1. 构建并验证nomogram模型预测ⅠA期肺腺癌 肺泡间转移.
- Author
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张龙富, 刘 洁, 倪 筝, 路新源, 胡 斌, 汪 灏, 冯明祥, and 张 勇
- Subjects
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LOGISTIC regression analysis , *RECEIVER operating characteristic curves , *COMPUTED tomography , *UNIVERSITY hospitals , *NOMOGRAPHY (Mathematics) - 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 patients, 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
- Published
- 2022
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