Does a pharmacokinetic/pharmacodynamic model and Bayesian method accurately predict INR and individualize maintenance fluindione dosage in patients on oral anticoagulation?
A pharmacokinetic/pharmacodynamic model using a Bayesian method can accurately predict INR and help individualize fluindione dosage in patients requiring oral anticoagulation.
This study was designed to construct a pharmacokinetic/pharmacodynamic model describing the evolution of International Normalized Ratio (INR) under oral anticoagulation treatment by fluindione in patients and to develop a method for individualization of fluindione dosage. Three indirect response models describing the concentration-INR relationship were tested using a nonparametric estimation method. INR was modelled as a quantity being produced and eliminated. According to a log-likelihood ratio test, the evolution of INR was best modelled as an inhibition of its elimination by fluindione. The selected model was evaluated in 24 additional patients with INR measurements (after 2, 3, 4, 6, and 10 doses). Using a Bayesian method with data until day 4, INR was correctly predicted for days 6 and 10. The population characteristics of fluindione were estimated, pooling the two groups of patients. A Bayesian method for individualization of dosage regimen was developed, based on a risk function for INR at steady state. Prescription rules for fluindione were derived using this method retrospectively on the 73 patients in this study.
Comets et al. (Tue,) studied this question.