A machine learning model for predicting abnormal liver function induced by a Chinese herbal medicine preparation(Zhengqing Fengtongning)in patients with rheumatoid arthritis based on real-world study  

作　　者：Ze Yu Fang Kou Ya Gao Fei Gao Chun-ming Lyu Hai Wei 

机构地区：[1]Institute of Interdisciplinary Integrative Medicine Research,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China [2]Department of Pharmacy,Fuwai Hospital,Chinese Academy of Medical Sciences,Beijing 100037,China [3]Beijing Medicinovo Technology Co.Ltd.,Beijing 100071,China [4]Experiment Center for Science and Technology,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China

出　　处：《Journal of Integrative Medicine》2025年第1期25-35,共11页结合医学学报(英文版)

基　　金：supported by the Budgeted Fund of Shanghai University of Traditional Chinese Medicine(Natural Science)(No.2021LK037);the Open Project of Qinghai Province Key Laboratory of Tibetan Medicine Pharmacology and Safety Evaluation(No.2021-ZY-03).

摘　　要：Objective Rheumatoid arthritis(RA)is a systemic autoimmune disease that affects the small joints of the whole body and degrades the patients’quality of life.Zhengqing Fengtongning(ZF)is a traditional Chinese medicine preparation used to treat RA.ZF may cause liver injury.In this study,we aimed to develop a prediction model for abnormal liver function caused by ZF.Methods This retrospective study collected data from multiple centers from January 2018 to April 2023.Abnormal liver function was set as the target variable according to the alanine transaminase(ALT)level.Features were screened through univariate analysis and sequential forward selection for modeling.Ten machine learning and deep learning models were compared to find the model that most effectively predicted liver function from the available data.Results This study included 1,913 eligible patients.The LightGBM model exhibited the best performance(accuracy=0.96)out of the 10 learning models.The predictive metrics of the LightGBM model were as follows:precision=0.99,recall rate=0.97,F1_score=0.98,area under the curve(AUC)=0.98,sensitivity=0.97 and specificity=0.85 for predicting ALT<40 U/L;precision=0.60,recall rate=0.83,F1_score=0.70,AUC=0.98,sensitivity=0.83 and specificity=0.97 for predicting 40≤ALT<80 U/L;and precision=0.83,recall rate=0.63,F1_score=0.71,AUC=0.97,sensitivity=0.63 and specificity=1.00 for predicting ALT≥80 U/L.ZF-induced abnormal liver function was found to be associated with high total cholesterol and triglyceride levels,the combination of TNF-αinhibitors,JAK inhibitors,methotrexate+nonsteroidal anti-inflammatory drugs,leflunomide,smoking,older age,and females in middle-age(45-65 years old).Conclusion This study developed a model for predicting ZF-induced abnormal liver function,which may help improve the safety of integrated administration of ZF and Western medicine.

关 键 词：Rheumatoid arthritis MEDICINE Chinese traditional Zhengqing Fengtongning Abnormal liver function Machine learning Real world 

分 类 号：R259[医药卫生—中西医结合] TP181[医药卫生—中医内科学]