Erschienen in:
07.06.2019 | Original Article – Clinical Oncology
A prognostic score system with lymph node ratio in stage IIIA-N2 NSCLC patients after surgery and adjuvant chemotherapy
verfasst von:
Han Han, Yue Zhao, Zhendong Gao, Difan Zheng, Fangqiu Fu, Zitong Zhao, Ya Tang, Jiaqing Xiang, Yihua Sun, Hong Hu, Haiquan Chen
Erschienen in:
Journal of Cancer Research and Clinical Oncology
|
Ausgabe 8/2019
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Abstract
Purpose
The survival of patients with IIIA-N2 non-small cell lung cancer after surgery followed by adjuvant chemotherapy is heterogeneous. The aim of this study is to form a prognostic system and a heat map method to visualize the overall survival rates in those patients.
Methods
Univariate and multivariate Cox hazards regression models and the associated Wald Chi square coefficient were used to form the prognostic score system. Recursive partitioning analysis was used to determine the cutoff values of lymph node ratio and prognostic score in SEER cohort and validated in FDUSCC cohort. Meanwhile, a heat map method was used to visualize the overall survival probabilities of 3, 5 and 10 years for individual patient of both cohorts.
Results
Lymph node ratio (with cutoff of 0.36) significantly correlates with overall survival of these patients. In addition, in patients with the same level of N2 disease, lymph node ratio still significantly affects survival. Also, after the multivariate analysis in SEER cohort, six factors were independent prognostic factors including age, sex, type of surgery, size, lymph node ratio and differentiation. A prognostic sore system with these factors (with cutoff of 12) was validated as a predictor for overall survival in FDUSCC cohort.
Conclusions
This prognostic score system including lymph node ratio can predict the survival rates of IIIA-N2 patient after surgery and post-operative chemotherapy. Lymph node ratio could be a useful supplementation in TNM stage classification for IIIA-N2 patients. The heat map method can visualize the predicted overall survival of an individual patient.