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Development and Validation of a Clinical Prognostic Nomogram for Esophageal Adenocarcinoma Patients

BACKGROUND: Clinical staging is essential for clinical decisions but remains imprecise. We purposed to construct a novel survival prediction model for improving clinical staging system (cTNM) for patients with esophageal adenocarcioma (EAC). METHODS: A total of 4180 patients diagnosed with EAC were...

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Autores principales: Shao, Chen-ye, Yu, Yue, Li, Qi-fan, Liu, Xiao-long, Song, Hai-zhu, Shen, Yi, Yi, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445330/
https://www.ncbi.nlm.nih.gov/pubmed/34540700
http://dx.doi.org/10.3389/fonc.2021.736573
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author Shao, Chen-ye
Yu, Yue
Li, Qi-fan
Liu, Xiao-long
Song, Hai-zhu
Shen, Yi
Yi, Jun
author_facet Shao, Chen-ye
Yu, Yue
Li, Qi-fan
Liu, Xiao-long
Song, Hai-zhu
Shen, Yi
Yi, Jun
author_sort Shao, Chen-ye
collection PubMed
description BACKGROUND: Clinical staging is essential for clinical decisions but remains imprecise. We purposed to construct a novel survival prediction model for improving clinical staging system (cTNM) for patients with esophageal adenocarcioma (EAC). METHODS: A total of 4180 patients diagnosed with EAC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and included as the training cohort. Significant prognostic variables were identified for nomogram model development using multivariable Cox regression. The model was validated internally by bootstrap resampling, and then subjected to external validation with a separate cohort of 886 patients from 2 institutions in China. The prognostic performance was measured by concordance index (C-index), Akaike information criterion (AIC) and calibration plots. Different risk groups were stratified by the nomogram scores. RESULTS: A total of six variables were determined related with survival and entered into the nomogram construction. The calibration curves showed satisfied agreement between nomogram-predicted survival and actual observed survival for 1-, 3-, and 5-year overall survival. By calculating the AIC and C-index values, our nomogram presented superior discriminative and risk-stratifying ability than current TNM staging system. Significant distinctions in survival curves were observed between different risk subgroups stratified by nomogram scores. CONCLUSION: The established and validated nomogram presented better risk-stratifying ability than current clinical staging system, and could provide a convenient and reliable tool for individual survival prediction and treatment strategy making.
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spelling pubmed-84453302021-09-17 Development and Validation of a Clinical Prognostic Nomogram for Esophageal Adenocarcinoma Patients Shao, Chen-ye Yu, Yue Li, Qi-fan Liu, Xiao-long Song, Hai-zhu Shen, Yi Yi, Jun Front Oncol Oncology BACKGROUND: Clinical staging is essential for clinical decisions but remains imprecise. We purposed to construct a novel survival prediction model for improving clinical staging system (cTNM) for patients with esophageal adenocarcioma (EAC). METHODS: A total of 4180 patients diagnosed with EAC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and included as the training cohort. Significant prognostic variables were identified for nomogram model development using multivariable Cox regression. The model was validated internally by bootstrap resampling, and then subjected to external validation with a separate cohort of 886 patients from 2 institutions in China. The prognostic performance was measured by concordance index (C-index), Akaike information criterion (AIC) and calibration plots. Different risk groups were stratified by the nomogram scores. RESULTS: A total of six variables were determined related with survival and entered into the nomogram construction. The calibration curves showed satisfied agreement between nomogram-predicted survival and actual observed survival for 1-, 3-, and 5-year overall survival. By calculating the AIC and C-index values, our nomogram presented superior discriminative and risk-stratifying ability than current TNM staging system. Significant distinctions in survival curves were observed between different risk subgroups stratified by nomogram scores. CONCLUSION: The established and validated nomogram presented better risk-stratifying ability than current clinical staging system, and could provide a convenient and reliable tool for individual survival prediction and treatment strategy making. Frontiers Media S.A. 2021-09-02 /pmc/articles/PMC8445330/ /pubmed/34540700 http://dx.doi.org/10.3389/fonc.2021.736573 Text en Copyright © 2021 Shao, Yu, Li, Liu, Song, Shen and Yi https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Shao, Chen-ye
Yu, Yue
Li, Qi-fan
Liu, Xiao-long
Song, Hai-zhu
Shen, Yi
Yi, Jun
Development and Validation of a Clinical Prognostic Nomogram for Esophageal Adenocarcinoma Patients
title Development and Validation of a Clinical Prognostic Nomogram for Esophageal Adenocarcinoma Patients
title_full Development and Validation of a Clinical Prognostic Nomogram for Esophageal Adenocarcinoma Patients
title_fullStr Development and Validation of a Clinical Prognostic Nomogram for Esophageal Adenocarcinoma Patients
title_full_unstemmed Development and Validation of a Clinical Prognostic Nomogram for Esophageal Adenocarcinoma Patients
title_short Development and Validation of a Clinical Prognostic Nomogram for Esophageal Adenocarcinoma Patients
title_sort development and validation of a clinical prognostic nomogram for esophageal adenocarcinoma patients
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445330/
https://www.ncbi.nlm.nih.gov/pubmed/34540700
http://dx.doi.org/10.3389/fonc.2021.736573
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