Evidence map›Paper›PMID 40241103›Full record

ArticleJournal of cardiothoracic surgery2025

A novel nomogram based on PET/CT to predict lymph nodal metastasis for lung adenocarcinoma with normal size lymph node.

Xinyu Zhu, Xinyu Jia, Shibing Teng, Kai Fu, Jiawei Chen, Jun Zhao, Chang Li

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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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xinyu Zhu *Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Xinyu Jia *Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Shibing Teng *Department of Thoracic Surgery, Suzhou Xiangcheng People's Hospital, Suzhou, China.
Kai FuDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Jiawei ChenDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Jun ZhaoDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China. junzhao@suda.edu.cn.
Chang LiDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China. cli@suda.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA precise assessment of lymph nodal status is essential for guiding an individualized treatment plan in lung adenocarcinoma patients. A novel nomogram using easily accessible indicators was developed and validated in this study to predict CT-negative lymph nodal metastasis.

methodsBetween September 2020 and December 2023, data from 132 consecutive patients diagnosed with lung adenocarcinoma who underwent lung resection with systemic lymph node dissection or sampling were retrospectively reviewed. Risk factors associated with lymph nodal metastasis were identified using univariable and multivariable logistic regression analyses. Subsequently, a nomogram was developed on basis of these identified parameters. The performance and validity of the nomogram were evaluated using the area under the receiver operating characteristic (ROC) curve, calibration curve, and bootstrap resampling techniques.

resultsFour predictors (primary tumor location, primary tumor SUVmax value, N1 lymph node SUVmax, and N2 lymph node SUVmax) were identified and incorporated into the nomogram. The nomogram exhibited notable discrimination, evidenced by an area under the ROC curve of 0.825 (95% CI: 0.749-0.886, P < 0.001). Excellent concordance between the predicted and observed probabilities of lymph nodal involvement was demonstrated by the calibration curve. Furthermore, decision curve analysis indicated a net benefit associated with the use of our nomogram.

conclusionThe nomogram demonstrated efficacy and practicality in predicting CT-negative lymph node metastasis for lung adenocarcinoma patients. It holds potential to offer valuable treatment guidance for clinicians.

Indexed as

Adenocarcinoma of LungLung NeoplasmsLymph NodesNomogramsPositron Emission Tomography Computed TomographyAgedFemaleHumansLymphatic MetastasisLymph Node ExcisionMaleMiddle AgedPredictive Value of TestsRetrospective StudiesROC CurveLung adenocarcinomaLymph nodal metastasisNomogramPositron emission tomography/Computed tomography (PET/CT)

Identifiers

PMID40241103
PMCPMC12001486

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LicenceCC BY-NC-ND
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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.