Literature DB >> 20204461

Accuracy assessment of pharmacogenetically predictive warfarin dosing algorithms in patients of an academic medical center anticoagulation clinic.

Paul B Shaw1, Jennifer L Donovan, Maichi T Tran, Stephenie C Lemon, Pamela Burgwinkle, Joel Gore.   

Abstract

The objectives of this retrospective cohort study are to evaluate the accuracy of pharmacogenetic warfarin dosing algorithms in predicting therapeutic dose and to determine if this degree of accuracy warrants the routine use of genotyping to prospectively dose patients newly started on warfarin. Seventy-one patients of an outpatient anticoagulation clinic at an academic medical center who were age 18 years or older on a stable, therapeutic warfarin dose with international normalized ratio (INR) goal between 2.0 and 3.0, and cytochrome P450 isoenzyme 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) genotypes available between January 1, 2007 and September 30, 2008 were included. Six pharmacogenetic warfarin dosing algorithms were identified from the medical literature. Additionally, a 5 mg fixed dose approach was evaluated. Three algorithms, Zhu et al. (Clin Chem 53:1199-1205, 2007), Gage et al. (J Clin Ther 84:326-331, 2008), and International Warfarin Pharmacogenetic Consortium (IWPC) (N Engl J Med 360:753-764, 2009) were similar in the primary accuracy endpoints with mean absolute error (MAE) ranging from 1.7 to 1.8 mg/day and coefficient of determination R (2) from 0.61 to 0.66. However, the Zhu et al. algorithm severely over-predicted dose (defined as >or=2x or >or=2 mg/day more than actual dose) in twice as many (14 vs. 7%) patients as Gage et al. 2008 and IWPC 2009. In conclusion, the algorithms published by Gage et al. 2008 and the IWPC 2009 were the two most accurate pharmacogenetically based equations available in the medical literature in predicting therapeutic warfarin dose in our study population. However, the degree of accuracy demonstrated does not support the routine use of genotyping to prospectively dose all patients newly started on warfarin.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20204461     DOI: 10.1007/s11239-010-0459-3

Source DB:  PubMed          Journal:  J Thromb Thrombolysis        ISSN: 0929-5305            Impact factor:   2.300


  14 in total

1.  Several-fold increase in risk of overanticoagulation by CYP2C9 mutations.

Authors:  Jonatan D Lindh; Stefan Lundgren; Lennart Holm; Lars Alfredsson; Anders Rane
Journal:  Clin Pharmacol Ther       Date:  2005-11       Impact factor: 6.875

Review 2.  Human P450 metabolism of warfarin.

Authors:  L S Kaminsky; Z Y Zhang
Journal:  Pharmacol Ther       Date:  1997       Impact factor: 12.310

3.  Prospective dosing of warfarin based on cytochrome P-450 2C9 genotype.

Authors:  Deepak Voora; Charles Eby; Mark W Linder; Paul E Milligan; Bonny L Bukaveckas; Howard L McLeod; William Maloney; John Clohisy; R Steven Burnett; Leonard Grosso; Susan K Gatchel; Brian F Gage
Journal:  Thromb Haemost       Date:  2005-04       Impact factor: 5.249

4.  Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy.

Authors:  Mitchell K Higashi; David L Veenstra; L Midori Kondo; Ann K Wittkowsky; Sengkeo L Srinouanprachanh; Fred M Farin; Allan E Rettie
Journal:  JAMA       Date:  2002-04-03       Impact factor: 56.272

5.  The impact of CYP2C9 and VKORC1 genetic polymorphism and patient characteristics upon warfarin dose requirements: proposal for a new dosing regimen.

Authors:  Elizabeth A Sconce; Tayyaba I Khan; Hilary A Wynne; Peter Avery; Louise Monkhouse; Barry P King; Peter Wood; Patrick Kesteven; Ann K Daly; Farhad Kamali
Journal:  Blood       Date:  2005-06-09       Impact factor: 22.113

6.  The largest prospective warfarin-treated cohort supports genetic forecasting.

Authors:  Mia Wadelius; Leslie Y Chen; Jonatan D Lindh; Niclas Eriksson; Mohammed J R Ghori; Suzannah Bumpstead; Lennart Holm; Ralph McGinnis; Anders Rane; Panos Deloukas
Journal:  Blood       Date:  2008-06-23       Impact factor: 22.113

7.  Estimation of warfarin maintenance dose based on VKORC1 (-1639 G>A) and CYP2C9 genotypes.

Authors:  Yusheng Zhu; Michael Shennan; Kristen K Reynolds; Nancy A Johnson; Matthew R Herrnberger; Roland Valdes; Mark W Linder
Journal:  Clin Chem       Date:  2007-05-17       Impact factor: 8.327

8.  Use of pharmacogenetics and clinical factors to predict the maintenance dose of warfarin.

Authors:  Brian F Gage; Charles Eby; Paul E Milligan; Gerald A Banet; Jill R Duncan; Howard L McLeod
Journal:  Thromb Haemost       Date:  2004-01       Impact factor: 5.249

9.  Estimation of the warfarin dose with clinical and pharmacogenetic data.

Authors:  T E Klein; R B Altman; N Eriksson; B F Gage; S E Kimmel; M-T M Lee; N A Limdi; D Page; D M Roden; M J Wagner; M D Caldwell; J A Johnson
Journal:  N Engl J Med       Date:  2009-02-19       Impact factor: 91.245

Review 10.  Genetic testing before anticoagulation? A systematic review of pharmacogenetic dosing of warfarin.

