Nomogram based on clinical characteristics and radiological features for the preoperative prediction of spread through air spaces in patients with clinical stage IA non-small cell lung cancer: a multicenter study

作者：Yun Wang, Deng Lyu, Di Zhang, Lei Hu, Junhong Wu, Wenting Tu, Yi Xiao, Li Fan, Shiyuan Liu · 发表于：Diagnostic and Interventional Radiology · 年份：2023 · DOI：10.4274/dir.2023.232404 · 被引用次数：5 · 研究领域：Lung Cancer Diagnosis and Treatment、Head and Neck Cancer Studies、Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis

PURPOSE: To investigate the value of clinical characteristics and radiological features for predicting spread through air spaces (STAS) in patients with clinical stage IA non-small cell lung cancer (NSCLC). METHODS: A total of 336 patients with NSCLC from our hospital were randomly divided into two groups, i.e., the training cohort (n = 236) and the internal validation cohort (n = 100) (7:3 ratio). Furthermore, 69 patients from two other hospitals were collected as the external validation cohort. Eight clinical patient characteristics were recorded, and 20 tumor radiological features were quantitatively measured and qualitatively analyzed. In the training cohort, the differences in clinical characteristics and radiological features were compared using univariate and multivariate analysis. A nomogram was created, and the predictive efficacy of the model was evaluated in the validation cohorts. The receiver operating characteristic curve and area under the curve (AUC) value were used to evaluate the discriminative ability of the model. In addition, the Hosmer-Lemeshow test and calibration curve were used to evaluate the goodness-of-fit of the model, and the decision curve was used to analyze the model's clinical application value. RESULTS: The best predictors included gender, the carcinoembryonic antigen (CEA), consolidation-to-tumor ratio (CTR), density type, and distal ribbon sign. Among these, the tumor density type [odds ratio (OR): 6.738] and distal ribbon sign (OR: 5.141)...