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A novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer
BACKGROUND: To develop and evaluate the prognostic value of a comprehensive inflammatory biomarker for postoperative colorectal cancer (CRC) patients. METHODS: A total of 646 CRC patients were recruited between August 2017 and December 2019 from Fujian Medical University Union Hospital, with follow-...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917685/ https://www.ncbi.nlm.nih.gov/pubmed/35277188 http://dx.doi.org/10.1186/s12957-022-02550-0 |
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author | Cai, Xiaoling Chen, Fa Liang, Lisheng Jiang, Weizhong Liu, Xing Wang, Dong Wu, Yunli Chen, Jinyan Guan, Guoxian Peng, Xian-e |
author_facet | Cai, Xiaoling Chen, Fa Liang, Lisheng Jiang, Weizhong Liu, Xing Wang, Dong Wu, Yunli Chen, Jinyan Guan, Guoxian Peng, Xian-e |
author_sort | Cai, Xiaoling |
collection | PubMed |
description | BACKGROUND: To develop and evaluate the prognostic value of a comprehensive inflammatory biomarker for postoperative colorectal cancer (CRC) patients. METHODS: A total of 646 CRC patients were recruited between August 2017 and December 2019 from Fujian Medical University Union Hospital, with follow-up data up to 2021. The least absolute shrinkage and selection operator method (LASSO) was used to select inflammation indicators in order to construct a comprehensive biomarker (named NSAP). The Cox regression model was utilized to analyze the association between the NSAP and the disease-free survival (DFS) of CRC. Predictive performance and clinical utility of prognostic models were evaluated by area under the curve (AUC) and decision curve analyses (DCAs). RESULTS: During a median follow-up of 23 months, 95 clinical outcomes were observed, with a 1-year survival rate is 89.47%. A comprehensive inflammatory biomarker (NSAP) was established based on four blood indicators (including neutrophil-to-lymphocyte ratio (NLR), neutrophil×monocyte-to-lymphocyte ratio (SIRI), albumin-to-globulin ratio (AGR), and platelet-to-lymphocytes ratio (PLR)). Patients with a lower NSAP had significantly associated with better DFS of CRC (HR=0.53, 95%CI 0.32–0.89). Moreover, compared to a previously established model, the traditional TNM staging system or/and tumor markers, the nomogram based on NSAP displayed more excellent predictive ability (0.752 vs 0.597, 0.711 and 0.735, P < 0.05). DCAs also demonstrated that the established nomogram had better utility for decision making. CONCLUSIONS: Our study suggests that NSAP may be a useful comprehensive prognostic biomarker for predicting the DFS of CRC patients. The nomogram based on NSAP can be considered a valuable tool to estimate the prognosis of patients with CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-022-02550-0. |
format | Online Article Text |
id | pubmed-8917685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89176852022-03-21 A novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer Cai, Xiaoling Chen, Fa Liang, Lisheng Jiang, Weizhong Liu, Xing Wang, Dong Wu, Yunli Chen, Jinyan Guan, Guoxian Peng, Xian-e World J Surg Oncol Research BACKGROUND: To develop and evaluate the prognostic value of a comprehensive inflammatory biomarker for postoperative colorectal cancer (CRC) patients. METHODS: A total of 646 CRC patients were recruited between August 2017 and December 2019 from Fujian Medical University Union Hospital, with follow-up data up to 2021. The least absolute shrinkage and selection operator method (LASSO) was used to select inflammation indicators in order to construct a comprehensive biomarker (named NSAP). The Cox regression model was utilized to analyze the association between the NSAP and the disease-free survival (DFS) of CRC. Predictive performance and clinical utility of prognostic models were evaluated by area under the curve (AUC) and decision curve analyses (DCAs). RESULTS: During a median follow-up of 23 months, 95 clinical outcomes were observed, with a 1-year survival rate is 89.47%. A comprehensive inflammatory biomarker (NSAP) was established based on four blood indicators (including neutrophil-to-lymphocyte ratio (NLR), neutrophil×monocyte-to-lymphocyte ratio (SIRI), albumin-to-globulin ratio (AGR), and platelet-to-lymphocytes ratio (PLR)). Patients with a lower NSAP had significantly associated with better DFS of CRC (HR=0.53, 95%CI 0.32–0.89). Moreover, compared to a previously established model, the traditional TNM staging system or/and tumor markers, the nomogram based on NSAP displayed more excellent predictive ability (0.752 vs 0.597, 0.711 and 0.735, P < 0.05). DCAs also demonstrated that the established nomogram had better utility for decision making. CONCLUSIONS: Our study suggests that NSAP may be a useful comprehensive prognostic biomarker for predicting the DFS of CRC patients. The nomogram based on NSAP can be considered a valuable tool to estimate the prognosis of patients with CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-022-02550-0. BioMed Central 2022-03-11 /pmc/articles/PMC8917685/ /pubmed/35277188 http://dx.doi.org/10.1186/s12957-022-02550-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Cai, Xiaoling Chen, Fa Liang, Lisheng Jiang, Weizhong Liu, Xing Wang, Dong Wu, Yunli Chen, Jinyan Guan, Guoxian Peng, Xian-e A novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer |
title | A novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer |
title_full | A novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer |
title_fullStr | A novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer |
title_full_unstemmed | A novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer |
title_short | A novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer |
title_sort | novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917685/ https://www.ncbi.nlm.nih.gov/pubmed/35277188 http://dx.doi.org/10.1186/s12957-022-02550-0 |
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