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Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy
The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Res...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4877645/ https://www.ncbi.nlm.nih.gov/pubmed/27215834 http://dx.doi.org/10.1038/srep26684 |
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author | Cao, Jinlin Yuan, Ping Wang, Luming Wang, Yiqing Ma, Honghai Yuan, Xiaoshuai Lv, Wang Hu, Jian |
author_facet | Cao, Jinlin Yuan, Ping Wang, Luming Wang, Yiqing Ma, Honghai Yuan, Xiaoshuai Lv, Wang Hu, Jian |
author_sort | Cao, Jinlin |
collection | PubMed |
description | The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resampling and a Chinese cohort (n = 145). A total of 4,109 patients from the SEER database were included for analysis. The multivariate analyses showed that the factors of age, race, histology, tumor site, tumor size, grade and depth of invasion, and the numbers of metastases and retrieved nodes were independent prognostic factors. All of these factors were selected into the nomogram. The nomogram showed a clear prognostic superiority over the seventh AJCC-TNM classification (C-index: SEER cohort, 0.716 vs 0.693, respectively; P < 0.01; Chinese cohort, 0.699 vs 0.680, respectively; P < 0.01). Calibration of the nomogram predicted the probabilities of 3- and 5-year survival, which corresponded closely with the actual survival rates. This novel prognostic model may improve clinicians’ abilities to predict individualized survival and to make treatment recommendations. |
format | Online Article Text |
id | pubmed-4877645 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48776452016-06-08 Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy Cao, Jinlin Yuan, Ping Wang, Luming Wang, Yiqing Ma, Honghai Yuan, Xiaoshuai Lv, Wang Hu, Jian Sci Rep Article The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resampling and a Chinese cohort (n = 145). A total of 4,109 patients from the SEER database were included for analysis. The multivariate analyses showed that the factors of age, race, histology, tumor site, tumor size, grade and depth of invasion, and the numbers of metastases and retrieved nodes were independent prognostic factors. All of these factors were selected into the nomogram. The nomogram showed a clear prognostic superiority over the seventh AJCC-TNM classification (C-index: SEER cohort, 0.716 vs 0.693, respectively; P < 0.01; Chinese cohort, 0.699 vs 0.680, respectively; P < 0.01). Calibration of the nomogram predicted the probabilities of 3- and 5-year survival, which corresponded closely with the actual survival rates. This novel prognostic model may improve clinicians’ abilities to predict individualized survival and to make treatment recommendations. Nature Publishing Group 2016-05-24 /pmc/articles/PMC4877645/ /pubmed/27215834 http://dx.doi.org/10.1038/srep26684 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Cao, Jinlin Yuan, Ping Wang, Luming Wang, Yiqing Ma, Honghai Yuan, Xiaoshuai Lv, Wang Hu, Jian Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy |
title | Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy |
title_full | Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy |
title_fullStr | Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy |
title_full_unstemmed | Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy |
title_short | Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy |
title_sort | clinical nomogram for predicting survival of esophageal cancer patients after esophagectomy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4877645/ https://www.ncbi.nlm.nih.gov/pubmed/27215834 http://dx.doi.org/10.1038/srep26684 |
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