Why the study?
Does a Bayesian algorithm based on clotting factor activity accurately predict maintenance warfarin dosage regimens in healthy volunteers?
Does a Bayesian algorithm based on clotting factor activity accurately predict maintenance warfarin dosage regimens in healthy volunteers?
A Bayesian algorithm using non-steady-state factor VII response measurements can rapidly predict warfarin maintenance dosing requirements without needing drug concentration measurements.
May support simplified warfarin dosing prediction in volunteers without concentrations; hypothesis-generating, requires patient validation.
A Bayesian algorithm, employing a population pharmacokinetic-pharmacodynamic model, for the effective and rapid prediction of warfarin maintenance dosing requirements was developed. The algorithm was evaluated prospectively in five healthy volunteers who were given a 15-mg single dose of racemic warfarin. Based on previous population pharmacokinetic and pharmacodynamic parameters and factor VII response measurements taken during the first 48 hours, dosage regimens to achieve a subtherapeutic degree of anticoagulation (50% of normal) were determined. Three factor VII response measurements were sufficient to determine dosing requirements in the five volunteers. The advantage of the algorithm is that it does not require warfarin concentration measurements and uses non-steady-state data.
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Pitsiu et al. (2003) studied this question.
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