Authors:  Kirsten Neudoerffer Kangelaris; Stephen Bent; Robert L Nussbaum; David A Garcia; Jeffrey A Tice
Journal:  J Gen Intern Med       Date:  2009-03-21       Impact factor: 5.128

View more
  13 in total

1.  Testing of VKORC1 and CYP2C9 alleles to guide warfarin dosing. Test category: pharmacogenomic (treatment).

Authors:  Daurice Grossniklaus
Journal:  PLoS Curr       Date:  2010-09-14

2.  Iterative Development and Evaluation of a Pharmacogenomic-Guided Clinical Decision Support System for Warfarin Dosing.

Authors:  Brittany L Melton; Alan J Zillich; Jason Saleem; Alissa L Russ; James E Tisdale; Brian R Overholser
Journal:  Appl Clin Inform       Date:  2016-11-23       Impact factor: 2.342

Review 3.  Role of pharmacogenomics in the management of traditional and novel oral anticoagulants.

Authors:  Larisa H Cavallari; Jaekyu Shin; Minoli A Perera
Journal:  Pharmacotherapy       Date:  2011-12       Impact factor: 4.705

4.  Effect of the VKORC1 D36Y variant on warfarin dose requirement and pharmacogenetic dose prediction.

Authors:  Daniel Kurnik; Husam Qasim; Sophie Sominsky; Aharon Lubetsky; Noa Markovits; Chun Li; C Michael Stein; Hillel Halkin; Eva Gak; Ronen Loebstein
Journal:  Thromb Haemost       Date:  2012-08-07       Impact factor: 5.249

5.  Prospective validation of the International Warfarin Pharmacogenetics Consortium algorithm in high-risk elderly people (VIALE study).

Authors:  Amelia Filippelli; Simona Signoriello; Ciro Bancone; Graziamaria Corbi; Valentina Manzo; Severino Iesu; Cecilia Politi; Alberto Gigantino; Maria Teresa De Donato; Paolo Masiello; Vittorio Simeon; Alessandro Della Corte; Michele Cellurale; Valeria Conti; Massimo Frigino; Tiziana Ciarambino; Marta Marracino; Laura Carpenito; Nicola Ferrara; Marisa De Feo; Ciro Gallo
Journal:  Pharmacogenomics J       Date:  2019-12-05       Impact factor: 3.550

6.  Pharmacogenetic aspects of coumarinic oral anticoagulant therapies.

Authors:  Saurabh Singh Rathore; Surendra Kumar Agarwal; Shantanu Pande; Sushil Kumar Singh; Tulika Mittal; Balraj Mittal
Journal:  Indian J Clin Biochem       Date:  2011-05-01

7.  Genetic polymorphisms and dosing of vitamin K antagonist in Indian patients after heart valve surgery.

Authors:  Shiv Kumar Choudhary; Arun Basil Mathew; Amit Parhar; Milind Padmakar Hote; Sachin Talwar; Palleti Rajashekhar
Journal:  Indian J Thorac Cardiovasc Surg       Date:  2019-04-22

Review 8.  Effect of genetic variants, especially CYP2C9 and VKORC1, on the pharmacology of warfarin.

Authors:  Erik Fung; Nikolaos A Patsopoulos; Steven M Belknap; Daniel J O'Rourke; John F Robb; Jeffrey L Anderson; Nicholas W Shworak; Jason H Moore
Journal:  Semin Thromb Hemost       Date:  2012-10-06       Impact factor: 4.180

9.  Validation of pharmacogenetic algorithms and warfarin dosing table in Egyptian patients.

Authors:  Naglaa Samir Bazan; Nirmeen Ahmed Sabry; Amal Rizk; Sherif Mokhtar; Osama Badary
Journal:  Int J Clin Pharm       Date:  2012-07-27

10.  Pathway analysis of genome-wide data improves warfarin dose prediction.

Authors:  Roxana Daneshjou; Nicholas P Tatonetti; Konrad J Karczewski; Hersh Sagreiya; Stephane Bourgeois; Katarzyna Drozda; James K Burmester; Tatsuhiko Tsunoda; Yusuke Nakamura; Michiaki Kubo; Matthew Tector; Nita A Limdi; Larisa H Cavallari; Minoli Perera; Julie A Johnson; Teri E Klein; Russ B Altman
Journal:  BMC Genomics       Date:  2013-05-28       Impact factor: 3.969

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.