RESUMEN
Objective Constructing a risk prediction model of IgA nephropathy proteinuria treated by traditional Chinese medicine based on random survival forest model,Screening prognostic risk factors of IgA nephropathy proteinuria.Methods Collecting retrospectively clinical data of 129 cases diagnosed with IgA nephropathy,randomly divided them into training set(60%)and test set(40%).The risk prediction model of IgA nephropathy proteinuria was constructed in the training set with the random survival forest model,and the prognostic risk factors were screened by VIMP method.The accuracy of risk prediction model was validated in the test set with time-dependent ROC curve(tdROC).Results According to the result of VIMP,the prognostic risk factors for IgA nephropathy proteinuria are in the order of eGFR,hypertension,traditional Chinese medicine,24 hUPRO>1 g,genomo sclerosis ratio,Lee grading,fat,hyperlipidemia,hypertrophymia,hyparmane ledmia,Anemia,age and gender.The eGFR was negatively and non-linearly associated with the risk rate of developing persistent proteinuria.Glomerulosclerosis ratio greater than 0.3 is approximately linearly and positively associated with the risk rate of persistent proteinuria.Conclusion Random survival forest model has good predictive performance in the risk prediction model of IgA nephropathy proteinuria treated by traditional Chinese medicine.This risk model can determine the result of IgA nephropathy treated by traditional Chinese medicine,and which is helpful for clinical follow-up monitoring and formulation of individualized treatment plans.