scholarly journals Polo‐like kinase 4 correlates with greater tumor size, lymph node metastasis and confers poor survival in non‐small cell lung cancer

2019 ◽  
Vol 34 (4) ◽  
Author(s):  
Qin Zhou ◽  
Gongchun Fan ◽  
Yuanyuan Dong
Keyword(s):  
Lung Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Tumor Size ◽  
Small Cell ◽  
Small Cell Lung ◽  
Poor Survival ◽  
Node Metastasis

Increased high-mobility group A2 correlates with lymph node metastasis and prognosis of non-small cell lung cancer

2018 ◽  
Vol 21 (3) ◽  
pp. 547-555 ◽  
Author(s):  
Xiangjun Guo ◽  
Jiaxin Shi ◽  
Yan Wen ◽  
Mengmeng Li ◽  
Qin Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
High Mobility ◽  
Small Cell ◽  
High Mobility Group ◽  
Small Cell Lung ◽  
Node Metastasis

scholarly journals Development of Nomograms for Predicting Lymph Node Metastasis and Distant Metastasis in Newly Diagnosed T1-2 Non-Small Cell Lung Cancer: A Population-Based Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Yiming Qi ◽  
Shuangshuang Wu ◽  
Linghui Tao ◽  
Yunfu Shi ◽  
Wenjuan Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lung Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Small Cell Lung Cancer ◽  
Distant Metastasis ◽  
Tumor Size ◽  
Small Cell ◽  
Small Cell Lung ◽  
Node Metastasis

BackgroundFor different lymph node metastasis (LNM) and distant metastasis (DM), the diagnosis, treatment and prognosis of T1-2 non-small cell lung cancer (NSCLC) are different. It is essential to figure out the risk factors and establish prediction models related to LNM and DM.MethodsBased on the surveillance, epidemiology, and end results (SEER) database from 1973 to 2015, a total of 43,156 eligible T1-2 NSCLC patients were enrolled in the retrospective study. Logistic regression analysis was used to determine the risk factors of LNM and DM. Risk factors were applied to construct the nomograms of LNM and DM. The predictive nomograms were discriminated against and evaluated by Concordance index (C-index) and calibration plots, respectively. Decision curve analysis (DCAs) was accepted to measure the clinical application of the nomogram. Cumulative incidence function (CIF) was performed further to detect the prognostic role of LNM and DM in NSCLC-specific death (NCSD).ResultsEight factors (age at diagnosis, race, sex, histology, T-stage, marital status, tumor size, and grade) were significant in predicting LNM and nine factors (race, sex, histology, T-stage, N-stage, marital status, tumor size, grade, and laterality) were important in predicting DM(all, P< 0.05). The calibration curves displayed that the prediction nomograms were effective and discriminative, of which the C-index were 0.723 and 0.808. The DCAs and clinical impact curves exhibited that the prediction nomograms were clinically effective.ConclusionsThe newly constructed nomograms can objectively and accurately predict LNM and DM in patients suffering from T1-2 NSCLC, which may help clinicians make individual clinical decisions before clinical management.

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