Evidence map›Paper›PMID 39604960›Full record

ArticleBMC pulmonary medicine2024

A nomogram for predicting lymphovascular invasion in lung adenocarcinoma: a retrospective study.

Miaomaio Lin, Xiang Zhao, Haipeng Huang, Huashan Lin, Kai Li

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Article in BMC pulmonary medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Miaomaio LinDepartment of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Xiang ZhaoDepartment of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Haipeng HuangDepartment of Radiology, People's Hospital of Guangxi Zhuang Autonomous, Nanning, China.
Huashan LinDepartment of Pharmaceutical Diagnosis, GE Healthcare, Shanghai, China.
Kai LiDepartment of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China. doctorlikai@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroudLymphovascular invasion (LVI) was histological factor that was closely related to prognosis of lung adenocarcinoma (LAC).The primary aim was to investigate the value of a nomogram incorporating clinical and computed tomography (CT) factors to predict LVI in LAC, and validating the predictive efficacy of a clinical model for LVI in patients with lung adenocarcinoma with lesions ≤ 3 cm.

methodsA total of 450 patients with LAC were retrospectively enrolled. Clinical data and CT features were analyzed to identify independent predictors of LVI. A nomogram incorporating the independent predictors of LVI was built. The performance of the nomogram was evaluated by assessing its discriminative ability and clinical utility.We took 321 patients with tumours ≤ 3 cm in diameter to continue constructing the clinical prediction model, which was labelled subgroup clinical model.

resultsCarcinoembryonic antigen (CEA) level, maximum tumor diameter, spiculation, and vacuole sign were independent predictors of LVI. The LVI prediction nomogram showed good discrimination in the training set [area under the curve (AUC), 0.800] and the test set (AUC, 0.790), the subgroup clinical model also owned the stable predictive efficacy for preoperative prediction of LVI in lung adenocarcinoma patients, and both training and test set AUC reached 0.740.

conclusionsThe nomogram developed in this study could predict the risk of LVI in LAC patients, facilitate individualized risk-stratification, and help inform treatment decision-makin, and the subgroup clinical model also had good predictive performance for lung cancer patients with lesion ≤ 3 cm in diameter.

Indexed as

Adenocarcinoma of LungLung NeoplasmsNeoplasm InvasivenessNomogramsTomography, X-Ray ComputedAdultAgedCarcinoembryonic AntigenFemaleHumansLymphatic MetastasisMaleMiddle AgedPrognosisRetrospective StudiesCarcinoembryonic AntigenComputed TomographyLung adenocarcinomaLymphovascular invasionNomogram

Identifiers

PMID39604960
PMCPMC11603933

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