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Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering
BACKGROUND: The Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) classification is a key gastric cancer prognosis system. This study aimed to create a new TNM system to provide a reference for the clinical diagnosis and treatment of gastric cancer. METHODS: A review of gastr...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029135/ https://www.ncbi.nlm.nih.gov/pubmed/29970022 http://dx.doi.org/10.1186/s12885-018-4623-z |
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author | Wang, Zhiqiong Li, Mo Xu, Zhen Jiang, Yanlin Gu, Huizi Yu, Ying Zhu, Haitao Zhang, Hao Lu, Ping Xin, Junchang Xu, Hong Liu, Caigang |
author_facet | Wang, Zhiqiong Li, Mo Xu, Zhen Jiang, Yanlin Gu, Huizi Yu, Ying Zhu, Haitao Zhang, Hao Lu, Ping Xin, Junchang Xu, Hong Liu, Caigang |
author_sort | Wang, Zhiqiong |
collection | PubMed |
description | BACKGROUND: The Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) classification is a key gastric cancer prognosis system. This study aimed to create a new TNM system to provide a reference for the clinical diagnosis and treatment of gastric cancer. METHODS: A review of gastric cancer patients’ records was conducted in The First Hospital of China Medical University and the Liaoning Cancer Hospital and Institute. Based on patients’ prognoses data, computer-aided unsupervised clustering was performed for all possible TNM staging situations to create a new staging division system. RESULTS: The primary outcome measure was 5-year survival, analyzed according to TNM classifications. Computer-aided unsupervised clustering for all TNM staging situations was used to create TNM division criteria that were more consistent with clinical situations. Furthermore, unsupervised clustering for the number of lymph node metastasis in the N stage led to the formulation of a classification method that differs from the existing N stage criteria, and unsupervised clustering for tumor size provided an additional reference for prognosis estimates. CONCLUSIONS: Finally, we developed a TNM staging system based on the computer-aided unsupervised clustering method; this system was more in line with clinical prognosis data when compared with the 7th edition of UICC gastric cancer TNM classification. |
format | Online Article Text |
id | pubmed-6029135 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60291352018-07-09 Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering Wang, Zhiqiong Li, Mo Xu, Zhen Jiang, Yanlin Gu, Huizi Yu, Ying Zhu, Haitao Zhang, Hao Lu, Ping Xin, Junchang Xu, Hong Liu, Caigang BMC Cancer Research Article BACKGROUND: The Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) classification is a key gastric cancer prognosis system. This study aimed to create a new TNM system to provide a reference for the clinical diagnosis and treatment of gastric cancer. METHODS: A review of gastric cancer patients’ records was conducted in The First Hospital of China Medical University and the Liaoning Cancer Hospital and Institute. Based on patients’ prognoses data, computer-aided unsupervised clustering was performed for all possible TNM staging situations to create a new staging division system. RESULTS: The primary outcome measure was 5-year survival, analyzed according to TNM classifications. Computer-aided unsupervised clustering for all TNM staging situations was used to create TNM division criteria that were more consistent with clinical situations. Furthermore, unsupervised clustering for the number of lymph node metastasis in the N stage led to the formulation of a classification method that differs from the existing N stage criteria, and unsupervised clustering for tumor size provided an additional reference for prognosis estimates. CONCLUSIONS: Finally, we developed a TNM staging system based on the computer-aided unsupervised clustering method; this system was more in line with clinical prognosis data when compared with the 7th edition of UICC gastric cancer TNM classification. BioMed Central 2018-07-03 /pmc/articles/PMC6029135/ /pubmed/29970022 http://dx.doi.org/10.1186/s12885-018-4623-z 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, Zhiqiong Li, Mo Xu, Zhen Jiang, Yanlin Gu, Huizi Yu, Ying Zhu, Haitao Zhang, Hao Lu, Ping Xin, Junchang Xu, Hong Liu, Caigang Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering |
title | Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering |
title_full | Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering |
title_fullStr | Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering |
title_full_unstemmed | Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering |
title_short | Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering |
title_sort | improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029135/ https://www.ncbi.nlm.nih.gov/pubmed/29970022 http://dx.doi.org/10.1186/s12885-018-4623-z |
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