Abstract
The incorporation of pharmacogenomics information into the drug dosing estimation formulations has been shown to increase the accuracy in drug dosing and decrease the frequency of adverse drug effects in many studies in the literature. In this paper, an estimation framework based on the Bayesian structural equation modeling, which is driven by pharmacogenomics, is proposed. The results show that the model compares favorably with the linear models in terms of prediction and explaining the variations in warfarin dosing.
Publication types
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Comparative Study
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Research Support, Non-U.S. Gov't
MeSH terms
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Adolescent
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Adult
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Aged
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Aged, 80 and over
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Bayes Theorem
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Child
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Cohort Studies
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Cytochrome P-450 CYP2C9 / genetics
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Data Mining
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Databases, Factual
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Humans
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Middle Aged
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Pharmacogenetics / methods*
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Precision Medicine / methods*
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Turkey
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Vitamin K Epoxide Reductases / genetics
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Warfarin / administration & dosage*
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Warfarin / pharmacology*
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White People / genetics
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Young Adult
Substances
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Warfarin
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CYP2C9 protein, human
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Cytochrome P-450 CYP2C9
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VKORC1 protein, human
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Vitamin K Epoxide Reductases