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

Benjamin D. Horne; Petra A. Lenzini; Mia Wadelius; Andrea L. Jorgensen; Stephen E. Kimmel; Paul M. Ridker; Niclas Eriksson; Jeffrey L. Anderson; Munir Pirmohamed; Nita A. Limdi; Robert C. Pendleton; Gwendolyn A. McMillin; James K. Burmester; Daniel Kurnik; C. Michael Stein; Michael D. Caldwell; Charles S. Eby; Anders Rane; Jonatan D. Lindh; Jae-Gook Shin; Ho-Sook Kim; Pantep Angchaisuksiri; Robert J. Glynn; Kathryn E. Kronquist; John F. Carlquist; Gloria R. Grice; Robert L. Barrack; Juan Li; Brian F. Gage

doi:10.1160/TH11-06-0388

Thrombosis and Haemostasis, Table of Contents

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

¹Cardiovascular Department, Intermountain Medical Center, Salt Lake City, Utah, USA

²Division of Genetic Epidemiology, Department of Medicine, University of Utah, Salt Lake City, Utah, USA

,

Petra A. Lenzini

³Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA

,

Mia Wadelius

⁴Department of Medical Sciences, Clinical Pharmacology, Uppsala University, Uppsala, Sweden

,

Andrea L. Jorgensen

⁵Center for Medical Statistics and Health Evaluation, University of Liverpool, Liverpool, UK

,

Stephen E. Kimmel

⁶Departments of Medicine and of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA

,

Paul M. Ridker

⁷Center for Cardiovascular Disease Prevention, Harvard Medical School, Boston, Massachusetts, USA

⁸Division of Preventive Medicine, Harvard Medical School, Boston, Massachusetts, USA

⁹Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA

,

Niclas Eriksson

⁴Department of Medical Sciences, Clinical Pharmacology, Uppsala University, Uppsala, Sweden

¹⁰Uppsala Clinical Research Center – UCR, Uppsala University Hospital, Uppsala, Sweden

,

Jeffrey L. Anderson

¹Cardiovascular Department, Intermountain Medical Center, Salt Lake City, Utah, USA

¹¹Division of Cardiology, Department of Medicine, University of Utah, Salt Lake City, Utah, USA

,

Munir Pirmohamed

¹²Wolfson Center for Personalized Medicine, University of Liverpool, Liverpool, UK

,

Nita A. Limdi

¹³Departments of Neurology and Epidemiology, University of Alabama, Birmingham, Alabama, USA

,

Robert C. Pendleton

¹⁴Division of General Internal Medicine, Department of Medicine, University of Utah, Salt Lake City, Utah, USA

,

Gwendolyn A. McMillin

¹⁵Associated and Regional University Pathologists, Department of Pathology, University of Utah, Salt Lake City, Utah, USA

,

James K. Burmester

¹⁶Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA

,

Daniel Kurnik

¹⁷Division of Clinical Pharmacology, Department of Medicine and Pharmacology, Vanderbilt University, Nashville, Tennessee, USA

,

C. Michael Stein

¹⁷Division of Clinical Pharmacology, Department of Medicine and Pharmacology, Vanderbilt University, Nashville, Tennessee, USA

,

Michael D. Caldwell

¹⁸Department of Surgery, Marshfield Clinic, Marshfield, Wisconsin, USA

,

Charles S. Eby

³Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA

¹⁹Department of Pathology, Washington University in St. Louis, St. Louis, Missouri, USA

,

Anders Rane

²⁰Division of Clinical Pharmacology, Karolinska Institutet, Stockholm, Sweden

,

Jonatan D. Lindh

²⁰Division of Clinical Pharmacology, Karolinska Institutet, Stockholm, Sweden

,

Jae-Gook Shin

²¹Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea

,

Ho-Sook Kim

²¹Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea

,

Pantep Angchaisuksiri

²²Department of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand

,

Robert J. Glynn

⁷Center for Cardiovascular Disease Prevention, Harvard Medical School, Boston, Massachusetts, USA

⁸Division of Preventive Medicine, Harvard Medical School, Boston, Massachusetts, USA

,

Kathryn E. Kronquist

²³Molecular Diagnostic Laboratory, Kaiser Permanente, Denver, Colorado, USA

,

John F. Carlquist

¹Cardiovascular Department, Intermountain Medical Center, Salt Lake City, Utah, USA

¹¹Division of Cardiology, Department of Medicine, University of Utah, Salt Lake City, Utah, USA

,

Gloria R. Grice

²⁴Department of Pharmacy Practice, St. Louis College of Pharmacy, St. Louis, Missouri, USA

,

Robert L. Barrack

³Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA

²⁵Department of Orthopaedic Surgery, Washington University in St. Louis, St. Louis, Missouri, USA

,

Juan Li

³Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA

,

Brian F. Gage

³Department of Internal Medicine, Washington University in St. Louis, St. Louis, Missouri, USA

› Author Affiliations

Abstract

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

Full Text

References

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