Background: This study reviewed all published valproic acid (VPA) population pharmacokinetic (PPK) models in adult patients and assessed them using external validation methods to determine predictive performance.
Methods: Thirteen published PPK models (labeled with letters A to M) not restricted to children were identified in PubMed, Embase, and Web of Science databases. They were evaluated in a sample totaling 411 serum concentrations from 146 adult inpatients diagnosed with bipolar disorder in a Chinese hospital. Serum concentrations of VPA were analyzed by validated ultra-performance liquid chromatography-tandem mass spectrometry. Performance was assessed by four tests (prediction-based diagnostics, visual predictive checks, normalized prediction distribution error, and Bayesian forecasting).
Results: Models K and L, developed in large samples of Chinese and Thai patients, showed good performance in our Chinese dataset. Models H and J demonstrated good performance in 2 and 3 of the 4 tests, respectively. Another seven models exhibited intermediate performance. The models with the worst performance, F and M, could not be improved by Bayesian forecasting.
Conclusion: In our validation study, the most important factors contributing to good performance were absence of children, Asian ethnicity, one-compartment models, and inclusion of body weight and VPA dose in previously published models.
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http://dx.doi.org/10.1080/17512433.2022.2075849 | DOI Listing |
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