The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
Expert Rev Clin Pharmacol. 2022 May;15(5):621-635. doi: 10.1080/17512433.2022.2075849. Epub 2022 Jun 2.
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.
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).
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.
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.
本研究回顾了所有已发表的用于成年患者的丙戊酸(VPA)群体药代动力学(PPK)模型,并使用外部验证方法对其进行评估,以确定其预测性能。
在 PubMed、Embase 和 Web of Science 数据库中确定了 13 个未限制在儿童中的已发表的 PPK 模型(用字母 A 到 M 标记)。它们在一个中国医院的 146 名被诊断为双相情感障碍的成年住院患者的 411 个血清浓度样本中进行了评估。使用经验证的超高效液相色谱-串联质谱法分析 VPA 的血清浓度。通过四个测试(基于预测的诊断、视觉预测检查、归一化预测分布误差和贝叶斯预测)评估性能。
在我们的中国数据集,由来自中国和泰国的大样本患者开发的模型 K 和 L 表现出良好的性能。模型 H 和 J 在 4 个测试中的 2 个和 3 个中表现出良好的性能。另外 7 个模型表现出中等性能。表现最差的模型 F 和 M 无法通过贝叶斯预测得到改善。
在我们的验证研究中,对良好性能贡献最大的因素是没有儿童、亚洲人种、单室模型,以及在之前发表的模型中包含体重和 VPA 剂量。