Estimation of the warfarin dose with clinical and pharmacogenetic data

Abstract

Background: Genetic variability among patients plays an important role in determining the dose of warfarin that should be used when oral anticoagulation is initiated, but practical methods of using genetic information have not been evaluated in a diverse and large population. We developed and used an algorithm for estimating the appropriate warfarin dose that is based on both clinical and genetic data from a broad population base.

Methods: Clinical and genetic data from 4043 patients were used to create a dose algorithm that was based on clinical variables only and an algorithm in which genetic information was added to the clinical variables. In a validation cohort of 1009 subjects, we evaluated the potential clinical value of each algorithm by calculating the percentage of patients whose predicted dose of warfarin was within 20% of the actual stable therapeutic dose; we also evaluated other clinically relevant indicators.

Results: In the validation cohort, the pharmacogenetic algorithm accurately identified larger proportions of patients who required 21 mg of warfarin or less per week and of those who required 49 mg or more per week to achieve the target international normalized ratio than did the clinical algorithm (49.4% vs. 33.3%, P<0.001, among patients requiring < or = 21 mg per week; and 24.8% vs. 7.2%, P<0.001, among those requiring > or = 49 mg per week).

Conclusions: The use of a pharmacogenetic algorithm for estimating the appropriate initial dose of warfarin produces recommendations that are significantly closer to the required stable therapeutic dose than those derived from a clinical algorithm or a fixed-dose approach. The greatest benefits were observed in the 46.2% of the population that required 21 mg or less of warfarin per week or 49 mg or more per week for therapeutic anticoagulation.

2009 Massachusetts Medical Society

Figures

Figure 1. Comparisons of Warfarin Doses Predicted According to the Clinical Algorithm and the Pharmacogenetic Algorithm

Panel A shows the comparisons based on genotype and on use or nonuse of amiodarone. This example of a 50-year-old non-Asian, nonblack patient who is 1.75 m tall and weighs 80 kg shows that genotype can markedly change the recommended dose from more than 45 mg per week to less than 10 mg per week when all other factors are the same. Panel B shows the comparison based on race and genotype. This example of a 50-year-old patient who is 1.75 m tall and weighs 80 kg shows that racial differences in the estimated dose become insignificant when genetic information is added to the model and that the clinical algorithm, as compared with the pharmacogenetic algorithm, often produces an average value that may substantially overestimate or underestimate the dose.

Figure 2. Percentage of Patients with Dose Estimates within 20% of the Actual Dose, as Derived with the Use of a Pharmacogenetic Algorithm, a Clinical Algorithm, and a Fixed-Dose Approach

The dose estimates are shown according to three actual-dose groups: low-dose (≤21 mg per week), intermediate-dose (>21 to