title: Influence of Genotype on Warfarin Maintenance Dose Predictions Produced Using a Bayesian Dose Individualization Tool.
abstract: A previously established Bayesian dosing tool for warfarin was found to produce biased maintenance dose predictions. In this study, we aimed (1) to determine whether the biased warfarin dose predictions previously observed could be replicated in a new cohort of patients from 2 different clinical settings, (2) to explore the influence of CYP2C9 and VKORC1 genotype on predictive performance of the Bayesian dosing tool, and (3) to determine whether the previous population used to develop the kinetic-pharmacodynamic model underpinning the Bayesian dosing tool was sufficiently different from the test (posterior) population to account for the biased dose predictions.
  
  
  
  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.
  
  
  
  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.
  
  
  
  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.
authors.affiliation: *School of Pharmacy, University of Otago, Dunedin, New Zealand;†Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Malaysia;‡Department of Surgical Sciences, University of Otago, Dunedin, New Zealand;§Department of Haematology, Glasgow Royal Infirmary, Glasgow, Scotland;¶Department of Pharmacy, Glasgow Royal Infirmary, Glasgow, Scotland; and‖Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, Scotland.
authors.forename: Shamin M
authors.initials: SM
authors.lastname: Saffian
authors.forename: Stephen B
authors.initials: SB
authors.lastname: Duffull
authors.forename: Rebecca L
authors.initials: RL
authors.lastname: Roberts
authors.forename: Robert C
authors.initials: RC
authors.lastname: Tait
authors.forename: Leanne
authors.initials: L
authors.lastname: Black
authors.forename: Kirstin A
authors.initials: KA
authors.lastname: Lund
authors.forename: Alison H
authors.initials: AH
authors.lastname: Thomson
authors.forename: Daniel F B
authors.initials: DF
authors.lastname: Wright
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000925:Anticoagulants / Q000008:administration & dosage*; D001499:Bayes Theorem; D065729:Cytochrome P-450 CYP2C9 / Q000235:genetics; D005838:Genotype; D006801:Humans; D007700:Kinetics; D008297:Male; D008875:Middle Aged; D064417:Vitamin K Epoxide Reductases / Q000235:genetics; D014859:Warfarin / Q000008:administration & dosage*; D055815:Young Adult
chemical_list: D000925:Anticoagulants; D014859:Warfarin; D065729:Cytochrome P-450 CYP2C9; C578523:VKORC1 protein, human; D064417:Vitamin K Epoxide Reductases