浙江医学2023，Vol.45Issue(23)：2491-2495,5.DOI:10.12056/j.issn.1006-2785.2023.45.23.2023-913
基于临床CT特征的列线图模型预测浸润性肺腺癌预后分级的研究
Construction of a nomogram model based on clinical and CT features in predicting the prognosis grading of lung invasive adenocarcinoma
摘要
Abstract
Objective To construct a nomogram model based on clinical and CT features in predicting the prognostic grading of lung invasive adenocarcinoma(IAC).Methods Clinical and imaging data of 235 patients with IAC who underwent high-resolution CT examination and surgical treatment in Dongyang People's Hospital from July 2019 to June 2022 were retrospectively analyzed.According to IASLC 2020 version,178 patients were classified in the low-risk group and 57 patients in the high-risk group.The association of clinical and CT features with IASLC grading was analyzed with multivariate logistic regression,and a nomogram model for predicting prognosis grading was constructed based on the independent risk factors.Results There were significant differences in age,gender,smoking history,emphysema,tumor long diameter,and density,shape,spicule sign,lobulation sign,bronchial occlusion sign,and air bronchus sign on CT imaging between the two groups(all P＜0.05).Multivariate logistic regression analysis showed that smoking history,long diameter of tumor,and density,spicule sign,air bronchus sign on CT imaging were independent predictors of the IASLC prognosis grading(all P＜0.05).A nomogram model was constructed based on above five predictors with an AUC of 0.908,sensitivity of 0.780 and specificity of 0.855.The calibration curve showed that the model fit well,and the high net benefit of the decision curve analysis also reflected the clinical practicability of the model.Conclusion The constructed nomogram model based on clinical and CT features has high value in predicting the IASLC prognostic grading.关键词
浸润性肺腺癌/CT/预后分级/列线图Key words
Lung invasive adenocarcinoma/Computed tomography/Prognosis grade/Nomogram引用本文复制引用
杨泽斌,赵奋华,傅春龙,单康飞,吴淼,陈晓璐,吴梅康,徐杰萍,马驰骏,朱伟华..基于临床CT特征的列线图模型预测浸润性肺腺癌预后分级的研究[J].浙江医学,2023,45(23):2491-2495,5.基金项目
浙江省医药卫生科技计划项目(2023KY1289) （2023KY1289）
