Evidence map›Paper›PMID 40264135›Full record

ArticleJournal of cardiothoracic surgery2025

Nomogram model for the preoperative prediction of spread through air spaces in sub-centimeter non-small cell lung cancer.

Xiao Wang, Jingwei Shi, Zhengcheng Liu

Abstract read
In one paragraph

Article in Journal of cardiothoracic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Xiao WangDepartment of Thoracic Surgery, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, 211166, China.
Jingwei ShiDepartment of Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210008, China. shijingwei555@126.com.
Zhengcheng LiuDepartment of Thoracic Surgery, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, 211166, China. zhengcheng.liu@njglyy.com.

Funding

Jiangsu Provincial Medical Key Discipline ZDXK202229
6 · The paper itself

Abstract

introductionTo construct and validate a nomogram risk prediction model based on clinical characteristics and radiological features to predict spread through air spaces (STAS) of stage IA sub-centimeter non-small cell lung cancer.

methods112 patients who underwent surgical treatment in Nanjing Drum Tower Hospital with pathologically diagnosed stage IA sub-centimeter non-small cell lung cancer were retrospectively collected. The training cohort and the validation cohort were chosen in a 7:3 ratio. Based on the presence or absence of STAS in pathology results, they were divided into STAS positive and STAS negative groups. The independent risk predictors of STAS in clinical characteristics and radiological features were selected by univariate and multivariate logistic regression analysis and then used to construct a nomogram. The sensitivity and specificity were calculated based on the Youden index, area under the curve (AUC), calibration curves and decision curve analysis (DCA) were used to evaluate the performance of the model.

resultsThe incidence of STAS in the training cohort was 17.9%. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive and mean CT value were associated with the occurrence of STAS; multivariate logistic regression analysis showed that male (OR = 7.900, 95%CI: 1.502-41.545), anti-GAGE7 antibody positive (OR = 10.065, 95%CI: 1.256-80.659) and mean CT value (OR = 1.009, 95%CI: 1.004-1.014) were independent predictors for STAS. The nomogram based on the above factors achieved good predictive performance for STAS with AUC was 0.897 (sensitivity was 0.929, specificity was 0.781) in the training cohort and 0.860 in the validation cohort. The calibration curve and DCA validated the good performance of the model.

conclusionThe nomogram model established in this study had good predictive performance for STAS status of sub-centimeter lung cancer, and provide reference significance for preoperative planning of patients.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsNomogramsAgedFemaleHumansMaleMiddle AgedNeoplasm StagingPredictive Value of TestsPreoperative PeriodRetrospective StudiesTomography, X-Ray ComputedNomogramPrediction modelSpread through air spacesSub-centimeter lung cancer

Identifiers

PMID40264135
PMCPMC12016363

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.