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Anticoagulation Endpoints With Clinical Implementation of Warfarin Pharmacogenetic Dosing in a Real‐World Setting: A Proposal for a New Pharmacogenetic Dosing Approach

Overview of attention for article published in Clinical Pharmacology & Therapeutics, December 2016
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Title
Anticoagulation Endpoints With Clinical Implementation of Warfarin Pharmacogenetic Dosing in a Real‐World Setting: A Proposal for a New Pharmacogenetic Dosing Approach
Published in
Clinical Pharmacology & Therapeutics, December 2016
DOI 10.1002/cpt.558
Pubmed ID
Authors

MJ Arwood, J Deng, K Drozda, O Pugach, EA Nutescu, S Schmidt, JD Duarte, LH Cavallari

Abstract

Achieving therapeutic anticoagulation efficiently with warfarin is important to reduce thrombotic and bleeding risks and is influenced by genotype. Utilizing data from a diverse population of 257 patients who received VKORC1 and CYP2C9 genotype-guided warfarin dosing, we aimed to examine genotype-associated differences in anticoagulation endpoints and derive a novel pharmacogenetic nomogram to more optimally dose warfarin. We observed significant differences across patients with 0, 1, or ≥2 reduced-function VKORC1 or CYP2C9 alleles, respectively, in time to achieve therapeutic international normalized ratio (INR) (7.8 ± 5.8, 7.2 ± 4.7, and 5.4 ± 4.6 days, P = 0.0004) and mean percentage of time in therapeutic range in the first 28 days (22.2, 27.8, and 32.2%, P = 0.0127) with use of existing pharmacogenetic algorithms. These data suggest that more aggressive dosing is necessary for patients with 0 to 1 VKORC1/CYP2C9 variants to more efficiently achieve therapeutic anticoagulation. Herein, we provide a novel kinetic/pharmacodynamic-derived dosing nomogram optimized for a heterogeneous patient population.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 12%
Student > Bachelor 3 12%
Researcher 3 12%
Student > Master 3 12%
Lecturer 1 4%
Other 4 16%
Unknown 8 32%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 4 16%
Medicine and Dentistry 4 16%
Biochemistry, Genetics and Molecular Biology 3 12%
Agricultural and Biological Sciences 2 8%
Nursing and Health Professions 2 8%
Other 2 8%
Unknown 8 32%