4.7 Article

Which N Descriptor Is More Predictive of Prognosis in Resected Non-small Cell Lung Cancer The Number of Involved Nodal Stations or the Location-Based Pathological N Stage?

期刊

CHEST
卷 159, 期 6, 页码 2458-2469

出版社

ELSEVIER
DOI: 10.1016/j.chest.2020.12.012

关键词

N classification; non-small cell lung cancer; number of involved nodal stations; prognosis

资金

  1. National Natural Science Foundation of China [NSFC 91959126, NSFC 81770091]
  2. Clinical Research Plan of Shanghai Hospital Development Center [SHDC2020CR1021B]
  3. Fundamental Research Funds for the Central Universities [22120180607]
  4. Shanghai Municipal Education Commission
  5. Shanghai Education Development Foundation [18CG19]
  6. Clinical Research Project of Shanghai Pulmonary Hospital [fk18001]
  7. Shanghai Pulmonary Hospital [FKYQ1907]
  8. Chen Guang project
  9. Outstanding Young Talent project

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The study aimed to evaluate the prognostic significance and discriminatory capability of the number of involved nodal stations (nS) in a large Chinese cohort with non-small cell lung cancer. Results showed that patients could be classified into prognostically different subgroups based on the number of involved nodal stations, with a significant difference in disease-free survival and overall survival. Furthermore, the nS classification demonstrated a higher predictive capability than the location-based N classification.
BACKGROUND: The eighth edition of nodal classification for non-small cell lung cancer (NSCLC) is defined only by the anatomical location of metastatic lymph nodes. RESEARCH QUESTION: We sought to evaluate the prognostic significance and discriminatory capability of the number of involved nodal stations (nS) in a large Chinese cohort. STUDY DESIGN AND METHODS: A total of 4,011 patients with NSCLC undergoing surgical resection between 2009 and 2013 were identified. The optimal cutoff values for nS classification were determined with X-tile software. Kaplan-Meier and multivariate Cox analysis were used to examine the prognostic performance of nS classification in comparison with location-based N classification. A decision curve analysis was performed to evaluate the standardized net benefit of nS classification in predicting prognosis. RESULTS: All the patients were classified into four prognostically different subgroups according to the number of involved nodal stations: (1) nS0 (none positive), (2) nS1 (one involved station), (3) nS2 (two involved stations), and (4) nS >= 3 (three or more involved stations). The prognoses among all the neighboring categories of nS classification were statistically significantly different in terms of disease-free survival and overall survival. The multivariate Cox analysis demonstrated that nS was an independent prognostic factor of disease-free survival and overall survival. Patients with N1 or N2 stage disease could be divided into three prognostically different subgroups according to nS classification. However, the prognosis was similar between the N1 and N2 subgroups when patients were staged in the same nS category. The decision curve analysis showed that nS classification tended to have a higher predictive capability than location-based N classification. INTERPRETATION: The nS classification could be used to provide a more accurate prognosis for patients with resected NSCLC. The nS is worth taking into consideration when defining nodal category in the forthcoming ninth edition of the staging system.

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