目的 基于随机生存森林算法构建中医药干预的IgA肾病蛋白尿风险预测模型,筛选IgA肾病蛋白尿预后风险因素.方法 回顾性收集129例确诊为IgA肾病的临床资料,按照60%、40%的比例随机划分成训练集与测试集,在训练集中运用随机生存森林算法构建中医药干预的IgA肾病蛋白尿风险预测模型,利用VIMP法筛选预后风险因素,并在测试集中采用time-dependent ROC曲线(tdROC)对模型预测性能进行验证.结果 据VIMP值表明IgA肾病蛋白尿预后风险因素依次为eGFR、高血压、中医药干预、24 hUPRO>1 g、肾小球硬化比例、Lee分级、肥胖、血脂异常、高尿酸血症、低蛋白血症、贫血、年龄、性别.eGFR与发生持续蛋白尿风险率呈非线性负相关.肾小球硬化比例>0.3时与持续蛋白尿风险率呈近似线性正相关.结论该中医药干预的IgA肾病蛋白尿风险预测模型具有一定的预测性能,可判断经中医药干预的IgA肾病患者蛋白尿预后,有助于临床随访监测及制定个体化治疗方案.
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.