Establishment of A Prediction Model for the Efficacy of Glucocorticoid Combined with Cyclophosphamide in the Treatment of Idiopathic Membra-nous Nephropathy Based on Supervised Learning Algorithm
Establishment of A Prediction Model for the Efficacy of Glucocorticoid Combined with Cyclophosphamide in the Treatment of Idiopathic Membra-nous Nephropathy Based on Supervised Learning Algorithm
Objective To establish a supervised learning algorithm-based prediction model for the efficacy of Glu-cocorticoid(GC)combined with Cyclophosphamide in the treatment of idiopathic membranous nephropathy(IMN).Methods Patients diagnosed with IMN from July 1,2014 to June 30,2023 were selected and treated with GC combined with Cyclo-phosphamide for≥6 months,and relevant clinical data were collected.Nine supervised learning models were constructed using Python software,and the predictive performance of each model was evaluated by using the area under the receiver operat-ing characteristic(ROC)curve(AUC).Indicators related to efficacy were screened,and prediction tools were constructed according to the results.Results A total of 122 patients were included,of which57(46.7%)had a complete response,39(32.0%)had a partial response,and 26(21.3%)had no response.When all 136 clinical measures were included,light-weight gradient boosting machine(LGBM)had the highest AUC(0.965)among the nine supervised learning models.The re-sults of characteristic screening showed that the decrease rate of 24 h urinary protein quantification(24 h UTP)and the in-crease rate of serum albumin at 3 months after initiation of treatment had the strongest correlation with the efficacy.After re-modeling with only the above two features included,the AUC of LGBM was still the highest(0.978).Therefore,this study fi-nally constructed an online prediction tool based on LGBM,and the website is www.imnpredict.online.Conclusion The prediction model of the efficacy of GC combined with Cyclophosphamide on IMN based on supervised learning algorithm sug-gests that 24 h UTP and serum albumin change rate at 3 months after the initiation of treatment are the main factors to predict the efficacy in the patients.The model and online tool can predict the efficacy in the treatment of early IMN and provide a ref-erence for individualized treatment of patients.
关键词
特发性膜性肾病/糖皮质激素/环磷酰胺/疗效/监督学习/预测模型
Key words
Idiopathic membranous nephropathy/Glucocorticoid/Cyclophosphamide/Efficacy/Supervised learn-ing/Prediction model
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