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

被引:0
|
作者
Yu, Ze [1 ]
Kou, Fang [1 ]
Gao, Ya [2 ]
Gao, Fei [3 ]
Lyu, Chun-ming [4 ]
Wei, Hai [1 ]
机构
[1] Shanghai Univ Tradit Chinese Med, Inst Interdisciplinary Integrat Med Res, Shanghai 201203, Peoples R China
[2] Fuwai Hosp, Chinese Acad Med Sci, Dept Pharm, Beijing 100037, Peoples R China
[3] Beijing Medicinovo Technol Co Ltd, Beijing 100071, Peoples R China
[4] Shanghai Univ Tradit Chinese Med, Expt Ctr Sci & Technol, Shanghai 201203, Peoples R China
来源
JOURNAL OF INTEGRATIVE MEDICINE-JIM | 2025年 / 23卷 / 01期
关键词
Rheumatoid arthritis; Medicine; Chinese traditional; Zhengqing Fengtongning; Abnormal liver function; Machine learning; Real world; SINOMENINE; RISK;
D O I
10.1016/j.joim.2024.12.001
中图分类号
R [医药、卫生];
学科分类号
10 ;
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-alpha inhibitors, 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. Please cite this article as: Yu Z, Kou F, Gao Y, Lyu CM, Gao F, Wei H. 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. J Integr Med. 2025; 23(1): 25-35. (c) 2024 Shanghai Yueyang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:25 / 35
页数:11
相关论文
共 50 条
  • [41] Pharmacoeconomic analysis of biological disease modifying antirheumatic drugs in patients with rheumatoid arthritis based on real-world data from the IORRA observational cohort study in Japan
    Tanaka, Eiichi
    Inoue, Eisuke
    Yamaguchi, Rei
    Shimizu, Yoko
    Kobayashi, Akiko
    Sugimoto, Naoki
    Hoshi, Daisuke
    Shidara, Kumi
    Sato, Eri
    Seto, Yohei
    Nakajima, Ayako
    Momohara, Shigeki
    Taniguchi, Atsuo
    Yamanaka, Hisashi
    MODERN RHEUMATOLOGY, 2017, 27 (02) : 227 - 236
  • [42] Nomogram Models for Predicting Risk and Prognosis of Newly Diagnosed Ovarian Cancer Patients with Liver Metastases - A Large Population-Based Real-World Study
    Hou, Gui-Min
    Jiang, Chuang
    Du, Jin-peng
    Liu, Chang
    Chen, Xiang-zheng
    Yuan, Ke-fei
    Wu, Hong
    Zeng, Yong
    JOURNAL OF CANCER, 2021, 12 (24): : 7255 - 7265
  • [43] Influence of Traditional Chinese Medicine on Medical Adherence and Outcome in Estrogen Receptor (+) Breast Cancer Patients in Taiwan: A Real-World Population-Based Cohort Study
    Chan, Pi-Wei
    Chiu, Jen-Hwey
    Huang, Nicole
    Chen, Chyong-Mei
    Yu, Hung
    Liu, Chun-Yu
    Hsu, Chung-Hua
    PHYTOMEDICINE, 2021, 80
  • [44] Connecting the use of innovative treatments and glucocorticoids with the multidisciplinary evaluation through rule-based natural-language processing: a real-world study on patients with rheumatoid arthritis, psoriatic arthritis, and psoriasis
    Motta, Francesca
    Morandini, Pierandrea
    Maffia, Fiore
    Vecellio, Matteo
    Tonutti, Antonio
    De Santis, Maria
    Costanzo, Antonio
    Puggioni, Francesca
    Savevski, Victor
    Selmi, Carlo
    FRONTIERS IN MEDICINE, 2023, 10
  • [45] Trend in prescription and treatment retention of molecular-targeted drugs in 121,131 Japanese patients with rheumatoid arthritis: A population-based real-world study
    Takabayashi, Katsuhiko
    Ando, Fumihiko
    Ikeda, Kei
    Fujita, Shinsuke
    Nakajima, Hiroshi
    Hanaoka, Hideki
    Suzuki, Takahiro
    MODERN RHEUMATOLOGY, 2022, 32 (05) : 857 - 865
  • [46] Integration of Chinese Herbal Medicine into Routine Care Was Related to Lower Risk of Chronic Kidney Disease in Patients with Rheumatoid Arthritis: A Population-Based Nested Case-Control Study in Taiwan
    Liao, Hou-Hsun
    Chen, Hsiao-Tien
    Livneh, Hanoch
    Huang, Hua-Lung
    Lai, Ning-Sheng
    Lu, Ming-Chi
    Yeh, Chia-Chou
    Tsai, Tzung-Yi
    JOURNAL OF MULTIDISCIPLINARY HEALTHCARE, 2023, 16 : 1191 - 1201
  • [47] Effects of Chinese Medicine on the Survival of AIDS Patients Administered Second-Line ART in Rural Areas of China: A Retrospective Cohort Study Based on Real-World Data
    Jin, Yantao
    Zhang, Miao
    Ma, Yanmin
    Sang, Feng
    Li, Pengyu
    Yang, Chunling
    Wang, Dongli
    Guo, Huijun
    Liu, Zhibin
    Xu, Qianlei
    EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE, 2022, 2022
  • [48] Real-World Use of Tofacitinib Compared with Tumor Necrosis Factor Inhibitors in a Cohort of 211 Patients with Rheumatoid Arthritis: Data from a Drug-Based Registry Study in Taiwan
    Hsieh, Song-Chou
    Chen, Yi-Hsing
    Chen, Wei-Sheng
    Tsai, Wen-Chan
    Hu, Jui-Chieh
    Chen, Hsiang-Cheng
    Mardekian, Jack
    Lai, Chacun
    ARTHRITIS & RHEUMATOLOGY, 2018, 70
  • [49] DISCREPANCY BETWEEN THE EFFICACY OF BIOLOGICAL DMARDS BASED ON RANDOMIZED CONTROLLED TRIALS AND THE EFFICACY OF BIOLOGICAL DMARDS IN REAL-WORLD SETTINGS IN PATIENTS WITH RHEUMATOID ARTHRITIS: A STUDY USING THE IORRA COHORT
    Sugano, Eri
    Tanaka, Eiichi
    Inoue, Eisuke
    Abe, Mai
    Kawano, Mika
    Saka, Kumiko
    Sugitani, Naohiro
    Shimizu, Yoko
    Ochiai, Moeko
    Yamaguchi, Rei
    Sugimoto, Naoki
    Ikari, Katsunori
    Nakajima, Ayako
    Taniguchi, Atsuo
    Yamanaka, Hisashi
    ANNALS OF THE RHEUMATIC DISEASES, 2019, 78 : 1045 - 1045
  • [50] Machine learning-based decision support model for selecting intra-arterial therapies for unresectable hepatocellular carcinoma: A national real-world evidence-based study
    An, Chao
    Wei, Ran
    Liu, Wendao
    Fu, Yan
    Gong, Xiaolong
    Li, Chengzhi
    Yao, Wang
    Zuo, Mengxuan
    Li, Wang
    Li, Yansheng
    Wu, Fatian
    Liu, Kejia
    Yan, Dong
    Wu, Peihong
    Han, Jianjun
    BRITISH JOURNAL OF CANCER, 2024, : 832 - 842