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中华介入放射学电子杂志 ›› 2021, Vol. 09 ›› Issue (03) : 326 -330. doi: 10.3877/cma.j.issn.2095-5782.2021.03.015

影像诊断

磨玻璃结节肺浸润性腺癌危险因素分析及列线图预测模型构建
黄瑞雪1,(), 陈秋容1, 林育彤1, 黄育鑫1   
  1. 1. 515300 广东普宁,普宁市人民医院影像科
  • 收稿日期:2021-01-24 出版日期:2021-08-25
  • 通信作者: 黄瑞雪
  • 基金资助:
    揭阳市科技计划项目(YLWS077)

Analysis of risk factors and construction of nomogram prediction model for ground glass nodules diagnosed pulmonary invasive adenocarcinoma

Ruixue Huang1,(), Qiurong Chen1, Yutong Lin1, Yuxin Huang1   

  1. 1. Department of Imaging, Puning People's Hospital, Guangdong Puning 515300, China
  • Received:2021-01-24 Published:2021-08-25
  • Corresponding author: Ruixue Huang
引用本文:

黄瑞雪, 陈秋容, 林育彤, 黄育鑫. 磨玻璃结节肺浸润性腺癌危险因素分析及列线图预测模型构建[J/OL]. 中华介入放射学电子杂志, 2021, 09(03): 326-330.

Ruixue Huang, Qiurong Chen, Yutong Lin, Yuxin Huang. Analysis of risk factors and construction of nomogram prediction model for ground glass nodules diagnosed pulmonary invasive adenocarcinoma[J/OL]. Chinese Journal of Interventional Radiology(Electronic Edition), 2021, 09(03): 326-330.

目的

探究磨玻璃结节(GGN)肺浸润性腺癌危险因素并建立列线图预测模型。

方法

本研究纳入2017年1月1日至2019年12月31日在我院就诊并收治的GGN患者,收集每位患者的基线资料和临床资料,使用Logistic回归分析GGN肺浸润性腺癌的独立危险因素。根据回归模型的结果,绘制列线图模型和受试者特征曲线(ROC)。

结果

本研究GGN肺腺癌的发生率为60.73%(116/191),两组患者在吸烟史、病灶最大直径、CT值、空泡征等方面差异具有统计学意义(P < 0.05)。基于筛选的独立危险因素,建立预测列线图模型。列线图ROC曲线结果显示,预测浸润性腺癌风险值的最佳临界点为0.521 4,曲线下面积(AUC)为0.784,敏感度和特异度分别为72.31%、83.64%。

结论

吸烟史、病灶最大直径、CT值、空泡征是区分浸润前病变和浸润性腺癌的独立危险因素,对其综合评估对于GGN肺浸润性腺癌的诊断具有较高的临床应用价值,值得进一步推广使用。

Objective

To explore the risk factors of ground glass nodules (GGN) diagnosed pulmonary invasive adenocarcinoma and establish the nomogram model.

Methods

This study included GGN patients who were treated in our hospital from January 1, 2017 to December 31, 2019. The baseline and clinical data of each patient were collected. Logistic regression was used to analyze the independent risk factors of GGN diagnosed lung invasive adenocarcinoma. According to the results of the regression model, nomogram and the receiver operating characteristic curve (ROC) were drawn.

Results

The incidence of GGN diagnosed lung adenocarcinoma in this study was 60.73%. Smoking history, maximum lesion diameter, CT value and vacuole sign were independent risk factors to distinguish preinvasive lesions from invasive adenocarcinoma. Based on the screened independent risk factors, a predictive line chart model was established. The results of the line chart ROC curve showed that the best critical point for predicting the risk value of invasive adenocarcinoma was 0.521 4, the area under the curve (AUC) was 0.784, and the sensitivity and specificity were 72.31% and 83.64%, respectively.

Conclusions

Smoking history, maximum diameter of focus, CT value and vacuole sign are independent risk factors to distinguish preinvasive lesions from invasive adenocarcinoma. The comprehensive evaluation of smoking history, maximum diameter, CT value and vacuole sign is of high clinical value in the diagnosis of pulmonary invasive adenocarcinoma and is worth further popularizing.

表1 两组患者基本临床信息和CT征象的比较(n,%)
表2 Logistic回归分析浸润性腺癌的危险因素
图1 列线图模型预测GGN浸润性腺癌的风险
图2 列线图模型的ROC曲线
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