Literature DB >> 27121899

An expanded pharmacogenomics warfarin dosing table with utility in generalised dosing guidance.

Payman Shahabi, Laura B Scheinfeldt, Daniel E Lynch, Tara J Schmidlen, Sylvie Perreault, Margaret A Keller, Rachel Kasper, Lisa Wawak, Joseph P Jarvis, Norman P Gerry, Erynn S Gordon, Michael F Christman, Marie-Pierre Dubé, Neda Gharani1.   

Abstract

Pharmacogenomics (PGx) guided warfarin dosing, using a comprehensive dosing algorithm, is expected to improve dose optimisation and lower the risk of adverse drug reactions. As a complementary tool, a simple genotype-dosing table, such as in the US Food and Drug Administration (FDA) Coumadin drug label, may be utilised for general risk assessment of likely over- or under-anticoagulation on a standard dose of warfarin. This tool may be used as part of the clinical decision support for the interpretation of genetic data, serving as a first step in the anticoagulation therapy decision making process. Here we used a publicly available warfarin dosing calculator (www.warfarindosing.org) to create an expanded gene-based warfarin dosing table, the CPMC-WD table that includes nine genetic variants in CYP2C9, VKORC1, and CYP4F2. Using two datasets, a European American cohort (EUA, n=73) and the Quebec Warfarin Cohort (QWC, n=769), we show that the CPMC-WD table more accurately predicts therapeutic dose than the FDA table (51 % vs 33 %, respectively, in the EUA, McNemar's two-sided p=0.02; 52 % vs 37 % in the QWC, p<1×10(-6)). It also outperforms both the standard of care 5 mg/day dosing (51 % vs 34 % in the EUA, p=0.04; 52 % vs 31 % in the QWC, p<1×10(-6)) as well as a clinical-only algorithm (51 % vs 38 % in the EUA, trend p=0.11; 52 % vs 45 % in the QWC, p=0.003). This table offers a valuable update to the PGx dosing guideline in the drug label.

Entities:  

Keywords:  CYP2C9; CYP4F2; Pharmacogenomics; VKORC1; warfarin

Mesh:

Substances:

Year:  2016        PMID: 27121899      PMCID: PMC6375065          DOI: 10.1160/TH15-12-0955

Source DB:  PubMed          Journal:  Thromb Haemost        ISSN: 0340-6245            Impact factor:   5.249


  8 in total

1.  Verification of pharmacogenomics-based algorithms to predict warfarin maintenance dose using registered data of Japanese patients.

Authors:  Maki Sasano; Masako Ohno; Yuya Fukuda; Shinpei Nonen; Sachiko Hirobe; Shinichiro Maeda; Yoshihiro Miwa; Junya Yokoyama; Hiroyuki Nakayama; Shigeru Miyagawa; Yoshiki Sawa; Yasushi Fujio; Makiko Maeda
Journal:  Eur J Clin Pharmacol       Date:  2019-03-09       Impact factor: 2.953

2.  Pharmacogenetics and Practice: Tailoring Prescribing for Safety and Effectiveness.

Authors:  Cathy R Fulton; Marelize Swart; Thomas De Luca; Stephanie N Liu; Kimberly S Collins; Zeruesenay Desta; Brandon T Gufford; Michael T Eadon
Journal:  J Nurse Pract       Date:  2018-11-02       Impact factor: 0.767

Review 3.  Pharmacogenomics of CYP2C9: Functional and Clinical Considerations.

Authors:  Ann K Daly; Allan E Rettie; Douglas M Fowler; John O Miners
Journal:  J Pers Med       Date:  2017-12-28

4.  Prevalence of clinically actionable genotypes and medication exposure of older adults in the community.

Authors:  Nilofar Daneshi; Elizabeth Holliday; Stephen Hancock; Jennifer J Schneider; Rodney J Scott; John Attia; Elizabeth A Milward
Journal:  Pharmgenomics Pers Med       Date:  2017-01-27

5.  Challenges in Translating GWAS Results to Clinical Care.

Authors:  Laura B Scheinfeldt; Tara J Schmidlen; Norman P Gerry; Michael F Christman
Journal:  Int J Mol Sci       Date:  2016-08-04       Impact factor: 5.923

6.  Precision Military Medicine: Conducting a multi-site clinical utility study of genomic and lifestyle risk factors in the United States Air Force.

Authors:  Susan K Delaney; Ruth Brenner; Tara J Schmidlen; Michael P Dempsey; Kim E London; Erynn S Gordon; Mark Bellafante; Ashley Nasuti; Laura B Scheinfeldt; Kaveri D Rajula; Leo Jose; Joseph P Jarvis; Norman P Gerry; Michael F Christman
Journal:  NPJ Genom Med       Date:  2017-01-19       Impact factor: 8.617

Review 7.  Warfarin dosing algorithms: A systematic review.

Authors:  Innocent G Asiimwe; Eunice J Zhang; Rostam Osanlou; Andrea L Jorgensen; Munir Pirmohamed
Journal:  Br J Clin Pharmacol       Date:  2020-11-18       Impact factor: 4.335

8.  Development of a system to support warfarin dose decisions using deep neural networks.

Authors:  Heemoon Lee; Hyun Joo Kim; Hyoung Woo Chang; Dong Jung Kim; Jonghoon Mo; Ji-Eon Kim
Journal:  Sci Rep       Date:  2021-07-20       Impact factor: 4.379

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.