Correlation of solid proportion and lymph node metastasis in lung cancers ≤30 mm in diameter
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Lymph node metastasis (LNM) of lung cancer is relatively common in clinical practice, and accurate diagnosis of LNM remains challenging. This study aimed to clarify the correlation between clinical computed tomography (CT) imaging features and LNM in lung cancers ≤30 mm according to different solid proportions (SPs). Methods: A total of 2,074 patients with lung cancer confirmed by surgical pathology and lymph node dissection were included. All lung cancers were categorized into three groups: ground-glass nodule (GGN), solid nodule (SN), and GGN + SN. Predictive models 1, 2, and 3 were constructed for the respective groups, and univariate and multivariate logistic regression analyses were used to determine the LNM risk in each group. Differences between models were compared with the Delong test. Results: In model 1 (GGN), SP was the sole independent risk factor, and the area under the curve (AUC) and accuracy of this model were 0.929 [95% confidence interval (CI): 0.911-0.947] and 0.850, respectively. In model 2 (SN), high blood pressure, heterogeneous ventilation or perfusion, short diameter (SD), and CT mean density value (CTmean) were independent risk factors, with the AUC and accuracy of this model being 0.733 (95% CI: 0.678-0.788) and 0.735, respectively. In model 3, age, SP, spiculation, pleural tag, and rim sign were independent risk factors, with the AUC and accuracy of this model being 0.904 (95% CI: 0.888-0.920) and 0.751, respectively. The Delong test revealed significant differences between model 2 and both models 1 and 3 (P<0.05). Conclusions: Model 1 and model 3 demonstrated high diagnostic value for the preoperative prediction of LNM in patients with lung cancer.
Authors: Dengfa Yang, Fengjuan Tian, Xiting Peng, Caidi He, Linfeng He, Hengfeng Shi, Cui Zhang, Zhenyu Cao, Zongyu Xie, Jian Wang
Institutions: Taizhou Municipal Hospital, Taizhou University, Taizhou University, Sir Run Run Shaw Hospital, Zhejiang University, Anhui Medical University, Anqing City Hospital, Zhejiang Chinese Medical University, Tongde Hospital of Zhejiang Province, First Affiliated Hospital of Bengbu Medical College
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4416455173