Establishment and validation prediction models of benign and malignant predictors for solitary pulmonary nodules

Zhu Xiaoqian; Zheng Li; Jiang Depeng

doi:10.13406/j.cnki.cyxb.003100

您当前的位置：

首页 >

文章列表页 >

Establishment and validation prediction models of benign and malignant predictors for solitary pulmonary nodules

Clinical research | 更新时间：2022-11-09

- Establishment and validation prediction models of benign and malignant predictors for solitary pulmonary nodules
- Journal of Shanxi Agricultural Sciences Vol. 47, Issue 10, Pages: 1193-1198(2022)
- 作者机构：
  
  重庆医科大学附属第二医院呼吸与危重症医学科，重庆　400010
- 作者简介：
- 基金信息：
- DOI：10.13406/j.cnki.cyxb.003100
  CLC： R563.9
- Published：28 October 2022，
  
  Received：11 November 2021，
扫描看全文
Zhu Xiaoqian, Zheng Li, Jiang Depeng. Establishment and validation prediction models of benign and malignant predictors for solitary pulmonary nodules. [J]. Journal of Shanxi Agricultural Sciences 47(10):1193-1198(2022)
DOI：

Zhu Xiaoqian, Zheng Li, Jiang Depeng. Establishment and validation prediction models of benign and malignant predictors for solitary pulmonary nodules. [J]. Journal of Shanxi Agricultural Sciences 47(10):1193-1198(2022) DOI： 10.13406/j.cnki.cyxb.003100.

摘要

目的：

探讨良恶性孤立性肺结节（solitary puhnonary nodule，SPN）的预测因子并建立预测模型，验证模型效能，并与经典模型进行诊断效能比较，以期提高早期肺癌的非侵入性诊断准确率。

方法：

选取2014年1月至2021年1月经重庆医科大学附属第二医院诊治的522例SPN患者，分为试验组（432例）和验证组（90例），回顾性分析其临床及CT影像学特征，筛选出恶性SPN的独立预测因子，并建立临床预测模型。将验证组资料代入模型进行验证，并与Mayo模型及北大模型进行诊断效能比较，绘制受试者工作特征（receiver operating characteristic，ROC）曲线。

结果：

二元logistic分析显示，上叶、毛刺征、分叶征、血管集束征、边界不清及结节最大径是判断良恶性结节的独立危险因子，建立的预测模型为

/（1+

），

=-3.742+（0.185×结节最大径）+（1.423×毛刺征）+（1.143×分叶征）+（3.783×血管集束征）+（2.526×边界不清）+（0.730×上叶）。本研究模型 ROC曲线下面积（0.875）高于Mayo模型（0.776）及北大模型（0.779）（

0.05），提示本研究模型诊断效能可能优于Mayo模型及北大模型。

结论：

上叶、毛刺征、分叶征、血管集束征、边界不清、结节最大径是预测良恶性SPN的独立预测因子，本预测模型诊断效能可能优于国内外经典模型，对早期肺癌的诊断有更大的借鉴意义。

Abstract

Objective:

To analyze the prdictors of solitary pulmonary nodules（SPN） and establish a mathematical prediction model to verify the accuracy of the model and compare the diagnostic efficiency with the classical models，in order to improve the accuracy of non-invasive diagnosis of early lung cancer.

Methods:

A total of 522 SPN patients treated by The Second Affiliated Hospital of Chongqing Medical University from January 2014 to January 2021 were selected and divided into case group（432 cases） and validation group（90 cases），and their clinical and CT imaging features were retrospectively analyzed to screen out independent predictors of malignant SPN and establish a clinical prediction model. The validation group data were inserted into the model for verification，the diagnostic efficacy was compared with the Mayo model and Peking University model，and the receiver operating characteristic（ROC） curve was drawn.

Results:

Binary Logistic analysis showed that upper lobe，spiculation，lobulation，vascular aggregation sign，unclear boundary and the maximum diameter of nodules were independent risk factors for benign and malignant SPN. The established prediction model was

/（1+

），

=-3.742+（0.185×the maximum diameter of nodule）+（1.423×spiculation）+（1.143×lobulation）+（3.783×vascular aggregation sign）+（2.526×unclear boundary）+（0.730×upperlobe）. The area under ROC curve（AUC） of our model（0.875） was significantly higher than that of the Mayo model（0.776） and Peking University model（0.779）（

0.05）. It was suggested that the diagnostic efficiency of this model might be better than that of Mayo model and Peking University model.

Conclusion:

Upper lobe，spiculation，lobulation，vascular aggregation sign，unclear boundary and the maximum diameter of nodules are independent risk factors for benign and malignant SPN，and the diagnostic efficiency of our prediction model might be better than that of Mayo model and Peking University model，which is of great significance for the diagnosis of early lung cancer.

关键词

孤立性肺结节肺癌logistic回归分析预测模型模型验证

Keywords

solitary pulmonary nodulelung cancerlogistic regression analysisprediction modelmodel validation

references

查看原文

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Effect of Glycyrrhiza uralensis Fisch. endophytes combined with cisplatin on proliferation and apoptosis of A549 cells

Correlation analysis and prediction model construction of CT signs and infiltration degree of pure ground-glass nodule lung adenocarcinoma

Development and internal validation of a prognostic model of metachronous dual primary lung cancer based on SEER database

Clinical analysis of dermatomyositis/polymyositis complicated with lung disease

Related Author

Zhang Shanglong

Zhang Nan

Lian Xiaolong

Ye Liqiao

Ma Quhuan

Deng Yi

Hu Yu

Du Ming

Related Institution

College of Pharmacy，Gansu University of Chinese Medicine

Department of Cardiothoracic Surgery，The First Affiliated Hospital of Chongqing Medical University

Shandong Provincial Hospital, Shandong University

Department of Thoracic Surgery, The Second Hospital of Shandong University

College of Water Resource and Hydropower, Sichuan Univ.

⁰