To develop a warfarin-dosing algorithm that could be combined with pharmacogenomic and demographic factors, and to evaluate its effectiveness in a randomized prospective controlled clinical trial.Methods
A pharmacogenetics-based dosing model was derived using retrospective data from 266 Chinese patients and multiple linear regression analysis. To prospectively validate this model, 156 patients with an operation of heart valve replacement were enrolled and randomly assigned to the group of pharmacogenetics-guided or traditional dosing for warfarin therapy. All patients were followed up for 50 days after initiation of warfarin therapy. The log-rank test was compared with the time-to-event (Kaplan–Meier) curves. Cox proportional hazards-regression model was used to assess the hazard ratio of the time to reach stable dose.Results
The linear regression model derived from the pharmacogenomic model correlated with 54.1% of warfarin dosing variance. The final multiple linear regression model included age, body surface area, VKORC1, and CYP2C9 genotype. The study showed that the hazard ratio for the time to reach stable dose was 1.932 for the traditional dosing group versus the model-based group and a close and highly significant relationship was observed to exist between the predicted and the actual warfarin dose (R2=0.454).Conclusion
A pharmacogenetics-based dosing algorithm has been developed for improvement in the time to reach the stable dosing of warfarin. This model may be useful in helping the clinicians to prescribe warfarin with greater safety and efficiency.