特发性膜性肾病患者Nomogram预测模型的构建

Construction of Predictive Model of Nomogram in Patients with Idiopathic Membranous Nephropathy

摘要

目的 通过Nomogram列线图建立一个用于预测特发性膜性肾病患者预后的模型。方法 选择2018年1月~2020年12月在承德医学院附属医院首次住院并行肾穿刺活检术确诊为特发性膜性肾病（IMN）的初诊初治患者195例,并进行24个月的随访。根据随访结束时是否出现肾终点事件,将患者分为2组,分别为肾脏终点组和未达到肾脏终点组。将纳入单因素Logistic分析中P<0.2的影响因素进行多因素Logistic回归分析,按照赤池信息准则（AIC）选取最优Logistic回归模型构建IMN患者预后不良的预测模型。结果 用于预测IMN预后不良预测模型的预测因子包括：年龄、平均动脉压、肾穿刺前病程、白蛋白、血肌酐。IMN患者的受试者工作特性曲线下面积（AUROC）为0.729。校准曲线的Hosmer-Lemeshow检验的统计值为1.44（P=0.49）。决策曲线（DCA）显示IMN的预测概率值在0.17至0.44之间时本模型临床适用。结论 本研究构建了用于预测IMN患者预后不良的预测模型,该预测模型的预测能力、校准能力和临床净获益良好,有助于预测IMN患者的预后。

Abstract

Objective To establish a predictive model for predicting the prognosis of patients with idiopathic membranous nephropathy (IMN) by Nomogram diagram. Methods The newly diagnosed patients with IMN diagnosed by renal biopsy in The Affiliated Hospital of Chengde Medical University from January 2018 to December 2020 were selected and followed up for 24 months. The patients were divided into two groups according to whether the patients had renal endpoint events at the end of follow-up. Patients who did not have terminal events at the end of follow-up were enrolled in the group that did not reach the renal endpoint. The influencing factors with P<0.2 in univariate Logistic analysis were analyzed by multivariate Logistic regression analysis, and the optimal Logistic regression model was selected according to Akaike information criterion (AIC) to construct the predictive model of poor prognosis of IMN patients. The discrimination ability of the model was verified and evaluated by the area under the receiver operating characteristic (AUROC), and the calibration curve and decision curve analysis (DCA) were drawn to evaluate the calibration, clinical net income and practicability of the model. Results The predictive factors used to predict the poor prognosis of IMN include age, mean arterial pressure(MAP), duration of disease before renal puncture, albumin and serum creatinine. The AUROC of patients with IMN was 0.729. The statistical value of the Hosmer-Lemeshow test of the calibration curve is 1.44 (P=0.49). DCA curve shows that this model is clinically applicable when the predictive probability of IMN is between 0.17 and 0.44. Conclusion In this study, a predictive model for predicting the poor prognosis of IMN patients was constructed. The predictive model has good predictive ability, calibration ability, and clinical net benefit, it can be applied to predict the prognosis of IMN patients.

关键词

特发性膜性肾病 / 肾脏终点 / 预后 / 列线图

Key words

idiopathic membranous nephropathy / renal end point / prognosis / nomograms

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基金资助

2022年度河北省医学科学研究课题计划（20220409）