Akimoto Hayato, Nagashima Takuya, Minagawa Kimino, Hayakawa Takashi, Takahashi Yasuo, Asai Satoshi
Division of Pharmacology, Department of Biomedical Sciences, Nihon University School of Medicine, Tokyo, Japan.
Division of Genomic Epidemiology and Clinical Trials, Clinical Trials Research Center, Nihon University School of Medicine, Tokyo, Japan.
Front Pharmacol. 2022 Jul 6;13:910205. doi: 10.3389/fphar.2022.910205. eCollection 2022.
Drug-induced liver injury (DILI) is a common adverse drug reaction, with abnormal elevation of serum alanine aminotransferase (ALT). Several clinical studies have investigated whether a combination of two drugs alters the reporting frequency of DILI using traditional statistical methods such as multiple logistic regression (MLR), but this model may over-fit the data. This study aimed to detect a synergistic interaction between two drugs on the risk of abnormal elevation of serum ALT in Japanese adult patients using three machine-learning algorithms: MLR, logistic least absolute shrinkage and selection operator (LASSO) regression, and extreme gradient boosting (XGBoost) algorithms. A total of 58,413 patients were extracted from Nihon University School of Medicine's Clinical Data Warehouse and assigned to case ( = 4,152) and control ( = 54,261) groups. The MLR model over-fitted a training set. In the logistic LASSO regression model, three combinations showed relative excess risk due to interaction (RERI) for abnormal elevation of serum ALT: diclofenac and famotidine (RERI 2.427, 95% bootstrap confidence interval 1.226-11.003), acetaminophen and ambroxol (0.540, 0.087-4.625), and aspirin and cilostazol (0.188, 0.135-3.010). Moreover, diclofenac (adjusted odds ratio 1.319, 95% bootstrap confidence interval 1.189-2.821) and famotidine (1.643, 1.332-2.071) individually affected the risk of abnormal elevation of serum ALT. In the XGBoost model, not only the individual effects of diclofenac (feature importance 0.004) and famotidine (0.016), but also the interaction term (0.004) was included in important predictors. Although further study is needed, the combination of diclofenac and famotidine appears to increase the risk of abnormal elevation of serum ALT in the real world.
药物性肝损伤（DILI）是一种常见的药物不良反应，表现为血清丙氨酸氨基转移酶（ALT）异常升高。多项临床研究使用多元逻辑回归（MLR）等传统统计方法，调查了两种药物联合使用是否会改变DILI的报告频率，但该模型可能会过度拟合数据。本研究旨在使用三种机器学习算法——MLR、逻辑最小绝对收缩和选择算子（LASSO）回归以及极端梯度提升（XGBoost）算法，检测两种药物对日本成年患者血清ALT异常升高风险的协同相互作用。从日本大学医学院临床数据仓库中提取了总共58413名患者，并将其分为病例组（n = 4152）和对照组（n = 54261）。MLR模型对训练集过度拟合。在逻辑LASSO回归模型中，三种组合显示出因相互作用导致血清ALT异常升高的相对超额风险（RERI）：双氯芬酸和法莫替丁（RERI 2.427，95%自抽样置信区间1.226 - 11.003）、对乙酰氨基酚和氨溴索（0.540，0.087 - 4.625）以及阿司匹林和西洛他唑（0.188，0.135 - 3.010）。此外，双氯芬酸（调整比值比1.319，95%自抽样置信区间1.189 - 2.821）和法莫替丁（1.643，1.332 - 2.071）分别影响血清ALT异常升高的风险。在XGBoost模型中，重要预测因子不仅包括双氯芬酸（特征重要性0.004）和法莫替丁（0.016）的个体效应，还包括相互作用项（0.004）。尽管需要进一步研究，但在现实世界中，双氯芬酸和法莫替丁联合使用似乎会增加血清ALT异常升高的风险。
