J Clinical Pharma

221

217

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Phenoconversion is a phenomenon that converts genotypic extensive metabolizers (EMs) into phenotypic poor metabolizers (PMs) of drugs, thereby modifying their clinical response to that of genotypic PMs. Phenoconversion, usually resulting from nongenetic extrinsic factors, has a significant impact on the analysis and interpretation of genotype-focused clinical outcome association studies and personalizing therapy in routine clinical practice. The high phenotypic variability or genotype-phenotype mismatch, frequently observed due to phenoconversion within the genotypic EM population, means that the real number of phenotypic PM subjects may be greater than predicted from their genotype alone, because many genotypic EMs would be phenotypically PMs. If the phenoconverted population with genotype-phenotype mismatch, most extensively studied for CYP2D6, is as large as the evidence suggests, there is a real risk that genotype-focused association studies, typically correlating only the genotype with clinical outcomes, may miss clinically strong pharmacogenetic associations, thus compromising any potential for advancing the prospects of personalized medicine. This review focuses primarily on co-medication-induced phenoconversion and discusses potential approaches to rectify some of the current shortcomings. It advocates routine phenotyping of subjects in genotype-focused association studies and proposes a new nomenclature to categorize study populations. Even with strong and reliable data associating patients' genotypes with clinical outcome(s), there are problems clinically in applying this knowledge into routine pharmacotherapy because of potential genotype-phenotype mismatch. Drug-induced phenoconversion during routine clinical practice remains a major public health issue. Therefore, the principal challenges facing personalized medicine, which need to be addressed, include identification of the following factors: (i) drugs that are susceptible to phenoconversion; (ii) co-medications that can cause phenoconversion; and (iii) dosage amendments that need to be applied during and following phenoconversion. Pharmacogenetics and personalized medicineThe majority of drug-metabolizing enzymes (DMEs) are subject to genetic polymorphism and show some degree of functionally significant polymorphism in the population. The clearest data in this regard relate to cytochromes P450 CYP2D6 and CYP2C19 and thiopurine methyltransferase (TPMT). These genetically determined polymorphisms give rise to three distinct genotype-based subpopulations with respect to each DME, namely extensive metabolizers (EMs), poor metabolizers (PMs) and a subgroup in between, the intermediate metabolizers (IMs). In addition, for CYP2D6 and CYP2C19, there is a fourth genotype, the ultrarapid metabolizer (UM) genotype, resulting from inheritance of either multiple copies of the functional wild-type allele, such as CYP2D6*1, or a higher metabolic capacity resulting from increased transcription of DME due to the presence of a genetic variant found in the promoter ...

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“…Other studies have assessed the risk of bleeding or risk of hospitalization for haemorrhage due to drug interactions with warfarin. [7][8][9][10][11] A recent approach employed in a small number of studies that investigate warfarin drug-drug interactions is the use of real-world data from administrative databases. This approach allows the identification of the frequency of concurrent use of warfarin with other drugs and quantification of the combined treatment effect on INR values and has provided clinically highly useful information.…”

Section: Introductionmentioning

confidence: 99%