Imai Shungo, Kashiwagi Hitoshi, Sato Yuki, Miyai Takayuki, Sugawara Mitsuru, Takekuma Yoh
Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan.
Graduate School of Life Science, Hokkaido University, Sapporo, Japan.
Br J Clin Pharmacol. 2022 Mar;88(3):1211-1222. doi: 10.1111/bcp.15063. Epub 2021 Sep 28.
Musculoskeletal toxicity is a typical side effect of daptomycin (DAP). However, the risk factors have not been well established. Here, we aimed to identify independent factors affecting DAP-induced musculoskeletal toxicity using a combination of machine learning and conventional statistical methods.
A population-based, retrospective, observational cohort study was conducted using the Japanese electronic medical record database. Patients who received DAP between October 2011 and December 2020 were enrolled. Two definitions of musculoskeletal toxicity were employed: (1) elevation of creatine phosphokinase (CPK) value more than twice from baseline and >200 IU/L, and (2) >1000 IU/L. First, multiple logistic regression analyses (a conventional statistical method) were performed to identify independent factors affecting CPK elevation. Then, decision tree analyses, a machine learning method, were performed to detect combinations of factors that change CPK elevation risk.
Of the 2970 patients who received DAP, 706 were included. Elevation of CPK values >200 IU/L and >1000 IU/L occurred in 83 (11.8%) and 17 (2.41%) patients, respectively. In multiple logistic regression analysis, baseline CPK value and concomitant use of hydrophobic statins were commonly extracted as independent factors affecting each CPK elevation, but concomitant use of hydrophilic statins was not. In decision tree analysis, patients who received hydrophobic statins and had high baseline CPK values were classified into the high-risk group.
Our novel approach revealed new risk factors for CPK elevation. Our findings suggest that high-risk patients require frequent CPK monitoring.
肌肉骨骼毒性是达托霉素（DAP）的典型副作用。然而，其风险因素尚未完全明确。在此，我们旨在结合机器学习和传统统计方法，确定影响DAP诱导的肌肉骨骼毒性的独立因素。
利用日本电子病历数据库进行了一项基于人群的回顾性观察队列研究。纳入2011年10月至2020年12月期间接受DAP治疗的患者。采用了两种肌肉骨骼毒性的定义：（1）肌酸磷酸激酶（CPK）值较基线升高两倍以上且>200 IU/L，以及（2）>1000 IU/L。首先，进行多因素逻辑回归分析（一种传统统计方法）以确定影响CPK升高的独立因素。然后，进行决策树分析（一种机器学习方法）以检测改变CPK升高风险的因素组合。
在2970例接受DAP治疗的患者中，706例被纳入研究。CPK值>200 IU/L和>1000 IU/L升高的患者分别有83例（11.8%）和17例（2.41%）。在多因素逻辑回归分析中，基线CPK值和同时使用疏水他汀类药物通常被提取为影响每次CPK升高的独立因素，但同时使用亲水他汀类药物则不是。在决策树分析中，接受疏水他汀类药物且基线CPK值高的患者被分类为高风险组。
我们的新方法揭示了CPK升高的新风险因素。我们的研究结果表明，高风险患者需要频繁监测CPK。
