Huang Huiping, Liu Qingxia, Zhang Xiaohan, Xie Helin, Liu Maobai, Chaphekar Nupur, Wu Xuemei
Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, China.
School of Pharmacy, Fujian Medical University, Fuzhou, China.
Front Pharmacol. 2022 Jul 7;13:835037. doi: 10.3389/fphar.2022.835037. eCollection 2022.
Busulfan (BU) is a bi-functional DNA-alkylating agent used in patients undergoing hematopoietic stem cell transplantation (HSCT). Over the last decades, several population pharmacokinetic (pop PK) models of BU have been established, but external evaluation has not been performed for almost all models. The purpose of the study was to evaluate the predictive performance of published pop PK models of intravenous BU in adults using an independent dataset from Chinese HSCT patients, and to identify the best model to guide personalized dosing. The external evaluation methods included prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. In prediction-based diagnostics, the relative prediction error (PE%) was calculated by comparing the population predicted concentration (PRED) with the observations. Simulation-based diagnostics included the prediction- and variability-corrected visual predictive check (pvcVPC) and the normalized prediction distribution error (NPDE). Bayesian forecasting was executed by giving prior one to four observations. The factors influencing the model predictability, including the impact of structural models, were assessed. A total of 440 concentrations (110 patients) were obtained for analysis. Based on prediction-based diagnostics and Bayesian forecasting, preferable predictive performance was observed in the model developed by Huang et al. The median PE% was -1.44% which was closest to 0, and the maximum F of 57.27% and F of 72.73% were achieved. Bayesian forecasting demonstrated that prior concentrations remarkably improved the prediction precision and accuracy of all models, even with only one prior concentration. This is the first study to comprehensively evaluate published pop PK models of BU. The model built by Huang et al. had satisfactory predictive performance, which can be used to guide individualized dosage adjustment of BU in Chinese patients.
白消安(BU)是一种双功能DNA烷化剂,用于接受造血干细胞移植(HSCT)的患者。在过去几十年中,已经建立了多个白消安的群体药代动力学(pop PK)模型,但几乎所有模型都未进行外部评估。本研究的目的是使用来自中国HSCT患者的独立数据集评估已发表的成人静脉注射白消安pop PK模型的预测性能,并确定指导个体化给药的最佳模型。外部评估方法包括基于预测的诊断、基于模拟的诊断和贝叶斯预测。在基于预测的诊断中,通过将群体预测浓度(PRED)与观察值进行比较来计算相对预测误差(PE%)。基于模拟的诊断包括预测和变异性校正的视觉预测检查(pvcVPC)和标准化预测分布误差(NPDE)。通过给出先验的一到四个观察值来执行贝叶斯预测。评估了影响模型可预测性的因素,包括结构模型的影响。共获得440个浓度(110例患者)用于分析。基于基于预测的诊断和贝叶斯预测,在Huang等人开发的模型中观察到了较好的预测性能。PE%的中位数为-1.44%,最接近0,最大F值为57.27%,F值为72.73%。贝叶斯预测表明,即使只有一个先验浓度,先验浓度也显著提高了所有模型的预测精度和准确性。这是第一项全面评估已发表的白消安pop PK模型的研究。Huang等人建立的模型具有令人满意的预测性能,可用于指导中国患者白消安的个体化剂量调整。