在接受预防剂量治疗的患者中,对未结合的塞法林人口药动力学模型的外部验证
Toshiaki Komatsu1, Yuka Kawai2, Yoko Takayama3
1Department of Pharmacy, Kitasato University Hospital, 1-15-1 Kitazato, Minami-ku, Sagamihara 252-0375, Japan.
Biological & pharmaceutical bulletin
|May 21, 2025
概括
这项研究验证了未结合的塞法林的药理动力学模型. 科马松模型证明了在手术患者中未结合的塞法林度的最佳预测性能.
科学领域:
- 药理动力学和药理动力学
- 药物度监测 药物度监测
- 抗生素剂量优化 抗生素剂量优化
背景情况:
- 准确预测未结合的塞法林度对于优化治疗疗效和最大限度地减少毒性至关重要.
- 现有的无结合塞法林的人口药理动力学 (PPK) 模型需要外部验证来评估其现实世界的预测性能.
- 了解塞法林药理动学的个体间变异性对于个性化剂量策略至关重要.
研究的目的:
- 通过使用独立的临床数据集,评估已公布的未结合塞法佐林的种群药动力学模型的预测性能.
- 确定最准确和可靠的模型,用于预测手术患者中未结合的塞法林度.
- 为了评估选定的未结合的塞法林PPK模型的偏差和精度.
主要方法:
- 在PubMed上进行了系统的文献搜索,确定了相关的未结合的塞法林PPK模型.
- 外部验证使用了来自64名患者的临床数据,并采用了218个未结合的度样本.
- 使用预测错误 (PE) 和相对PE (RPE) 评估了预测偏差;使用平均绝对误差 (MAE),根平均平方误差 (RMSE) 和平均相对误差 (MRE) 评估了预测精度.
主要成果:
- 科马松模型表现出正偏差,但表现出最好的预测精度,MAE为4.71,RMSE为9.02,MRE为30.2%.
- 其他三种评估模型在预测未结合的塞法林度时表现出负偏差.
- 格模型显示了第二好的表现,MAE,RMSE和MRE值分别为11.5,16.1和107.2%.
结论:
- 与其他评估模型相比,Komatsu和Chung模型在未结合的塞法林度方面的预测性能优于其他评估模型.
- 这些经过验证的模型适用于预测手术患者群体中未结合的塞法林度概况.
- 进一步的研究可能会探索将这些模型集成到用于塞法林剂量的临床决策支持系统中.
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