ArticleEuropean journal of clinical pharmacology2018
Impact of incorporating ABCB1 and CYP4F2 polymorphisms in a pharmacogenetics-guided warfarin dosing algorithm for the Brazilian population.
Article in European journal of clinical pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Opposite Response to Vitamin K Antagonists: A Report of Two Cases and Systematic Review of Literature.Journal of personalized medicine · 2022Review
- Cardiovascular Pharmacogenomics: An Update on Clinical Studies of Antithrombotic Drugs in Brazilian Patients.Molecular diagnosis & therapy · 2021Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
purposeInterpatient variation of warfarin dose requirements may be explained by genetic variations and general and clinical factors. In this scenario, diverse population-calibrated dosing algorithms, which incorporate the main warfarin dosing influencers, have been widely proposed for predicting supposed warfarin maintenance dose, in order to prevent and reduce adverse events. The aim of the present study was to evaluate the impact of the inclusion of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms as additional covariates in a previously developed pharmacogenetic-based warfarin dosing algorithm calibrated for the Brazilian population.
methodsTwo independent cohorts of patients treated with warfarin (n = 832 and n = 133) were included for derivation and replication of the algorithm, respectively. Genotyping of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms was performed by polymerase chain reaction followed by melting curve analysis and TaqMan® assay, respectively. A multiple linear regression was performed for the warfarin stable doses as a dependent variable, considering clinical, general, and genetic data as covariates.
resultsThe inclusion of ABCB1 and CYP4F2 polymorphisms was able to improve the algorithm's coefficient of determination (R
conclusionAlthough our study indicates that the contribution of the combined ABCB1 and CYP4F2 genotypes in explaining the overall variability in warfarin dose is not very large, we demonstrated that these pharmacogenomic data are statistically significant. However, the clinical relevance and cost-effective impact of incorporating additional variants in warfarin dosing algorithms should be carefully evaluated.
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Registered trials
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