The Creating an Optimal Warfarin Nomogram (CROWN) Study

Todd S. Perlstein; Samuel Z. Goldhaber; Kerrie Nelson; Victoria Joshi; T. Vance Morgan; Lawrence J. Lesko; Joo-Yeon Lee; Jogarao Gobburu; David Schoenfeld; Raju Kucherlapati; Mason W. Freeman; Mark A. Creager

doi:10.1160/TH11-08-0568

Thrombosis and Haemostasis, Table of Contents

Thromb Haemost 2012; 107(01): 59-68
DOI: 10.1160/TH11-08-0568

Blood Coagulation, Fibrinolysis and Cellular Haemostasis

Schattauer GmbH

The Creating an Optimal Warfarin Nomogram (CROWN) Study

Authors

Todd S. Perlstein

¹Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
Samuel Z. Goldhaber

¹Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
Kerrie Nelson

²Biostatistics Center, Massachusetts General Hospital, Boston, Massachusetts, USA
Victoria Joshi

⁵Departments of Pathology, Massachusetts General Hospital and Brigham and Women’s Hospital, Partners Center for Personalized Genetic Medicine, Boston, Massachusetts, USA
T. Vance Morgan

⁶Center for Personalized Genetic Medicine, Harvard Medical School, Boston, Massachusetts, USA
Lawrence J. Lesko

⁷Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA
Joo-Yeon Lee

⁷Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA
Jogarao Gobburu

⁷Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA
David Schoenfeld

²Biostatistics Center, Massachusetts General Hospital, Boston, Massachusetts, USA

³Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA
Raju Kucherlapati

⁶Center for Personalized Genetic Medicine, Harvard Medical School, Boston, Massachusetts, USA
Mason W. Freeman

⁴Lipid Metabolism Unit and Endocrine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
Mark A. Creager

¹Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA

Abstract

Summary

A significant proportion of warfarin dose variability is explained by variation in the genotypes of the cytochrome P450 CYP2C9 and the vitamin K epoxide reductase complex, VKORC1, enzymes that influence warfarin metabolism and sensitivity, respectively. We sought to develop an optimal pharmacogenetic warfarin dosing algorithm that incorporated clinical and genetic information. We enroled patients initiating warfarin therapy. Genotyping was performed of the VKORC1, –1639G>A, the CYP2C9*2, 430C>T, and the CYP2C9*3, 1075C>A genotypes. The initial warfarin dosing algorithm (Algorithm A) was based upon established clinical practice and published warfarin pharmacogenetic information. Subsequent dosing algorithms (Algorithms B and Algorithm C) were derived from pharmacokinetic / pharmacodynamic (PK/PD) modelling of warfarin dose, international normalised ratio (INR), clinical and genetic factors from patients treated by the preceding algorithm(s). The primary outcome was the time in the therapeutic range, considered an INR of 1.8 to 3.2. A total of 344 subjects are included in the study analyses. The mean percentage time within the therapeutic range for each subject increased progressively from Algorithm A to Algorithm C from 58.9 (22.0), to 59.7 (23.0), to 65.8 (16.9) percent (p = 0.04). Improvement also occurred in most secondary endpoints, which included the per-patient percentage of INRs outside of the therapeutic range (p = 0.004), the time to the first therapeutic INR (p = 0.07), and the time to achieve stable therapeutic anticoagulation (p < 0.001). In conclusion, warfarin pharmacogenetic dosing can be optimised in real time utilising observed PK/PD information in an adaptive fashion.

Clinical Trial Registration: ClinicalTrials.gov (NCT00401414)

