Literature DB >> 14691573

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

Brian F Gage1, Charles Eby, Paul E Milligan, Gerald A Banet, Jill R Duncan, Howard L McLeod.   

Abstract

Knowledge of pharmacogenetics may help clinicians predict their patients' therapeutic dose of warfarin, thereby decreasing the risk of bleeding during warfarin initiation. Our goal was to use pharmacogenetics to develop an algorithm that uses genetic, clinical, and demographic factors to estimate the warfarin dose a priori. We collected a blood sample, demographic variables, laboratory values, smoking status, names of medications, and dietary history from 369 patients who were taking a maintenance dose of warfarin. Using polymerase chain reaction, we genotyped each participant for the presence of 8 polymorphisms in the cytochrome P450 2C9 system. Using multiple regression, we quantified the association between warfarin dose and all factors. Advanced age, lower body surface area (BSA), and the presence of cytochrome P450 2C9 *2 or *3 single nucleotide polymorphisms were strongly associated (P < 0.001) with lower warfarin dose: the maintenance dose decreased by 8% per decade of age, by 13% per standard deviation decrease in BSA, by 19% per 2C9*2 allele, and by 30% per 2C9*3 allele. Warfarin doses were 29% lower in patients who took amiodarone, 12% lower in patients who took simvastatin, 21% lower in patients whose target INR was 2.5 rather than 3.0, and 11% lower in white rather than African-American participants (P < 0.05 for these comparisons). An algorithm that included these factors and one of borderline significance (sex), explained 39% of the variance in the maintenance warfarin dose. Use of this pharmacogenetic model had potential to prevent patients from being overdosed when initiating warfarin: we estimate that only 24 (6.5%) patients would have been over- dosed by >2 mg/day with pharmacogenetic dosing compared to 59 (16%) patients who would have been overdosed if they had been prescribed the empirical dose of 5 mg/day (P < 0.001). In conclusion, the maintenance warfarin dose can be estimated from demographic, clinical, and pharmacogenetic factors that can be obtained at the time of warfarin initiation.

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Year:  2004        PMID: 14691573     DOI: 10.1160/TH03-06-0379

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


  90 in total

1.  Genetic warfarin dosing: tables versus algorithms.

Authors:  Brian S Finkelman; Brian F Gage; Julie A Johnson; Colleen M Brensinger; Stephen E Kimmel
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2.  Pharmacogenetics--expectations and reality.

Authors:  Geoff Tucker
Journal:  BMJ       Date:  2004-07-03

3.  CYP4F2 rs2108622: a minor significant genetic factor of warfarin dose in Han Chinese patients with mechanical heart valve replacement.

Authors:  Han-Jing Cen; Wu-Tao Zeng; Xiu-Yu Leng; Min Huang; Xiao Chen; Jia-Li Li; Zhi-Ying Huang; Hui-Chang Bi; Xue-Ding Wang; Yan-Ling He; Fan He; Rui-Na Zhou; Qi-Shan Zheng; Li-Zi Zhao
Journal:  Br J Clin Pharmacol       Date:  2010-08       Impact factor: 4.335

4.  Integration of genetic, clinical, and INR data to refine warfarin dosing.

Authors:  P Lenzini; M Wadelius; S Kimmel; J L Anderson; A L Jorgensen; M Pirmohamed; M D Caldwell; N Limdi; J K Burmester; M B Dowd; P Angchaisuksiri; A R Bass; J Chen; N Eriksson; A Rane; J D Lindh; J F Carlquist; B D Horne; G Grice; P E Milligan; C Eby; J Shin; H Kim; D Kurnik; C M Stein; G McMillin; R C Pendleton; R L Berg; P Deloukas; B F Gage
Journal:  Clin Pharmacol Ther       Date:  2010-04-07       Impact factor: 6.875

5.  Combined CYP2C9, VKORC1 and CYP4F2 frequencies among racial and ethnic groups.

Authors:  Stuart A Scott; Rame Khasawneh; Inga Peter; Ruth Kornreich; Robert J Desnick
Journal:  Pharmacogenomics       Date:  2010-06       Impact factor: 2.533

6.  CYP2C9 promoter variable number tandem repeat polymorphism regulates mRNA expression in human livers.

Authors:  Danxin Wang; Xiaochun Sun; Yan Gong; Brian E Gawronski; Taimour Y Langaee; Mohamed Hossam A Shahin; Sherief I Khalifa; Julie A Johnson
Journal:  Drug Metab Dispos       Date:  2012-01-30       Impact factor: 3.922

Review 7.  Pharmacogenetics of target genes across the warfarin pharmacological pathway.

Authors:  Suman Lal; Srinivasa Rao Jada; Xiaoqiang Xiang; Wan-Teck Lim; Edmund J D Lee; Balram Chowbay
Journal:  Clin Pharmacokinet       Date:  2006       Impact factor: 6.447

8.  Influence of Age on Warfarin Dose, Anticoagulation Control, and Risk of Hemorrhage.

Authors:  Aditi Shendre; Gaurav M Parmar; Chrisly Dillon; Timothy Mark Beasley; Nita A Limdi
Journal:  Pharmacotherapy       Date:  2018-02-27       Impact factor: 4.705

9.  Laboratory and clinical outcomes of pharmacogenetic vs. clinical protocols for warfarin initiation in orthopedic patients.

Authors:  P A Lenzini; G R Grice; P E Milligan; M B Dowd; S Subherwal; E Deych; C S Eby; C R King; R M Porche-Sorbet; C V Murphy; R Marchand; E A Millican; R L Barrack; J C Clohisy; K Kronquist; S K Gatchel; B F Gage
Journal:  J Thromb Haemost       Date:  2008-07-24       Impact factor: 5.824

10.  Predictors of unstable anticoagulation in African Americans.

Authors:  Larisa H Cavallari; Jonathan L Aston; Kathryn M Momary; Nancy L Shapiro; Shitalben R Patel; Edith A Nutescu
Journal:  J Thromb Thrombolysis       Date:  2008-06-19       Impact factor: 2.300

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