Yanling Fan1, Yanfang Du1, Wenqu Sun2, Haiyong Wang3. 1. Department of Haematology and Oncology, Jinxiang People's Hospital, Jinxiang Hospital Affiliated to Jining Medical University, Jining, 272200, China. 2. Department of Cardiothoracic Surgery, Jinxiang HongDa Hospital Affiliated to Jining Medical University, Jining, 272200, China. 3. Department of Internal-Medicine Oncology, Shandong Cancer Hospital and Institute, Shandong Cancer Hospital Affiliated To Shandong University, Shandong Academy of Medical Sciences, Jinan, 250117, China. wanghaiyong6688@126.com.
Abstract
BACKGROUND: The study was designed to explore the value of including positive lymph node count in the TNM staging system of non-small cell lung cancer. PATIENTS AND METHODS: The X-tile model was applied to determine the cutoff values of positive lymph node count. Survival curves were generated using the Kaplan-Meier method and differences in survival among subgroups were examined using the log-rank test. The influence of different variables on overall survival and lung cancer-specific survival was further evaluated using univariate and multivariate Cox proportional hazard models. All statistical analyses were performed using SPSS version 22.0 (SPSS, Chicago, IL, USA). All p values were 2-sided and p < 0.05 was considered statistically significant. RESULTS: The overall survival and lung cancer-specific survival between stage IIIA and IIIB classified by the sixth edition TNM staging system show no statistically significant difference (p = 0.479 for overall survival; p = 0.081 for lung cancer specific survival). The X-tile model was used to screen three different cutoff values including nN = 0, nN1-3 and nN4-. The nN value is a significant independent prognostic factor that affects overall survival and lung cancer-specific survival of non-small cell lung cancer patients (all, p < 0.001). We obtained the hypothesized TNM sub-stages based on location and the number of PLN. There were significant differences between the hypothesized stage IIIA and IIIB regarding overall survival and lung cancer-specific survival (all, p < 0.001). CONCLUSIONS: It needs to be considered that N stage in combination with positive lymph node count may be used to predict the prognosis of non-small cell lung cancer for stage III cases with increased accuracy than category location-based stage.
BACKGROUND: The study was designed to explore the value of including positive lymph node count in the TNM staging system of non-small cell lung cancer. PATIENTS AND METHODS: The X-tile model was applied to determine the cutoff values of positive lymph node count. Survival curves were generated using the Kaplan-Meier method and differences in survival among subgroups were examined using the log-rank test. The influence of different variables on overall survival and lung cancer-specific survival was further evaluated using univariate and multivariate Cox proportional hazard models. All statistical analyses were performed using SPSS version 22.0 (SPSS, Chicago, IL, USA). All p values were 2-sided and p < 0.05 was considered statistically significant. RESULTS: The overall survival and lung cancer-specific survival between stage IIIA and IIIB classified by the sixth edition TNM staging system show no statistically significant difference (p = 0.479 for overall survival; p = 0.081 for lung cancer specific survival). The X-tile model was used to screen three different cutoff values including nN = 0, nN1-3 and nN4-. The nN value is a significant independent prognostic factor that affects overall survival and lung cancer-specific survival of non-small cell lung cancerpatients (all, p < 0.001). We obtained the hypothesized TNM sub-stages based on location and the number of PLN. There were significant differences between the hypothesized stage IIIA and IIIB regarding overall survival and lung cancer-specific survival (all, p < 0.001). CONCLUSIONS: It needs to be considered that N stage in combination with positive lymph node count may be used to predict the prognosis of non-small cell lung cancer for stage III cases with increased accuracy than category location-based stage.