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新型非实性肺小结节恶性概率预测模型的构建与验证

肖飞 余其多 张真榕 刘德若 梁朝阳

中国肺癌杂志2019,Vol.22Issue(1):26-33,8.
中国肺癌杂志2019,Vol.22Issue(1):26-33,8.DOI:10.3779/j.issn.1009-3419.2019.01.06

新型非实性肺小结节恶性概率预测模型的构建与验证

Establishment and Verification of A Novel Predictive Model of Malignancy for Non-solid Pulmonary Nodules

肖飞 1余其多 1张真榕 1刘德若 1梁朝阳1

作者信息

  • 1. 中日友好医院胸外科 100029 北京
  • 折叠

摘要

Abstract

Background and objective Mathematical predictive model is an effective method for preliminarily identifying the malignant pulmonary nodules.As the epidemiological trend of lung cancer changes, the detection rate of groundglass-opacity (GGO) like early stage lung cancer is increasing rapidly, timely and proper clinical management can effectively improve the patients'prognosis.Our study aims to establish a novel predictive model of malignancy for non-solid pulmonary nodules, which would provide an objective evidence for invasive procedure and avoid unnecessary operation and the consequences.Methods We retrospectively analyzed the basic demographics, serum tumor markers and imaging features of 362cases of non-solid pulmonary nodule from January 2013 to April 2018.All nodules received biopsy or surgical resection, and got pathological diagnosis.Cases were randomly divided into two groups.The modeling group was used for univariate analysis and logistic regression to determine independent risk factors and establish the predictive model.Data of the validation group was used to validate the predictive value and make a comparison with other models.Results Of the 362 cases with nonsolid pulmonary nodule, 313 (86.5%) cases were diagnosed as AAH/AIS, MIA or invasive adenocarcinoma, 49 cases were diagnosed as benign lesions.Age, serum tumor markers CEA and Cyfra21-1, consolidation tumor ratio value, lobulation and calcification were identified as independent risk factors.The AUC value of the ROC curve was 0.894, the predictive sensitivity and specificity were 87.6%, 69.7%, the positive and negative predictive value were 94.8%, 46.9%.The validated predictive value is significantly better than that of the VA, Brock and GMUFH models.Conclusion Proved with high predictive sensitivity and positive predictive value, this novel model could help enable preliminarily screening of"high-risk"non-solid pulmonary

关键词

肺小结节/肺肿瘤/预测模型/恶性概率

Key words

Pulmonary nodule/Lung neoplasms/Predictive model/Probability of malignancy

引用本文复制引用

肖飞,余其多,张真榕,刘德若,梁朝阳..新型非实性肺小结节恶性概率预测模型的构建与验证[J].中国肺癌杂志,2019,22(1):26-33,8.

中国肺癌杂志

OA北大核心CSCDCSTPCDMEDLINE

1009-3419

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