Bayesian Forecasting of Serum Lithium Concentrations

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Abstract
Twelve pharmacokinetic methods of estimating lithium maintenance dosage requirements were compared in 21 patients with bipolar illness. Methods which were compared included the single- and multiple-point methods of Perry, 4 non-linear regression and 6 Bayesian methods. The REVOL algorithm was employed for converging on to estimates of clearance and apparent volume of distribution for the non-linear regression and Bayesian methods. Data analysis was based on an evaluation of prediction error as a measure of bias, and absolute prediction error as a measure of precision. In a direct comparison, there were no statistically significant differences in bias or precision between any of the methods.

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