Evaluation of a Bayesian pharmacokinetic program for phenytoin concentration predictions in outpatient population

The present work evaluates the performances of a Bayesian program (PKS) for phenytoin concentration predictions in an outpatient population. The retrospective study involved 19 epileptic adults receiving oral phenytoin. The program was used to predict estimated serum concentrations from 0, 1, 2 or 3 feedback concentrations. Measurements of prediction bias (ME) decreased as soon as one steady-state concentration (Css) was used for estimations. Precision (MAE) was significantly improved with I Css and was even better and stable with 2 and 3 Css. Likewise, RMSE (composite of bias and precision) regularly decreased when the number of Css used increased. On a clinical way, 12% of the estimations were unacceptable (prediction error > 5 mg/l) with 1 Css and less than 3% with 2 or 3 Css. This number of rejected estimations increased to 45% when no feedback concentration was used. Besides, the program was able to predict important rises of serum levels in spite of relative low increase of the dose when 1 Css at least was known. Thus, the phenytoin dosing program has acceptable performances when at least 1 Css is known, and represents a potential tool to assist the clinician in the particular condition of outpatient population.