期刊
TRANSLATIONAL LUNG CANCER RESEARCH
卷 10, 期 2, 页码 866-+出版社
AME PUBLISHING COMPANY
DOI: 10.21037/tlcr-20-997
关键词
Limited-stage small-cell lung cancer (LS-SCLC); neutrophil-to-lymphocyte ratio (NLR); platelet-to-lymphocyte ratio (PLR); prognosis
资金
- National Natural Science Foundation of China [81773007]
- Shanghai Municipal Human Resources and Social Security Bureau [201706]
- Three-year Action Plan Project for Promoting Clinical Skills and Clinical Innovation in Municipal Hospitals [16CR2013A]
- Shanghai Municipal Commission of Health and Family Planning [2017YQ018]
The study aimed to establish NLR and PLR related nomograms based on clinical data and peripheral blood markers to predict the survival of LS-SCLC patients. Elevated NLR and PLR were found to predict poor prognosis in their respective nomograms, showing better accuracy and stability compared to the TNM staging system. The models had a better effect in predicting prognosis as indicated by C-index and calibration curves.
Background: We aim to establish neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) related nomograms based on the clinical data and peripheral blood markers to predict the survivals of patients with limited-stage small-cell lung cancer (LS-SCLC). Methods: A total of 299 LS-SCLC patients after surgery were enrolled in this study. Univariate and multivariate analyses were conducted to select independent prognostic factors to develop the nomograms and then subjected to bootstrap internal validation. The optimal cutoff value of NLR and PLR before surgery was calculated by X-tile (version 3.6.1) and the overall survival (OS) was analyzed by Kaplan-Meier method and compared by log-rank test. Results: According to the X-tile calculation, the NLR value and PLR cutoff values are 2.6 and 156.7, respectively. The prognosis of patients with elevated NLR or PLR value was significantly worse than patients with lower NLR (HR =1.798, 95% CI: 1.284-2.518, P=0.001) or PLR (HR =1.781, 95% CI: 1.318-2.407, P<0.001) value. Two Nomograms were developed according to the two multivariate cox regression models based on NLR and PLR. Concordance index (C-index) curves and calibration curves show that the two models have a better effect in predicting prognosis. At the same time, compared with the tumor node metastasis (TNM) staging system, our models also show better accuracy and stability. Conclusions: Elevated NLR and PLR predict poor prognosis in their respective nomograms in patients with LS-SCLC.
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