VKORC1 , CYP2C9 and CYP4F2 Genetic-based Algorithm for Warfarin Dosing: An Italian Retrospective Study
A total of 371 patients under stable warfarin therapy were retrospectively selected to develop a pharmacogenetic algorithm to identify the individual maintenance dose. The variables that were entered into the algorithm were: VKORC1, CYP2C9 and CYP4F2 polymorphisms, body surface area and age. The per...
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          | Published in | Pharmacogenomics Vol. 12; no. 1; pp. 15 - 25 | 
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| Main Authors | , , , , , , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        England
          Future Medicine Ltd
    
        01.01.2011
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 1462-2416 1744-8042 1744-8042  | 
| DOI | 10.2217/pgs.10.162 | 
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| Summary: | A total of 371 patients under stable warfarin therapy were retrospectively selected to develop a pharmacogenetic algorithm to identify the individual maintenance dose.
The variables that were entered into the algorithm were: VKORC1, CYP2C9 and CYP4F2 polymorphisms, body surface area and age.
The percentage of cases whose predicted mean weekly warfarin dose was within 20% of the actual maintenance dose was 51.8% considering patients overall, and were 36.2, 66.2 and 55.4%, respectively, taking into account patients requiring low (≤25 mg/week), intermediate (25-45 mg/week) and high (≥45 mg/week) doses. The algorithm could correctly assign 73.8 and 63.2% of patients to the low- and high-dose regimens, respectively. We developed and validated a pharmacogenetic algorithm in a series of Italian patients, we then tested, in the same series of italian patients, the formulas of three published algorithms. These three algorithms were developed and validated by their authors in a series of patients different from our own. The performance of our algorithm in our patients series was slightly higher than that achieved when using the three other algorithms in our patients series.
The high predictive accuracy of low and high warfarin requirements of our algorithm warrants its application in prospective studies for clinical validation. | 
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23  | 
| ISSN: | 1462-2416 1744-8042 1744-8042  | 
| DOI: | 10.2217/pgs.10.162 |