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An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy

BACKGROUND: Emerging inflammatory response biomarkers are developed to predict the survival of patients with cancer, the aim of our study is to establish an inflammation-related nomogram based on the classical predictive biomarkers to predict the survivals of patients with non-small cell lung cancer...

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Autores principales: Wang, Ying, Qu, Xiao, Kam, Ngar-Woon, Wang, Kai, Shen, Hongchang, Liu, Qi, Du, Jiajun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019648/
https://www.ncbi.nlm.nih.gov/pubmed/29940884
http://dx.doi.org/10.1186/s12885-018-4513-4
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author Wang, Ying
Qu, Xiao
Kam, Ngar-Woon
Wang, Kai
Shen, Hongchang
Liu, Qi
Du, Jiajun
author_facet Wang, Ying
Qu, Xiao
Kam, Ngar-Woon
Wang, Kai
Shen, Hongchang
Liu, Qi
Du, Jiajun
author_sort Wang, Ying
collection PubMed
description BACKGROUND: Emerging inflammatory response biomarkers are developed to predict the survival of patients with cancer, the aim of our study is to establish an inflammation-related nomogram based on the classical predictive biomarkers to predict the survivals of patients with non-small cell lung cancer (NSCLC). METHODS: Nine hundred and fifty-two NSCLC patients with lung cancer surgery performed were enrolled into this study. The cutoffs of inflammatory response biomarkers were determined by Receiver operating curve (ROC). Univariate and multivariate analysis were conducted to select independent prognostic factors to develop the nomogram. RESULTS: The median follow-up time was 40.0 months (range, 1 to 92 months). The neutrophil to lymphocyte ratio (cut-off: 3.10, HR:1.648, P = 0.045) was selected to establish the nomogram which could predict the 5-year OS probability. The C-index of nomogram was 0.72 and the 5-year OS calibration curve displayed an optimal agreement between the actual observed outcomes and the predictive results. CONCLUSIONS: Neutrophil to lymphocyte ratio was shown to be a valuable biomarker for predicting survival of patients with NSCLC. The addition of neutrophil to lymphocyte ratio could improve the accuracy and predictability of the nomogram in order to provide reference for clinicians to assess patient outcomes.
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spelling pubmed-60196482018-07-06 An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy Wang, Ying Qu, Xiao Kam, Ngar-Woon Wang, Kai Shen, Hongchang Liu, Qi Du, Jiajun BMC Cancer Research Article BACKGROUND: Emerging inflammatory response biomarkers are developed to predict the survival of patients with cancer, the aim of our study is to establish an inflammation-related nomogram based on the classical predictive biomarkers to predict the survivals of patients with non-small cell lung cancer (NSCLC). METHODS: Nine hundred and fifty-two NSCLC patients with lung cancer surgery performed were enrolled into this study. The cutoffs of inflammatory response biomarkers were determined by Receiver operating curve (ROC). Univariate and multivariate analysis were conducted to select independent prognostic factors to develop the nomogram. RESULTS: The median follow-up time was 40.0 months (range, 1 to 92 months). The neutrophil to lymphocyte ratio (cut-off: 3.10, HR:1.648, P = 0.045) was selected to establish the nomogram which could predict the 5-year OS probability. The C-index of nomogram was 0.72 and the 5-year OS calibration curve displayed an optimal agreement between the actual observed outcomes and the predictive results. CONCLUSIONS: Neutrophil to lymphocyte ratio was shown to be a valuable biomarker for predicting survival of patients with NSCLC. The addition of neutrophil to lymphocyte ratio could improve the accuracy and predictability of the nomogram in order to provide reference for clinicians to assess patient outcomes. BioMed Central 2018-06-26 /pmc/articles/PMC6019648/ /pubmed/29940884 http://dx.doi.org/10.1186/s12885-018-4513-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Wang, Ying
Qu, Xiao
Kam, Ngar-Woon
Wang, Kai
Shen, Hongchang
Liu, Qi
Du, Jiajun
An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy
title An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy
title_full An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy
title_fullStr An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy
title_full_unstemmed An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy
title_short An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy
title_sort inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019648/
https://www.ncbi.nlm.nih.gov/pubmed/29940884
http://dx.doi.org/10.1186/s12885-018-4513-4
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