Validation and Comparison of Pharmacogenetics-Based Warfarin Dosing Algorithms for Application of Pharmacogenetic Testing Nitin Roper, Barry Storer,

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Presentation transcript:

Validation and Comparison of Pharmacogenetics-Based Warfarin Dosing Algorithms for Application of Pharmacogenetic Testing Nitin Roper, Barry Storer, Robert Bona, Min Fang The Journal of Molecular Diagnostics Volume 12, Issue 3, Pages 283-291 (May 2010) DOI: 10.2353/jmoldx.2010.090110 Copyright © 2010 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 1 Characteristics of the study population. A: Distribution histogram of the therapeutic maintenance dose of warfarin among study subjects. The x axis represents the warfarin dose in mg/week. The y axis represents the number of subjects for the respective dosing range. Four subjects (weekly dose of 75 to 95 mg) are the main cause for deviation from a normal distribution. All four subjects are wild-type. B: A box-and-whisker plot of the therapeutic maintenance dose for each genotype category for the study subjects. CYP2C9 genotypes are according to standard nomenclature. The VKORC1 genotypes are based on haplotype nomenclature: BB represents wild-type; AB, heterozygote; AA, homozygote. The Journal of Molecular Diagnostics 2010 12, 283-291DOI: (10.2353/jmoldx.2010.090110) Copyright © 2010 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 2 Development of a new regression algorithm for predicting warfarin dosing (UCHC model). A: Average stable maintenance doses in mg/week based on the number of genotype variants. Number of patients in each group: wild-type (0 variant), 35 (28%); 1 variant, 41 (33%); 2 variants, 36 (29%); 3 variants, 11 (8.8%); and 4 variants, 2 (1.6%). Dose differences across groups are highly significant (P < 0.001). B: Correlation analysis of the actual versus predicted doses using the regression algorithm shown in Table 2. Each patient is represented by a dot. The solid line is the linear regression, and the dotted line is the line of perfect prediction. The Journal of Molecular Diagnostics 2010 12, 283-291DOI: (10.2353/jmoldx.2010.090110) Copyright © 2010 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 3 Comparison of four published algorithms with the UCHC model for determining warfarin dosing. Shown are the scatterplots of the actual versus predicted doses by each of the algorithms for 974 patients in the IWPC. Solid lines are the least squares regression, and dotted lines represent the line of perfect prediction. The Journal of Molecular Diagnostics 2010 12, 283-291DOI: (10.2353/jmoldx.2010.090110) Copyright © 2010 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 4 Comparison of all genotype-based dosing models based on the percentage of patients with predicted doses within 20% of actual. The x axis shows three actual dose groups: low (less than 21 mg/week), intermediate (21 to 49 mg/week), and high (greater than 49 mg/week). The y axis depicts the percentage of patients within each dose-group whose predicted dose is ideal (within 20% of actual). A: Comparison in the UCHC dataset. B: Comparison in the IWPC validation dataset. The Journal of Molecular Diagnostics 2010 12, 283-291DOI: (10.2353/jmoldx.2010.090110) Copyright © 2010 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 5 Sensitivity of dosing algorithms based on a sliding window of ±10 mg of actual doses. A: Comparison in the UCHC dataset. B: Comparison in the IWPC validation dataset. The Journal of Molecular Diagnostics 2010 12, 283-291DOI: (10.2353/jmoldx.2010.090110) Copyright © 2010 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions