构建并验证nomogram模型预测ⅠA期肺腺癌肺泡间转移

张龙富; 刘洁; 倪筝; 路新源; 胡斌; 汪灏; 冯明祥; 张勇

doi:10.19401/j.cnki.1007-3639.2022.12.009

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构建并验证nomogram模型预测ⅠA期肺腺癌肺泡间转移

论著 | 更新时间：2025-12-31

- 构建并验证nomogram模型预测ⅠA期肺腺癌肺泡间转移
- Development and validation of a nomogram for predicting spread through air spaces in stage ⅠA lung adenocarcinoma
- 中国癌症杂志 2022年32卷第12期页码：1210-1217
- 作者机构：
  
  1. 上海市徐汇区中心医院呼吸与危重症医学科，上海 200031
  2. 复旦大学附属中山医院呼吸与危重症医学科，上海 200032
  3. 复旦大学附属中山医院病理科，上海 200032
  4. 复旦大学公共卫生学院公共卫生安全教育部重点实验室，上海 200032
  5. 复旦大学附属中山医院胸外科，上海 200032
- 作者简介：
  
  [ "张龙富（ORCID: 0000-0002-6657-2664），硕士，主治医师。" ]
  张勇（ORCID: 0000-0003-1631-7048），博士，副主任医师。
- 基金信息：
  
  上海市医学重点专科建设计划(ZK2019C14);徐汇区医学科研项目(SHXH202113)
- DOI：10.19401/j.cnki.1007-3639.2022.12.009
  中图分类号： R734.2
- 收稿：2022-09-10，
  
  修回：2022-11-05，
  
  纸质出版：2022-12-30
- 稿件说明：
移动端阅览
张龙富, 刘洁, 倪筝, 等. 构建并验证nomogram模型预测ⅠA期肺腺癌肺泡间转移[J]. 中国癌症杂志, 2022,32(12):1210-1217.

Longfu ZHANG, Jie LIU, Zheng NI, et al. Development and validation of a nomogram for predicting spread through air spaces in stage ⅠA lung adenocarcinoma[J]. China Oncology, 2022, 32(12): 1210-1217.
张龙富, 刘洁, 倪筝, 等. 构建并验证nomogram模型预测ⅠA期肺腺癌肺泡间转移[J]. 中国癌症杂志, 2022,32(12):1210-1217. DOI： 10.19401/j.cnki.1007-3639.2022.12.009.

Longfu ZHANG, Jie LIU, Zheng NI, et al. Development and validation of a nomogram for predicting spread through air spaces in stage ⅠA lung adenocarcinoma[J]. China Oncology, 2022, 32(12): 1210-1217. DOI： 10.19401/j.cnki.1007-3639.2022.12.009.

摘要

背景和目的：

肺泡间转移（spread through air spaces，STAS）是早期肺腺癌的不良预后因素，尤其是楔形切除的患者，术前预测STAS有助于选择更佳的手术方式。本研究旨在建立并验证基于术前临床和影像学特征的列线图（nomogram）来预测ⅠA期肺腺癌的STAS。

方法：

回顾性分析2017年1月—2018年12月在复旦大学附属中山医院接受手术治疗的595例ⅠA期肺腺癌患者，通过4%的甲醛溶液固定石蜡包埋组织切片评估STAS结

果。基于术前临床资料和胸部计算机体层成像（computed tomography，CT），4种临床特征和11种影像学特征纳入分析。通过logistic回归筛选临床和影像学特征中预测STAS的独立预测因素并构建nomogram模型。通过一致性指数（concordance index，C-index）、受试者工作特征（receiver operating characteristic，ROC）曲线的曲线下面积（area under curve，AUC）、校准图来评估模型的效能。

结果：

在595例ⅠA期肺腺癌患者中，STAS阳性为87例（14.6%）。单因素及多因素logistic回归结果显示分叶征（OR = 8.156，95% CI：1.021 ~ 65.099）、毛刺征（OR = 5.258，95% CI：2.506 ~ 11.032）和实性成分占比（consolidation tumor ratio，CTR）（0.50

CTR≤0.75，OR = 16.955，95% CI：3.579 ~ 80.309；0.75

CTR≤1.00，OR = 20.793，95% CI：4.383 ~ 98.636）是STAS阳性的独立预测因素。基于这些预测因素建立的nomogram模型，对于STAS有较好的预测效能；C-index为0.901，AUC为0.897，且校准曲线拟合良好。

结论：

本研究建立并验证了预测ⅠA 期肺腺癌STAS的nomogram模型。本模型操作简单，有较好的预测效能，有利于术前选择合理的手术方式。

Abstract

Background and purpose:

Spread through air spaces (STAS) is a poor prognostic factor for early lung adenocarcinoma

especially in patients with wedge resection. Preoperative prediction of STAS is helpful to select a better surgical treatment. This study aimed to develop and validate a nomogram based on preoperative clinical and computed tomography (CT) characteristics to predict STAS in stage ⅠA lung adenocarcinoma.

Methods:

A total of 595 patients with stage ⅠA lung adenocarcinoma who underwent surgical treatment in Zhongshan Hospital Fudan University from January 2017 to December 2018 were retrospectively analyzed. The results of STAS were evaluated by paraffin embedded tissues fixed with 4% formaldehyde solution. Based on preoperative clinical data and chest CT

4 clinical characteristics and 11 CT characteristics were analyzed. The independent predictors of STAS in clinical and CT characteristics were identified by logistic regression analysis and then used to build a nomogram. Concordance index (C-index)

area under the curve (AUC) of receiver operating characteristic (ROC) and calibration plots were used to evaluate the performance of the model.

Results:

Among the 595 stage ⅠA lung adenocarcinoma pati

ents

87 patients (14.6%) were STAS positive. Univariate and multivariate logistic regression analyses showed that lobulation (OR=8.156

95% CI: 1.021-65.099)

spiculation (OR=5.258

95% CI: 2.506-11.032) and consolidation tumor ratio (CTR) (0.50

CTR≤0.75; OR=16.955

95% CI: 3.579-80.309; 0.75

CTR≤1.00; OR=20.793

95% CI: 4.383-98.636) were independent predictors of STAS positivity. The nomogram based on these predictors achieved good predictive performance for STAS with a C-index of 0.901

an AUC of 0.897 and a well-fitted calibration curve.

Conclusion:

This study developed and validated a nomogram for predicting STAS in stage ⅠA lung adenocarcinoma. This model is simple to operate and has good predictive performance

which is conducive to the selection of reasonable surgical methods before operation.

关键词

Keywords

references

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