METHODS: The warfarin maintenance doses for 140 patients were predicted using the dosing tool and compared with the observed maintenance dose. The impact of genotype was assessed by predicting maintenance doses with prior parameter values known to be altered by genetic variability (eg, EC50 for VKORC1 genotype). The prior population was evaluated by fitting the published kinetic-pharmacodynamic model, which underpins the Bayesian tool, to the observed data using NONMEM and comparing the model parameter estimates with published values.
RESULTS: The Bayesian tool produced positively biased dose predictions in the new cohort of patients (mean prediction error [95% confidence interval]; 0.32 mg/d [0.14-0.5]). The bias was only observed in patients requiring ≥7 mg/d. The direction and magnitude of the observed bias was not influenced by genotype. The prior model provided a good fit to our data, which suggests that the bias was not caused by different prior and posterior populations.
CONCLUSIONS: Maintenance doses for patients requiring ≥7 mg/d were overpredicted. The bias was not due to the influence of genotype nor was it related to differences between the prior and posterior populations. There is a need for a more mechanistic model that captures warfarin dose-response relationship at higher warfarin doses.
MATERIALS AND METHODS: Five Malay patients receiving warfarin maintenance therapy were investigated for their CYP2C9*2, CYP2C9*3, and VKORC1-1639G>A genotypes and their vitamin K-dependent (VKD) clotting factor activities. The records of their daily warfarin doses and international normalized ratio (INR) 2 years prior to and after the measurement of VKD clotting factors activities were acquired. The mean warfarin doses were compared with predicted warfarin doses calculated from a genotypic-based dosing model developed for Asians.
RESULTS: A patient with the VKORC1-1639 GA genotype, who was supposed to have higher dose requirements, had a lower mean warfarin dose similar to those having the VKORC1-1639 AA genotype. This discrepancy may be due to the coadministration of celecoxib, which has the potential to decrease warfarins metabolism. Not all patients' predicted mean warfarin doses based on a previously developed dosing algorithm for Asians were similar to the actual mean warfarin dose, with the worst predicted dose being 54.34% higher than the required warfarin dose.
CONCLUSION: Multiple clinical factors can significantly change the actual required dose from the predicted dose from time to time. The additions of other dynamic variables, especially INR, VKD clotting factors, and concomitant drug use, into the dosing model are important in order to improve its accuracy.