A New Algorithm Optimized for Initial Dose Settings of Vancomycin Using Machine Learning
A New Algorithm Optimized for Initial Dose Settings of Vancomycin Using Machine Learning
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DOI：
10.1248/bpb.b19-00729
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发表时间：
2020-01-01
影响因子：
2
通讯作者：
Sugawara, Mitsuru
中科院分区：
文献类型：
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作者：
Imai, Shungo;Takekuma, Yoh;Sugawara, Mitsuru
本研究旨在利用机器学习（ML）和决策树（DT）分析构建万古霉素（VCM）初始剂量设置的优化算法。在北海道大学医院接受静脉注射VCM并接受治疗药物监测（TDM）的患者入选。研究期为2011年11月至2019年3月。总共有654名患者被纳入研究。患者分为两组，训练组（2011年11月至2017年12月接受VCM的患者; n = 496）和测试组（2018年1月至2019年3月接受VCM的患者; n = 158）。对于训练组，进行分类和回归树算法的DT分析，以构建VCM初始剂量设置的算法（称为DT算法）。对于试验组，比较了采用DT算法和三种常规剂量设定方法达到VCM治疗范围（谷值= 10-15和10-20 mg/L）的比率，以进行模型评价。DT算法用于估计肾小球滤过率>= 50 mL/min和体重>= 40 kg的患者。因此，推荐的每日剂量范围为20.0 - 58.1 mg/kg。在模型评价中，与传统剂量设定方法相比，DT算法获得了达到VCM治疗范围的最高比率。因此，我们的DT算法可以应用于临床实践。此外，ML可用于设定药物剂量。
This study aimed to construct an optimal algorithm for initial dose settings of vancomycin (VCM) using machine learning (ML) with decision tree (DT) analysis. Patients who were administered intravenous VCM and underwent therapeutic drug monitoring (TDM) at the Hokkaido University Hospital were enrolled. The study period was November 2011 to March 2019. In total, 654 patients were included in the study. Patients were divided into two groups, training (patients who received VCM from November 2011 to December 2017; n = 496) and testing (patients who received VCM from January 2018 to March 2019; n = 158) groups. For the training group, DT analysis of the classification and regression tree algorithm was performed to construct an algorithm (called DT algorithm) for the initial dose settings of VCM. For the testing group, the rates of attaining the VCM therapeutic range (trough value = 10-15 and 10-20 mg/L) with the DT algorithm and three conventional dose-setting methods were compared for model evaluation. The DT algorithm was constructed to be used for patients with estimated glomerular filtration rate >= 50 mL/min and body weight >= 40 kg. As a result, the recommended daily doses ranged from 20.0 to 58.1 mg/kg. In model evaluation, the DT algorithm obtained the highest rates of attaining the VCM therapeutic range compared to conventional dose-setting methods. Therefore, our DT algorithm can be applied to clinical practice. In addition, ML is useful for setting drug doses.