Long Xu1, Hang Su1, Yunlang She1, Chenyang Dai1, Mengmeng Zhao1, Jiani Gao1, Huikang Xie2, Yijiu Ren1, Dong Xie1, Chang Chen3. 1. Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. 2. Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. 3. Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. Electronic address: chenthoracic@163.com.
Abstract
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.
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.