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Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer
Preoperative staging of gastric cancer with computed tomography alone exhibits poor diagnostic accuracy, which may lead to improper treatment decisions. We developed novel patient stratification criteria to select appropriate treatments for gastric cancer patients based on preoperative staging and c...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668072/ https://www.ncbi.nlm.nih.gov/pubmed/29108339 http://dx.doi.org/10.18632/oncotarget.18607 |
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author | Cho, In Kwon, In Gyu Guner, Ali Son, Taeil Kim, Hyoung-Il Kang, Dae Ryong Noh, Sung Hoon Lim, Joon Seok Hyung, Woo Jin |
author_facet | Cho, In Kwon, In Gyu Guner, Ali Son, Taeil Kim, Hyoung-Il Kang, Dae Ryong Noh, Sung Hoon Lim, Joon Seok Hyung, Woo Jin |
author_sort | Cho, In |
collection | PubMed |
description | Preoperative staging of gastric cancer with computed tomography alone exhibits poor diagnostic accuracy, which may lead to improper treatment decisions. We developed novel patient stratification criteria to select appropriate treatments for gastric cancer patients based on preoperative staging and clinicopathologic features. A total of 5352 consecutive patients who underwent gastrectomy for gastric cancer were evaluated. Preoperative stages were determined according to depth of invasion and nodal involvement on computed tomography. Logistic regression analysis was used to identify clinicopathological factors associated with the likelihood of proper patient stratification. The diagnostic accuracies of computed tomography scans for depth of invasion and nodal involvement were 67.1% and 74.1%, respectively. Among clinicopathologic factors, differentiated tumor histology, tumors smaller than 5 cm, and gross appearance of early gastric cancer on endoscopy were shown to be related to a more advanced stage of disease on preoperative computed tomography imaging than actual pathological stage. Additional consideration of undifferentiated histology, tumors larger than 5 cm, and grossly advanced gastric cancer on endoscopy increased the probability of selecting appropriate treatment from 75.5% to 94.4%. The addition of histology, tumor size, and endoscopic findings to preoperative staging improves patient stratification for more appropriate treatment of gastric cancer. |
format | Online Article Text |
id | pubmed-5668072 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-56680722017-11-04 Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer Cho, In Kwon, In Gyu Guner, Ali Son, Taeil Kim, Hyoung-Il Kang, Dae Ryong Noh, Sung Hoon Lim, Joon Seok Hyung, Woo Jin Oncotarget Clinical Research Paper Preoperative staging of gastric cancer with computed tomography alone exhibits poor diagnostic accuracy, which may lead to improper treatment decisions. We developed novel patient stratification criteria to select appropriate treatments for gastric cancer patients based on preoperative staging and clinicopathologic features. A total of 5352 consecutive patients who underwent gastrectomy for gastric cancer were evaluated. Preoperative stages were determined according to depth of invasion and nodal involvement on computed tomography. Logistic regression analysis was used to identify clinicopathological factors associated with the likelihood of proper patient stratification. The diagnostic accuracies of computed tomography scans for depth of invasion and nodal involvement were 67.1% and 74.1%, respectively. Among clinicopathologic factors, differentiated tumor histology, tumors smaller than 5 cm, and gross appearance of early gastric cancer on endoscopy were shown to be related to a more advanced stage of disease on preoperative computed tomography imaging than actual pathological stage. Additional consideration of undifferentiated histology, tumors larger than 5 cm, and grossly advanced gastric cancer on endoscopy increased the probability of selecting appropriate treatment from 75.5% to 94.4%. The addition of histology, tumor size, and endoscopic findings to preoperative staging improves patient stratification for more appropriate treatment of gastric cancer. Impact Journals LLC 2017-06-22 /pmc/articles/PMC5668072/ /pubmed/29108339 http://dx.doi.org/10.18632/oncotarget.18607 Text en Copyright: © 2017 Cho et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Clinical Research Paper Cho, In Kwon, In Gyu Guner, Ali Son, Taeil Kim, Hyoung-Il Kang, Dae Ryong Noh, Sung Hoon Lim, Joon Seok Hyung, Woo Jin Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer |
title | Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer |
title_full | Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer |
title_fullStr | Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer |
title_full_unstemmed | Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer |
title_short | Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer |
title_sort | consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer |
topic | Clinical Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668072/ https://www.ncbi.nlm.nih.gov/pubmed/29108339 http://dx.doi.org/10.18632/oncotarget.18607 |
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