ArticleJTCVS open2022
Visualization of patterns of lymph node metastases in non-small cell lung cancer using network analysis.
Article in JTCVS open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06496360 (Prediction Model of Mediastinal Group IV Lymph Node Metastasis in Non-small Cell Lung Cancer Based on CT Radiomics), which is not on this map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Prediction Model of Mediastinal Group IV Lymph Node Metastasis in Non-small Cell Lung Cancer Based on CT Radiomics
Who cites it
4 citing papers in PubMed, 3 citations in OpenAlex.
- Elective nodal irradiation of high-risk regions is superior to involved field radiotherapy for limited-stage small cell lung cancer: a propensity score-matched retrospective study.Radiation oncology (London, England) · 2026Article
- Critical appraisal of "Prognostic impact of pure-solid non-small cell lung cancer in the superior versus basal segment of the lower lobe following lobectomy".General thoracic and cardiovascular surgery · 2026Article
- Identification of the lymph node metastasis atlas and optimal lymph node dissection strategy in patients with resectable lung invasive mucinous adenocarcinoma: a real-world multicenter study.Military Medical Research · 2025Article
- Application of network analysis and association rule mining for visualizing the lymph node metastasis patterns in esophageal squamous cell carcinoma.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: We aimed to visualize complicated patterns of lymph node metastases in surgically resected non-small cell lung cancer by applying a data mining technique. Methods: In this retrospective study, 783 patients underwent lobectomy or pneumonectomy with systematic mediastinal lymph node dissection for non-small cell lung cancer between January 2010 and December 2018. Surgically resected lymph nodes were classified according to the International Association for the Study of Lung Cancer lymph node map. Network analysis generated patterns of lymph node metastases from stations 1 to 14, and the degree of connection between 2 lymph node stations was assessed. Results: The median number of lymph nodes examined per patient was 20, and the pathological N category was pN0 in 428 cases, pN1 in 132, pN2 in 221, and pN3 in 2. N1 lymph node stations had strong associations with superior mediastinal lymph node stations for patients with primary tumors in the upper lobes and with station 7 for the lower lobes. There was also a connection from the N1 lymph node stations to superior mediastinal lymph node stations in the lower lobes. In the right middle lobe, an even distribution from station 12m toward stations 2R, 4R, and 7 was noted. We released an interactive web application to visualize these data: http://www.canexapp.com. Conclusions: Lymph node metastasis patterns differed according to the lobe bearing the tumor. Our results support the need for clinical trials to further investigate selective mediastinal lymph node dissection.
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Registered trials
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