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Erschienen in:
10.06.2019 | Original Article
Including positive lymph node count in the AJCC N staging may be a better predictor of the prognosis of NSCLC patients, especially stage III patients: a large population-based study
Erschienen in: International Journal of Clinical Oncology | Ausgabe 11/2019
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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.