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Prognostic value of computed tomography characteristics for overall survival in patients with maxillary cancer

BACKGROUND: Our aim was to identify the preoperative computed tomographic (CT) characteristics most efficient in predicting overall survival (OS) of patients with maxillary cancer (MC). METHODS: A retrospective review of CT images was performed in 115 patients with histopathologically confirmed prim...

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Autores principales: Yuan, Ying, Wang, Jingbo, Wu, Yingwei, Li, Guojun, Tao, Xiaofeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5057221/
https://www.ncbi.nlm.nih.gov/pubmed/27724942
http://dx.doi.org/10.1186/s12885-016-2830-z
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author Yuan, Ying
Wang, Jingbo
Wu, Yingwei
Li, Guojun
Tao, Xiaofeng
author_facet Yuan, Ying
Wang, Jingbo
Wu, Yingwei
Li, Guojun
Tao, Xiaofeng
author_sort Yuan, Ying
collection PubMed
description BACKGROUND: Our aim was to identify the preoperative computed tomographic (CT) characteristics most efficient in predicting overall survival (OS) of patients with maxillary cancer (MC). METHODS: A retrospective review of CT images was performed in 115 patients with histopathologically confirmed primary MC from January 2005 to December 2013, who were classified into 2 subtypes (epithelial and non-epithelial) according to tissue of origin. The prognostic value of CT characteristics for OS was determined firstly through univariate Kaplan-Meier survival estimates with log-rank tests. Significant predictors were further tested with multivariable Cox proportional hazard models. RESULTS: CT characteristics predictive of OS in univariate survival analysis were long and short diameter of the mass, long and short diameter of the largest cervical lymph node and adjacent soft tissue infiltration (P < 0.05). In the multivariable Cox analyses, the significantly independent predictors were long diameter of mass ≥ 4.2 cm (hazard ratio [HR] 1.8; 95 % confidence interval [CI] 1.1–3.0) and short diameter of the largest lymph node ≥ 7 mm (HR 1.9; 95 % CI 1.0–3.6) for all MC patients, as well as for non-epithelial MC patients (HR 3.1; 95 % CI 1.2–8.0; HR 3.3; 95 % CI 1.3–8.7, respectively). CONCLUSIONS: Preoperative CT characteristics of tumor size, lymph node size and adjacent structure infiltration are predictive of the OS time of MC patients. The information brought up in this study could be used in clinical practice to inform about the possible prognosis, and be beneficial to clinical decision making.
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spelling pubmed-50572212016-10-20 Prognostic value of computed tomography characteristics for overall survival in patients with maxillary cancer Yuan, Ying Wang, Jingbo Wu, Yingwei Li, Guojun Tao, Xiaofeng BMC Cancer Research Article BACKGROUND: Our aim was to identify the preoperative computed tomographic (CT) characteristics most efficient in predicting overall survival (OS) of patients with maxillary cancer (MC). METHODS: A retrospective review of CT images was performed in 115 patients with histopathologically confirmed primary MC from January 2005 to December 2013, who were classified into 2 subtypes (epithelial and non-epithelial) according to tissue of origin. The prognostic value of CT characteristics for OS was determined firstly through univariate Kaplan-Meier survival estimates with log-rank tests. Significant predictors were further tested with multivariable Cox proportional hazard models. RESULTS: CT characteristics predictive of OS in univariate survival analysis were long and short diameter of the mass, long and short diameter of the largest cervical lymph node and adjacent soft tissue infiltration (P < 0.05). In the multivariable Cox analyses, the significantly independent predictors were long diameter of mass ≥ 4.2 cm (hazard ratio [HR] 1.8; 95 % confidence interval [CI] 1.1–3.0) and short diameter of the largest lymph node ≥ 7 mm (HR 1.9; 95 % CI 1.0–3.6) for all MC patients, as well as for non-epithelial MC patients (HR 3.1; 95 % CI 1.2–8.0; HR 3.3; 95 % CI 1.3–8.7, respectively). CONCLUSIONS: Preoperative CT characteristics of tumor size, lymph node size and adjacent structure infiltration are predictive of the OS time of MC patients. The information brought up in this study could be used in clinical practice to inform about the possible prognosis, and be beneficial to clinical decision making. BioMed Central 2016-10-10 /pmc/articles/PMC5057221/ /pubmed/27724942 http://dx.doi.org/10.1186/s12885-016-2830-z Text en © The Author(s). 2016 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
Yuan, Ying
Wang, Jingbo
Wu, Yingwei
Li, Guojun
Tao, Xiaofeng
Prognostic value of computed tomography characteristics for overall survival in patients with maxillary cancer
title Prognostic value of computed tomography characteristics for overall survival in patients with maxillary cancer
title_full Prognostic value of computed tomography characteristics for overall survival in patients with maxillary cancer
title_fullStr Prognostic value of computed tomography characteristics for overall survival in patients with maxillary cancer
title_full_unstemmed Prognostic value of computed tomography characteristics for overall survival in patients with maxillary cancer
title_short Prognostic value of computed tomography characteristics for overall survival in patients with maxillary cancer
title_sort prognostic value of computed tomography characteristics for overall survival in patients with maxillary cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5057221/
https://www.ncbi.nlm.nih.gov/pubmed/27724942
http://dx.doi.org/10.1186/s12885-016-2830-z
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