COMPARING A MASS-BALANCE ALGORITHM WITH A BAYESIAN REGRESSION-ANALYSIS COMPUTER-PROGRAM FOR PREDICTING SERUM PHENYTOIN CONCENTRATIONS

The ability of a mass-balance algorithm to predict non-steady-state ph enytoin concentrations In neurosurgery patients was compared with that of Phenda, a computerized Bayesian regression analysis program. Fifty neurosurgery patients who had had two or more initial phenytoin serum concentrations measured at least 60 hours apart and at least 1 hour a fter any i.v. doses, with the second concentration being not more than twice and not less than half of the first, and who had had a third or final phenytoin measurement (for use in a prediction analysis) were e valuated. The patients' maximum rates of metabolism were calculated by using the two initial phenytoin concentrations and a mass-balance alg orithm, and the third phenytoin concentration was predicted. The patie nts' demographics and phenytoin dosages and concentrations were entere d into Phenda, which was used to predict the third phenytoin concentra tion. The ability of the two methods to predict the third concentratio n was evaluated by the method of Sheiner and Beal. Fifty observations from 48 patients were evaluated. The mass-balance algorithm had a posi tive prediction bias of 2.52 mg/L and a precision error of 5.08 mg/L, compared with 2.30 and 5.30, respectively, for Phenda. The difference in the results between the two methods was not significant. There was no significant difference between the mass-balance algorithm and Phend a in the ability to predict phenytoin concentrations.