基于年龄、NLR与MPV构建预测儿童紫癜性肾炎的Nomogram模型

    Construction of the Nomogram model for predicting purpura nephritis in children based on age, NLR and MPV

    • 摘要:
      目的: 基于年龄、中性粒细胞/淋巴细胞比值(NLR)与平均血小板体积(MPV)构建预测儿童紫癜性肾炎的Nomogram模型。
      方法: 回顾性收集332例HSP患儿的临床资料,采用R语言sample函数按7∶3比例随机抽样将患儿分为建模组和验证组,参照HSPN诊断标准,将2组患儿分别分为HSP组和HSPN组。建模组用于分析儿童HSPN的危险因素,采用R语言软件将筛选出的变量建立列线图预测模型。采用MedCalc软件绘制建模组和验证组的受试者工作特征(ROC)曲线,得出两者的AUC。绘制校准曲线、决策曲线评估列线图预测模型效能。
      结果: 多因素logistic回归分析发现年龄、NLR、MPV是HSPN发生的独立危险因素(OR = 1.204、1.716、1.426,P < 0.05~P < 0. 01);建模组及验证组C指数分别为0.84、0.86,ROC曲线下面积(AUC)分别为0.844(95%CI:0.791 ~ 0.888)、0.860(95%CI:0.776 ~ 0.921);校准曲线显示预测概率与实际概率之间具有良好的一致性,决策曲线分析表明列线图的临床应用价值较高。
      结论: 年龄、NLR、MPV与HSP肾脏损害相关,是发生肾脏损害的危险因素。构建列线图具有较高的预测准确性,可以较为可靠地预测过敏性紫癜患儿发生肾脏损害的风险,具有良好的临床应用价值。

       

      Abstract:
      Objective To construct a Nomogram model for predicting purpuric nephritis in children based on the age, neutrophil/lymphocyte ratio (NLR) and mean platelet volume (MPV).
      Methods The clinical data of 332 children with HSP were retrospectively collected, and the children were randomly divided into the modeling group and verification group using the R language sample function at a ratio of 7∶3. According to the diagnostic criteria of HSPN, the two groups were divided into the HSP group and HSPN group. The modeling group was used to analyze the risk factors of children's HSPN, and the variables selected by R language software were used to establish a nomogram prediction model. The receiver operating characteristic (ROC) curves of the modeling group and validation group were plotted by MedCalc software to obtain the AUC of two groups. The calibration curve and decision curve were drawn to evaluate the efficiency of the prediction model.
      Results The results of multivariate logistic regression analysis showed that the age, NLR and MPV were the independent risk factors of HSPN (OR = 1.204, 1.716, 1.426, P < 0.05 to P < 0.01). The C index of the modeling group and verification group were 0.84 and 0.86, respectively. The area under ROC curve (AUC) of the modeling group and verification group were 0.844 (95%CI: 0.791 ~ 0.888) and 0.860 (95%CI: 0.776 ~ 0.921), respectively. The results of calibration curve showed that there was a good agreement between the predicted probability and actual probability, and the results of decision curve analysis showed that the nomogram had a high value in clinical application.
      Conclusions The age, NLR and MPV are associated with the renal damage in HSP, and risk factors of renal damage. The Nomogram has high predictive accuracy, and can more reliably predict the risk of kidney damage in children with anaphylactoid purpura, which has good clinical application value.

       

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