Clinical Prediction of Lung Cancer Complicated with Pulmonary Infection After Thoracoscopic Surgery Based on Nomogram Model
10.3971/j.issn.1000-8578.2023.22.0585
- VernacularTitle:基于列线图模型对肺癌胸腔镜术后并发肺部感染的临床预测
- Author:
Xiuqiang ZHANG
1
;
Tao YANG
Author Information
1. Department of Thoracic Surgery, Tianjin Fifth Central Hospital, Tianjin 300450, China
- Publication Type:Research Article
- Keywords:
Lung infection;
Lung cancer;
Thoracoscopy;
Nomogram model;
Risk factors
- From:
Cancer Research on Prevention and Treatment
2023;50(1):52-57
- CountryChina
- Language:Chinese
-
Abstract:
Objective To analyze the risk factors of lung cancer patients complicated with pulmonary infection after thoracoscopic surgery and establish a predictive nomogram model. Methods A total of 315 patients with primary lung cancer who had undergone thoracoscopic surgery from January 2018 to October 2021 in our hospital were divided into two groups according to the incidence of pulmonary infection. Two groups of clinical data were collected for single-factor and regression analyses, and independent predictors were obtained. On this basis, a risk model was constructed and its predictive effectiveness was evaluated. Results The independent risk factors of lung cancer patients complicated with pulmonary infection after thoracoscopic radical operation were as follows: age≥62.5 years, smoking index≥100, PEF≤72.1 ml/s, TNM stage Ⅲ/Ⅳ, and operation time≥188.5 min (P < 0.05). Based on the above factors, the risk model of the column chart was established. Model-verification results showed that the C-index of the model was 0.909, and the correction curve showed that the column chart model had good differentiation and consistency. Conclusion Lung cancer patients' age, smoking index, TNM stage, PEF, and operation time are closely related to pulmonary infection after thoracoscopic radical operation. The nomogram model is useful for identifying high-risk patients and reducing postoperative complications.
