Establishment of A Model Combining with Traditional Chinese Medicine Syndrome for Predicting the Risk of Disease Progression in Patients with Membranous Nephropathy
10.13359/j.cnki.gzxbtcm.2025.03.035
- VernacularTitle:结合中医证候的膜性肾病患者疾病进展风险预测模型的建立
- Author:
Xiaoyan HUANG
1
;
Xian LI
;
Kun ZOU
;
Xiaofan HONG
;
Yue CAO
;
Xing LIANG
;
Rongrong WANG
;
Ping LI
;
Daixin ZHAO
;
Wu ZHOU
;
Kun BAO
Author Information
1. 广州中医药大学第二附属医院,广东广州 510120;粤港澳中医药与免疫疾病研究联合实验室,广东广州 510120;广东省中医药防治难治性慢病重点实验室,广东广州 510120
- Keywords:
idiopathic membranous nephropathy;
traditional Chinese medicine syndrome;
machine learning methods;
monofactor analysis;
recursive feature elimination;
model for risk prediction of disease progression
- From:
Journal of Guangzhou University of Traditional Chinese Medicine
2025;42(3):774-781
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct a model combining with traditional Chinese medicine(TCM)syndrome for predicting the risk of disease progression in patients with idiopathic membranous nephropathy(IMN)by machine learning methods,thus to quantitatively evaluating the value of TCM syndrome in the prediction of the risk of disease progression in IMN.Methods Monofactor analysis,recursive feature elimination(RFE)and multivariate binary Logistic regression analysis were used to screen the independent related factors affecting the risk of disease progression of IMN,and then a risk prediction model was constructed.A total of 102 patients with IMN were randomly assigned to the training set and the test set in a ratio of 65∶35,and then the comparison was conducted in the performance indicators of accuracy,sensitivity,specificity,F1 value,and area under the receiver operating characteristic(ROC)area under the curve(AUC)of the risk prediction model with or without the inclusion of the TCM syndrome information.Results Before the inclusion of TCM syndrome information,12 clinical characteristic variables for patients with MN were obtained after monofactor analysis combined with RFE screening,and they were age,hemoglobin quantification,urinary occult blood,24-hour urine protein quantification,urine protein-creatinine ratio,estimated glomerular filtration rate(eGFR),creatinine,uric acid,alanine transaminase,anti-phospholipase A2 receptor antibody(PLA2R-Ab),total cholesterol,and low-density lipoprotein cholesterd.A risk cholesterol prediction model containing the above variables was constructed.The multivariate binary Logistic regression analysis showed that the differences of the clinical variables mentioned above between the training-set group and test-set group were statistically significant,and the risk prediction model presented good sensitivity and predictability.Monofactor analysis combined with RFE screening was performed again after the inclusion of TCM syndrome information,and then 14 variables were obtained,which included blood stasis syndrome and dampness obstruction syndrome.The sensitivity and specificity of the model with the inclusion of the TCM syndrome information were significantly improved when compared with those without the inclusion of TCM syndrome information.Conclusion The results of the study initially indicate that TCM syndrome can be used as an important supplementary variable for predicting the risk of disease progression in IMN,and will provide a reference for intelligent diagnosis through the integration of traditional Chinese and western medicine information,and will supply the guidance for the treatment of IMN with TCM.
