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M2 Macrophage-Based Prognostic Nomogram for Gastric Cancer After Surgical Resection

A good prediction model is useful to accurately predict patient prognosis. Tumor–node–metastasis (TNM) staging often cannot accurately predict prognosis when used alone. Some researchers have shown that the infiltration of M2 macrophages in many tumors indicates poor prognosis. This approach has the...

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Autores principales: Hu, Jianwen, Ma, Yongchen, Ma, Ju, Yang, Yanpeng, Ning, Yingze, Zhu, Jing, Wang, Pengyuan, Chen, Guowei, Liu, Yucun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397443/
https://www.ncbi.nlm.nih.gov/pubmed/34458140
http://dx.doi.org/10.3389/fonc.2021.690037
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author Hu, Jianwen
Ma, Yongchen
Ma, Ju
Yang, Yanpeng
Ning, Yingze
Zhu, Jing
Wang, Pengyuan
Chen, Guowei
Liu, Yucun
author_facet Hu, Jianwen
Ma, Yongchen
Ma, Ju
Yang, Yanpeng
Ning, Yingze
Zhu, Jing
Wang, Pengyuan
Chen, Guowei
Liu, Yucun
author_sort Hu, Jianwen
collection PubMed
description A good prediction model is useful to accurately predict patient prognosis. Tumor–node–metastasis (TNM) staging often cannot accurately predict prognosis when used alone. Some researchers have shown that the infiltration of M2 macrophages in many tumors indicates poor prognosis. This approach has the potential to predict prognosis more accurately when used in combination with TNM staging, but there is less research in gastric cancer. A multivariate analysis demonstrated that CD163 expression, TNM staging, age, and gender were independent risk factors for overall survival. Thus, these parameters were assessed to develop the nomogram in the training data set, which was tested in the validation and whole data sets. The model showed a high degree of discrimination, calibration, and good clinical benefit in the training, validation, and whole data sets. In conclusion, we combined CD163 expression in macrophages, TNM staging, age, and gender to develop a nomogram to predict 3- and 5-year overall survivals after curative resection for gastric cancer. This model has the potential to provide further diagnostic and prognostic value for patients with gastric cancer.
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spelling pubmed-83974432021-08-28 M2 Macrophage-Based Prognostic Nomogram for Gastric Cancer After Surgical Resection Hu, Jianwen Ma, Yongchen Ma, Ju Yang, Yanpeng Ning, Yingze Zhu, Jing Wang, Pengyuan Chen, Guowei Liu, Yucun Front Oncol Oncology A good prediction model is useful to accurately predict patient prognosis. Tumor–node–metastasis (TNM) staging often cannot accurately predict prognosis when used alone. Some researchers have shown that the infiltration of M2 macrophages in many tumors indicates poor prognosis. This approach has the potential to predict prognosis more accurately when used in combination with TNM staging, but there is less research in gastric cancer. A multivariate analysis demonstrated that CD163 expression, TNM staging, age, and gender were independent risk factors for overall survival. Thus, these parameters were assessed to develop the nomogram in the training data set, which was tested in the validation and whole data sets. The model showed a high degree of discrimination, calibration, and good clinical benefit in the training, validation, and whole data sets. In conclusion, we combined CD163 expression in macrophages, TNM staging, age, and gender to develop a nomogram to predict 3- and 5-year overall survivals after curative resection for gastric cancer. This model has the potential to provide further diagnostic and prognostic value for patients with gastric cancer. Frontiers Media S.A. 2021-08-12 /pmc/articles/PMC8397443/ /pubmed/34458140 http://dx.doi.org/10.3389/fonc.2021.690037 Text en Copyright © 2021 Hu, Ma, Ma, Yang, Ning, Zhu, Wang, Chen and Liu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Hu, Jianwen
Ma, Yongchen
Ma, Ju
Yang, Yanpeng
Ning, Yingze
Zhu, Jing
Wang, Pengyuan
Chen, Guowei
Liu, Yucun
M2 Macrophage-Based Prognostic Nomogram for Gastric Cancer After Surgical Resection
title M2 Macrophage-Based Prognostic Nomogram for Gastric Cancer After Surgical Resection
title_full M2 Macrophage-Based Prognostic Nomogram for Gastric Cancer After Surgical Resection
title_fullStr M2 Macrophage-Based Prognostic Nomogram for Gastric Cancer After Surgical Resection
title_full_unstemmed M2 Macrophage-Based Prognostic Nomogram for Gastric Cancer After Surgical Resection
title_short M2 Macrophage-Based Prognostic Nomogram for Gastric Cancer After Surgical Resection
title_sort m2 macrophage-based prognostic nomogram for gastric cancer after surgical resection
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397443/
https://www.ncbi.nlm.nih.gov/pubmed/34458140
http://dx.doi.org/10.3389/fonc.2021.690037
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