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Thromb Haemost 2012; 107(02): 232-240
DOI: 10.1160/TH11-06-0388
Blood Coagulation, Fibrinolysis and Cellular Haemostasis
Schattauer GmbH

Pharmacogenetic warfarin dose refinements remain significantly influenced by genetic factors after one week of therapy

Benjamin D. Horne
1   Cardiovascular Department, Intermountain Medical Center, Salt Lake City, Utah, USA
2   Division of Genetic Epidemiology, Department of Medicine, University of Utah, Salt Lake City, Utah, USA
,
Petra A. Lenzini
3   Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
,
Mia Wadelius
4   Department of Medical Sciences, Clinical Pharmacology, Uppsala University, Uppsala, Sweden
,
Andrea L. Jorgensen
5   Center for Medical Statistics and Health Evaluation, University of Liverpool, Liverpool, UK
,
Stephen E. Kimmel
6   Departments of Medicine and of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
,
Paul M. Ridker
7   Center for Cardiovascular Disease Prevention, Harvard Medical School, Boston, Massachusetts, USA
8   Division of Preventive Medicine, Harvard Medical School, Boston, Massachusetts, USA
9   Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
,
Niclas Eriksson
4   Department of Medical Sciences, Clinical Pharmacology, Uppsala University, Uppsala, Sweden
10   Uppsala Clinical Research Center – UCR, Uppsala University Hospital, Uppsala, Sweden
,
Jeffrey L. Anderson
1   Cardiovascular Department, Intermountain Medical Center, Salt Lake City, Utah, USA
11   Division of Cardiology, Department of Medicine, University of Utah, Salt Lake City, Utah, USA
,
Munir Pirmohamed
12   Wolfson Center for Personalized Medicine, University of Liverpool, Liverpool, UK
,
Nita A. Limdi
13   Departments of Neurology and Epidemiology, University of Alabama, Birmingham, Alabama, USA
,
Robert C. Pendleton
14   Division of General Internal Medicine, Department of Medicine, University of Utah, Salt Lake City, Utah, USA
,
Gwendolyn A. McMillin
15   Associated and Regional University Pathologists, Department of Pathology, University of Utah, Salt Lake City, Utah, USA
,
James K. Burmester
16   Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
,
Daniel Kurnik
17   Division of Clinical Pharmacology, Department of Medicine and Pharmacology, Vanderbilt University, Nashville, Tennessee, USA
,
C. Michael Stein
17   Division of Clinical Pharmacology, Department of Medicine and Pharmacology, Vanderbilt University, Nashville, Tennessee, USA
,
Michael D. Caldwell
18   Department of Surgery, Marshfield Clinic, Marshfield, Wisconsin, USA
,
Charles S. Eby
3   Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
19   Department of Pathology, Washington University in St. Louis, St. Louis, Missouri, USA
,
Anders Rane
20   Division of Clinical Pharmacology, Karolinska Institutet, Stockholm, Sweden
,
Jonatan D. Lindh
20   Division of Clinical Pharmacology, Karolinska Institutet, Stockholm, Sweden
,
Jae-Gook Shin
21   Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea
,
Ho-Sook Kim
21   Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea
,
Pantep Angchaisuksiri
22   Department of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
,
Robert J. Glynn
7   Center for Cardiovascular Disease Prevention, Harvard Medical School, Boston, Massachusetts, USA
8   Division of Preventive Medicine, Harvard Medical School, Boston, Massachusetts, USA
,
Kathryn E. Kronquist
23   Molecular Diagnostic Laboratory, Kaiser Permanente, Denver, Colorado, USA
,
John F. Carlquist
1   Cardiovascular Department, Intermountain Medical Center, Salt Lake City, Utah, USA
11   Division of Cardiology, Department of Medicine, University of Utah, Salt Lake City, Utah, USA
,
Gloria R. Grice
24   Department of Pharmacy Practice, St. Louis College of Pharmacy, St. Louis, Missouri, USA
,
Robert L. Barrack
3   Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
25   Department of Orthopaedic Surgery, Washington University in St. Louis, St. Louis, Missouri, USA
,
Juan Li
3   Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
,
Brian F. Gage
3   Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
› Author Affiliations Financial support: This study was funded by the US National Institutes of Health (K23 NS45598; K24 HL070936; RO1s HL066176, HL074724, HL092173, HL097036), the Thailand Senior Researcher Fund, the National Research Foundation of Korea (Korea Ministry of Education, Science and Technology grant R13–2007–023–00000–0), the Swedish Heart and Lung foundation, the Swedish Research Council (Medicine 04496 and 523–2008–5568), the UK Department of Health, and the Deseret Foundation (Salt Lake City, UT, USA).
Further Information

Publication History

Received: 08 June 2011

Accepted after major revision: 04 November 2011

Publication Date:
29 November 2017 (online)

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Summary

By guiding initial warfarin dose, pharmacogenetic (PGx) algorithms may improve the safety of warfarin initiation. However, once international normalised ratio (INR) response is known, the contribution of PGx to dose refinements is uncertain. This study sought to develop and validate clinical and PGx dosing algorithms for warfarin dose refinement on days 6–11 after therapy initiation. An international sample of 2,022 patients at 13 medical centres on three continents provided clinical, INR, and genetic data at treatment days 6–11 to predict therapeutic warfarin dose. Independent derivation and retrospective validation samples were composed by randomly dividing the population (80%/20%). Prior warfarin doses were weighted by their expected effect on S-warfarin concentrations using an exponential-decay pharmacokinetic model. The INR divided by that “effective” dose constituted a treatment response index. Treatment response index, age, amiodarone, body surface area, warfarin indication, and target INR were associated with dose in the derivation sample. A clinical algorithm based on these factors was remarkably accurate: in the retrospective validation cohort its R2 was 61.2% and median absolute error (MAE) was 5.0 mg/week. Accuracy and safety was confirmed in a prospective cohort (N=43). CYP2C9 variants and VKORC1–1639 G→A were significant dose predictors in both the derivation and validation samples. In the retrospective validation cohort, the PGx algorithm had: R2= 69.1% (p<0.05 vs. clinical algorithm), MAE= 4.7 mg/week. In conclusion, a pharmacogenetic warfarin dose-refinement algorithm based on clinical, INR, and genetic factors can explain at least 69.1% of therapeutic warfarin dose variability after about one week of therapy.

Keywords

Warfarin - VKORC1 - CYP2C9 - pharmacogenetic

 

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