Keywords

Pharmacogenetics - warfarin - clinical trial

Full Text

References

References
1 Gallagher AM, Setakis E, Plumb JM. et al. Risks of stroke and mortality associated with suboptimal anticoagulation in atrial fibrillation patients. Thromb Haemost 2011; 106: 968-977.
2 Gage BF, Eby C, Johnson JA. et al. Use of pharmacogenetic and clinical factors to predict the therapeutic dose of warfarin. Clin Pharmacol Ther 2008; 84: 326-331.
3 Gage BF, Eby C, Milligan PE. et al. Use of pharmacogenetics and clinical factors to predict the maintenance dose of warfarin. Thromb Haemost 2004; 91: 87-94.
4 Klein TE, Altman RB, Eriksson N. et al. Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J Med 2009; 360: 753-764.
5 Schwarz UI, Ritchie MD, Bradford Y. et al. Genetic determinants of response to warfarin during initial anticoagulation. N Engl J Med 2008; 358: 999-1008.
6 Woodcock J, Lesko LJ. Pharmacogenetics--tailoring treatment for the outliers. N Engl J Med 2009; 360: 811-813.
7 Steward DJ, Haining RL, Henne KR. et al. Genetic association between sensitivity to warfarin and expression of CYP2C9*3. Pharmacogenetics 1997; 07: 361-367.
8 Joffe HV, Xu R, Johnson FB. et al. Warfarin dosing and cytochrome P450 2C9 polymorphisms. Thromb Haemost 2004; 91: 1123-1128.
9 Meckley LM, Wittkowsky AK, Rieder MJ. et al. An analysis of the relative effects of VKORC1 and CYP2C9 variants on anticoagulation related outcomes in warfarin-treated patients. Thromb Haemost 2008; 100: 229-239.
10 Voora D, Eby C, Linder MW. et al. Prospective dosing of warfarin based on cytochrome P-450 2C9 genotype. Thromb Haemost 2005; 93: 700-705.
11 Rost S, Fregin A, Ivaskevicius V. et al. Mutations in VKORC1 cause warfarin resistance and multiple coagulation factor deficiency type 2. Nature 2004; 427: 537-541.
12 Rieder MJ, Reiner AP, Gage BF. et al. Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med 2005; 352: 2285-2293.
13 Harrington DJ, Underwood S, Morse C. et al. Pharmacodynamic resistance to warfarin associated with a Val66Met substitution in vitamin K epoxide reductase complex subunit 1. Thromb Haemost 2005; 93: 23-26.
14 Caraco Y, Blotnick S, Muszkat M. CYP2C9 genotype-guided warfarin prescribing enhances the efficacy and safety of anticoagulation: a prospective randomized controlled study. Clin Pharmacol Ther 2008; 83: 460-470.
15 Anderson JL, Horne BD, Stevens SM. et al. Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anticoagulation. Circulation 2007; 116: 2563-2570.
16 Huang SW, Chen HS, Wang XQ. et al. Validation of VKORC1 and CYP2C9 genotypes on interindividual warfarin maintenance dose: a prospective study in Chinese patients. Pharmacogenet Genomics 2009; 19: 226-234.
17 Wang Y, Bhattaram AV, Jadhav PR. et al. Leveraging prior quantitative knowledge to guide drug development decisions and regulatory science recommendations: impact of FDA pharmacometrics during 2004–2006. J Clin Pharmacol 2008; 48: 146-156.
18 Bhattaram VA, Bonapace C, Chilukuri DM. et al. Impact of pharmacometric reviews on new drug approval and labeling decisions--a survey of 31 new drug applications submitted between 2005 and 2006. Clin Pharmacol Ther 2007; 81: 213-221.
19 Bhattaram VA, Booth BP, Ramchandani RP. et al. Impact of pharmacometrics on drug approval and labeling decisions: a survey of 42 new drug applications. AAPS J 2005; 07: E503-512.
20 Joshi VA, Duffy E, Funke BH. et al. Platform evaluation for rapid genotyping of CYP2C9 and VKORC1 alleles. Per Med 2009; 06: 449-457.
21 Hamberg AK, Dahl ML, Barban M. et al. A PK-PD model for predicting the impact of age, CYP2C9, and VKORC1 genotype on individualization of warfarin therapy. Clin Pharmacol Ther 2007; 81: 529-538.
22 Rosendaal FR, Cannegieter SC, van der Meer FJ. et al. A method to determine the optimal intensity of oral anticoagulant therapy. Thromb Haemost 1993; 69: 236-239.
23 Antman EM. Hirudin in acute myocardial infarction. Thrombolysis and Thrombin Inhibition in Myocardial Infarction (TIMI) 9B trial. Circulation 1996; 94: 911-921.
24 Hillman MA, Wilke RA, Yale SH. et al. A prospective, randomized pilot trial of model-based warfarin dose initiation using CYP2C9 genotype and clinical data. Clin Med Res 2005; 03: 137-145.
25 Epstein RS, Moyer TP, Aubert RE. et al. Warfarin genotyping reduces hospitalization rates results from the MM-WES (Medco-Mayo Warfarin Effectiveness study). J Am Coll Cardiol 2010; 55: 2804-2812.
26 Wadelius M, Chen LY, Lindh JD. et al. The largest prospective warfarin-treated cohort supports genetic forecasting. Blood 2009; 113: 784-792.
27 Salinger DH, Shen DD, Thummel K. et al. Pharmacogenomic trial design: use of a PK/PD model to explore warfarin dosing interventions through clinical trial simulation. Pharmacogenet Genomics 2009; 19: 965-971.
28 Reynolds KK, Valdes Jr. R, Hartung BR. et al. Individualizing warfarin therapy. Person Med 2007; 04: 11-31.
29 Ansell J, Hollowell J, Pengo V. et al. Descriptive analysis of the process and quality of oral anticoagulation management in real-life practice in patients with chronic non-valvular atrial fibrillation: the international study of anticoagulation management (ISAM). J Thromb Thrombolysis 2007; 23: 83-91.
30 Yuen E, Gueorguieva I, Wise S. et al. Ethnic differences in the population pharmacokinetics and pharmacodynamics of warfarin. J Pharmacokinet Pharmacodyn 2010; 37: 3-24.
31 Wu AH, Wang P, Smith A. et al. Dosing algorithm for warfarin using CYP2C9 and VKORC1 genotyping from a multi-ethnic population: comparison with other equations. Pharmacogenomics 2008; 09: 169-178.
32 You JH, Zuo Z, Lo CM. et al. Any effect of CYP2C9 variants on warfarin clearance in Chinese patients?. Thromb Haemost 2007; 97: 866-868.
33 Geisen C, Watzka M, Sittinger K. et al. VKORC1 haplotypes and their impact on the inter-individual and inter-ethnical variability of oral anticoagulation. Thromb Haemost 2005; 94: 773-779.
34 King CR, Deych E, Milligan P. et al. Gamma-glutamyl carboxylase and its influence on warfarin dose. Thromb Haemost 2010; 104: 750-754.
35 Vecsler M, Loebstein R, Almog S. et al. Combined genetic profiles of components and regulators of the vitamin K-dependent gamma-carboxylation system affect individual sensitivity to warfarin. Thromb Haemost 2006; 95: 205-211.
36 Chan E, McLachlan A, O'Reilly R. et al. Stereochemical aspects of warfarin drug interactions: use of a combined pharmacokinetic-pharmacodynamic model. Clin Pharmacol Ther 1994; 56: 286-294.
37 Adcock DM, Duff S. Enhanced standardization of the International Normalized Ratio through the use of plasma calibrants: a concise review. Blood Coagul Fibrinolysis 2000; 11: 583-590.

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