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Prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model

BACKGROUND: Inflammation plays an integral role in carcinogenesis and tumor progression. Inflammatory response biomarkers have shown to be promising prognostic factors for improving the predictive accuracy in various cancers. The aim of this study is to investigate the prognostic significance of pre...

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Autores principales: Deng, Qiwen, He, Bangshun, Liu, Xian, Yue, Jin, Ying, Houqun, Pan, Yuqin, Sun, Huiling, Chen, Jie, Wang, Feng, Gao, Tianyi, Zhang, Lei, Wang, Shukui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4343078/
https://www.ncbi.nlm.nih.gov/pubmed/25885254
http://dx.doi.org/10.1186/s12967-015-0409-0
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author Deng, Qiwen
He, Bangshun
Liu, Xian
Yue, Jin
Ying, Houqun
Pan, Yuqin
Sun, Huiling
Chen, Jie
Wang, Feng
Gao, Tianyi
Zhang, Lei
Wang, Shukui
author_facet Deng, Qiwen
He, Bangshun
Liu, Xian
Yue, Jin
Ying, Houqun
Pan, Yuqin
Sun, Huiling
Chen, Jie
Wang, Feng
Gao, Tianyi
Zhang, Lei
Wang, Shukui
author_sort Deng, Qiwen
collection PubMed
description BACKGROUND: Inflammation plays an integral role in carcinogenesis and tumor progression. Inflammatory response biomarkers have shown to be promising prognostic factors for improving the predictive accuracy in various cancers. The aim of this study is to investigate the prognostic significance of pre-operative neutrophil to lymphocyte ratio (NLR), derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR) and lymphocyte to monocyte ratio (LMR) in gastric cancer (GC). METHODS: 389 patients who had undergone gastrectomy were enrolled from 2007 to 2009 in this study. NLR, dNLR, PLR and LMR were calculated from peripheral blood cell count taken at pre-operation. Receiver operating curve (ROC) was used to determine the optimal cut-off levels for these biomarkers. A predictive model or nomogram was established to predict prognosis for cancer-specific survival (CSS) and disease-free survival (DFS), and the predictive accuracy of the nomogram was determined by concordance index (c-index). RESULTS: The median follow-up period was 24 months ranging from 3 months to 60 months. The optimal cut-off levels were 2.36 for NLR, 1.85 for dNLR, 132 for PLR and 4.95 for LMR by ROC curves analysis. Elevated NLR, dNLR and PLR were significantly associated with worse overall survival (OS), CSS and DFS, however, elevated LMR showed an adverse effect on worse OS, CSS and DFS. Multivariate analysis revealed that elevated dNLR was an independent factor for worse OS, and NLR was superior to dNLR, PLR and LMR in terms of hazard ratio (HR = 1.53, 95% CI = 1.11-2.11, P = 0.010), which was shown to be independent prognostic indicators for both CSS and DFS. Moreover, the nomogram could more accurately predict CSS (c-index: 0.89) and DFS (c-index: 0.84) in surgical GC patients. CONCLUSIONS: Pre-operative NLR and dNLR may serve as potential prognostic biomarkers in patients with GC who underwent surgical resection. The proposed nomograms can be used for the prediction of CSS and DFS in patients with GC who have undergone gastrectomy.
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spelling pubmed-43430782015-02-28 Prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model Deng, Qiwen He, Bangshun Liu, Xian Yue, Jin Ying, Houqun Pan, Yuqin Sun, Huiling Chen, Jie Wang, Feng Gao, Tianyi Zhang, Lei Wang, Shukui J Transl Med Research BACKGROUND: Inflammation plays an integral role in carcinogenesis and tumor progression. Inflammatory response biomarkers have shown to be promising prognostic factors for improving the predictive accuracy in various cancers. The aim of this study is to investigate the prognostic significance of pre-operative neutrophil to lymphocyte ratio (NLR), derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR) and lymphocyte to monocyte ratio (LMR) in gastric cancer (GC). METHODS: 389 patients who had undergone gastrectomy were enrolled from 2007 to 2009 in this study. NLR, dNLR, PLR and LMR were calculated from peripheral blood cell count taken at pre-operation. Receiver operating curve (ROC) was used to determine the optimal cut-off levels for these biomarkers. A predictive model or nomogram was established to predict prognosis for cancer-specific survival (CSS) and disease-free survival (DFS), and the predictive accuracy of the nomogram was determined by concordance index (c-index). RESULTS: The median follow-up period was 24 months ranging from 3 months to 60 months. The optimal cut-off levels were 2.36 for NLR, 1.85 for dNLR, 132 for PLR and 4.95 for LMR by ROC curves analysis. Elevated NLR, dNLR and PLR were significantly associated with worse overall survival (OS), CSS and DFS, however, elevated LMR showed an adverse effect on worse OS, CSS and DFS. Multivariate analysis revealed that elevated dNLR was an independent factor for worse OS, and NLR was superior to dNLR, PLR and LMR in terms of hazard ratio (HR = 1.53, 95% CI = 1.11-2.11, P = 0.010), which was shown to be independent prognostic indicators for both CSS and DFS. Moreover, the nomogram could more accurately predict CSS (c-index: 0.89) and DFS (c-index: 0.84) in surgical GC patients. CONCLUSIONS: Pre-operative NLR and dNLR may serve as potential prognostic biomarkers in patients with GC who underwent surgical resection. The proposed nomograms can be used for the prediction of CSS and DFS in patients with GC who have undergone gastrectomy. BioMed Central 2015-02-18 /pmc/articles/PMC4343078/ /pubmed/25885254 http://dx.doi.org/10.1186/s12967-015-0409-0 Text en © Deng et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
Deng, Qiwen
He, Bangshun
Liu, Xian
Yue, Jin
Ying, Houqun
Pan, Yuqin
Sun, Huiling
Chen, Jie
Wang, Feng
Gao, Tianyi
Zhang, Lei
Wang, Shukui
Prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model
title Prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model
title_full Prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model
title_fullStr Prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model
title_full_unstemmed Prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model
title_short Prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model
title_sort prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4343078/
https://www.ncbi.nlm.nih.gov/pubmed/25885254
http://dx.doi.org/10.1186/s12967-015-0409-0
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