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Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy
BACKGROUND: A prognostic model to predict the individual disease-specific survival (DSS) rates of non-metastatic esophageal cancer (nMEC) patients after preoperative radiotherapy (pRT) has not been established. In the current study, we aimed to establish a survival nomogram for nMEC patients after p...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152601/ https://www.ncbi.nlm.nih.gov/pubmed/30271214 http://dx.doi.org/10.2147/CMAR.S165168 |
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author | Xie, Kenan Liu, Song Liu, Jianjun |
author_facet | Xie, Kenan Liu, Song Liu, Jianjun |
author_sort | Xie, Kenan |
collection | PubMed |
description | BACKGROUND: A prognostic model to predict the individual disease-specific survival (DSS) rates of non-metastatic esophageal cancer (nMEC) patients after preoperative radiotherapy (pRT) has not been established. In the current study, we aimed to establish a survival nomogram for nMEC patients after pRT. METHODS: We identified 2,424 nMEC patients who underwent pRT from the Surveillance, Epidemiology, and End Results database. Approximately, 80% (n=1,948) of the included patients were randomly selected and designated as training data set, and the remaining patients (n=476) were defined as external validation set. Nomogram was established by the training set and validated by the validation set. RESULTS: According to the results of the multivariate analysis, a nomogram combined with age at diagnosis, sex, tumor location, yp-T stage, yp metastatic lymph node ratio stage (yp-mLNRS), and grade was developed. The C-index of the model was significantly higher than that of yp-TNM staging system (0.62, 95% CI, 0.58 to 0.66 vs 0.55, 95% CI, 0.51 to 0.60; p<0.001). Calibration plots of the nomogram showed that the probability of DSS rates optimally corresponded to the survival rates were observed. CONCLUSION: The proposed nomogram resulted in more reliable DSS prediction for nMEC patients in general population, regardless of the patient’s histological type. Upon validation, it will aid in individualized survival prediction and prove useful in clinical decision making in nMECs after pRT. |
format | Online Article Text |
id | pubmed-6152601 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61526012018-09-28 Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy Xie, Kenan Liu, Song Liu, Jianjun Cancer Manag Res Original Research BACKGROUND: A prognostic model to predict the individual disease-specific survival (DSS) rates of non-metastatic esophageal cancer (nMEC) patients after preoperative radiotherapy (pRT) has not been established. In the current study, we aimed to establish a survival nomogram for nMEC patients after pRT. METHODS: We identified 2,424 nMEC patients who underwent pRT from the Surveillance, Epidemiology, and End Results database. Approximately, 80% (n=1,948) of the included patients were randomly selected and designated as training data set, and the remaining patients (n=476) were defined as external validation set. Nomogram was established by the training set and validated by the validation set. RESULTS: According to the results of the multivariate analysis, a nomogram combined with age at diagnosis, sex, tumor location, yp-T stage, yp metastatic lymph node ratio stage (yp-mLNRS), and grade was developed. The C-index of the model was significantly higher than that of yp-TNM staging system (0.62, 95% CI, 0.58 to 0.66 vs 0.55, 95% CI, 0.51 to 0.60; p<0.001). Calibration plots of the nomogram showed that the probability of DSS rates optimally corresponded to the survival rates were observed. CONCLUSION: The proposed nomogram resulted in more reliable DSS prediction for nMEC patients in general population, regardless of the patient’s histological type. Upon validation, it will aid in individualized survival prediction and prove useful in clinical decision making in nMECs after pRT. Dove Medical Press 2018-09-18 /pmc/articles/PMC6152601/ /pubmed/30271214 http://dx.doi.org/10.2147/CMAR.S165168 Text en © 2018 Xie et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Xie, Kenan Liu, Song Liu, Jianjun Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy |
title | Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy |
title_full | Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy |
title_fullStr | Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy |
title_full_unstemmed | Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy |
title_short | Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy |
title_sort | nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152601/ https://www.ncbi.nlm.nih.gov/pubmed/30271214 http://dx.doi.org/10.2147/CMAR.S165168 |
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