Literature DB >> 32585196

Propensity-Matched Analysis of Clinical Relevance of the Highest Mediastinal Lymph Node Metastasis.

Shao Dong Wang1, Gan Wei Liu1, Xiao Li1, Xi Zhao Sui1, Fan Yang1, Jun Wang2.   

Abstract

BACKGROUND: The clinical relevance of the highest mediastinal lymph node (HMLL) metastasis in patients with pathological N2 non-small cell lung cancer (NSCLC) is still controversial. Our study aimed to reassess the effect of HMLL metastasis on survival.
METHODS: Patients with stage pT1-4N2M0 NSCLC who underwent major lung resection and systemic lymphadenectomy at Peking University People's Hospital from 2004 to 2015 were identified. Patients in the HMLL-positive group were matched to patients in the HMLL-negative group using 1:1 propensity score matching analysis. Overall survival was estimated by Kaplan-Meier method and compared using log-rank test, and multivariable Cox proportional hazard regression was constructed to identify risk factors associated with overall survival. The cumulative incidence of cancer specific mortality was evaluated through a competing risk analysis.
RESULTS: A total of 266 NSCLC patients with stage pT1-4N2M0 NSCLC were enrolled. Of those, 128 cases were HMLL positive and 138 cases were HMLL negative. A higher proportion of patients in the HMLL-positive group were female (P = .034) and had a higher rate of adenocarcinoma (P = .003). Compared with the HMLL-negative, the HMLL-positive group was not associated with worse survival in unmatched cohorts (adjusted hazard ratio = 1.21; 95% confidence interval, 0.87-1.68). After propensity score matching, 109 pairs were selected. No survival difference remained in matched cohorts (adjusted hazard ratio = 1.00; 95% confidence interval, 0.70-1.42).
CONCLUSIONS: Highest mediastinal lymph node metastasis does not exhibit worse survival in patients with stage pT1-4N2M0 NSCLC. The clinical relevance of HMLL metastasis needs further examination.
Copyright © 2021 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

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Year:  2020        PMID: 32585196     DOI: 10.1016/j.athoracsur.2020.05.027

Source DB:  PubMed          Journal:  Ann Thorac Surg        ISSN: 0003-4975            Impact factor:   4.330


  1 in total

1.  Machine Learning-Based Prediction of Lymph Node Metastasis Among Osteosarcoma Patients.

Authors:  Wenle Li; Yafeng Liu; Wencai Liu; Zhi-Ri Tang; Shengtao Dong; Wanying Li; Kai Zhang; Chan Xu; Zhaohui Hu; Haosheng Wang; Zhi Lei; Qiang Liu; Chunxue Guo; Chengliang Yin
Journal:  Front Oncol       Date:  2022-04-20       Impact factor: 5.738

  1 in total

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