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Development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a SEER population-based study and external validation

BACKGROUND: Adenocarcinoma in Esophagogastric Junction (AEG) is a severe gastrointestinal malignancy with a unique clinicopathological feature. Hence, we aimed to develop a competing risk nomogram for predicting survival for AEG patients and compared it with new 8th traditional tumor-node-metastasis...

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Autores principales: Wang, Tongbo, Wu, Yan, Zhou, Hong, Wu, Chaorui, Zhang, Xiaojie, Chen, Yingtai, Zhao, Dongbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836166/
https://www.ncbi.nlm.nih.gov/pubmed/33499821
http://dx.doi.org/10.1186/s12876-021-01618-7
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author Wang, Tongbo
Wu, Yan
Zhou, Hong
Wu, Chaorui
Zhang, Xiaojie
Chen, Yingtai
Zhao, Dongbing
author_facet Wang, Tongbo
Wu, Yan
Zhou, Hong
Wu, Chaorui
Zhang, Xiaojie
Chen, Yingtai
Zhao, Dongbing
author_sort Wang, Tongbo
collection PubMed
description BACKGROUND: Adenocarcinoma in Esophagogastric Junction (AEG) is a severe gastrointestinal malignancy with a unique clinicopathological feature. Hence, we aimed to develop a competing risk nomogram for predicting survival for AEG patients and compared it with new 8th traditional tumor-node-metastasis (TNM) staging system. METHODS: Based on data from the Surveillance, Epidemiology, and End Results (SEER) database of AEG patients between 2004 and 2010, we used univariate and multivariate analysis to filter clinical factors and then built a competing risk nomogram to predict AEG cause-specific survival. We then measured the clinical accuracy by comparing them to the 8th TNM stage with a Receiver Operating Characteristic (ROC) curve, Brier score, and Decision Curve Analysis (DCA). External validation was performed in 273 patients from China National Cancer Center. RESULTS: A total of 1755 patients were included in this study. The nomogram was based on five variables: Number of examined lymph nodes, grade, invasion, metastatic LNs, and age. The results of the nomogram was greater than traditional TNM staging with ROC curve (1-year AUC: 0.747 vs. 0.641, 3-year AUC: 0.761 vs. 0.679, 5-year AUC: 0.759 vs. 0.682, 7-year AUC: 0.749 vs. 0.673, P < 0.001), Brier score (3-year: 0.198 vs. 0.217, P = 0.012; 5-year: 0.198 vs. 0.216, P = 0.008; 7-year: 0.199 vs. 0.215, P = 0.014) and DCA. In external validation, the nomogram also showed better diagnostic value than traditional TNM staging and great prediction accuracy. CONCLUSION: We developed and validated a novel nomogram and risk stratification system integrating clinicopathological characteristics for AEG patients. The model showed superior prediction ability for AEG patients than traditional TNM classification.
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spelling pubmed-78361662021-01-26 Development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a SEER population-based study and external validation Wang, Tongbo Wu, Yan Zhou, Hong Wu, Chaorui Zhang, Xiaojie Chen, Yingtai Zhao, Dongbing BMC Gastroenterol Research Article BACKGROUND: Adenocarcinoma in Esophagogastric Junction (AEG) is a severe gastrointestinal malignancy with a unique clinicopathological feature. Hence, we aimed to develop a competing risk nomogram for predicting survival for AEG patients and compared it with new 8th traditional tumor-node-metastasis (TNM) staging system. METHODS: Based on data from the Surveillance, Epidemiology, and End Results (SEER) database of AEG patients between 2004 and 2010, we used univariate and multivariate analysis to filter clinical factors and then built a competing risk nomogram to predict AEG cause-specific survival. We then measured the clinical accuracy by comparing them to the 8th TNM stage with a Receiver Operating Characteristic (ROC) curve, Brier score, and Decision Curve Analysis (DCA). External validation was performed in 273 patients from China National Cancer Center. RESULTS: A total of 1755 patients were included in this study. The nomogram was based on five variables: Number of examined lymph nodes, grade, invasion, metastatic LNs, and age. The results of the nomogram was greater than traditional TNM staging with ROC curve (1-year AUC: 0.747 vs. 0.641, 3-year AUC: 0.761 vs. 0.679, 5-year AUC: 0.759 vs. 0.682, 7-year AUC: 0.749 vs. 0.673, P < 0.001), Brier score (3-year: 0.198 vs. 0.217, P = 0.012; 5-year: 0.198 vs. 0.216, P = 0.008; 7-year: 0.199 vs. 0.215, P = 0.014) and DCA. In external validation, the nomogram also showed better diagnostic value than traditional TNM staging and great prediction accuracy. CONCLUSION: We developed and validated a novel nomogram and risk stratification system integrating clinicopathological characteristics for AEG patients. The model showed superior prediction ability for AEG patients than traditional TNM classification. BioMed Central 2021-01-26 /pmc/articles/PMC7836166/ /pubmed/33499821 http://dx.doi.org/10.1186/s12876-021-01618-7 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research Article
Wang, Tongbo
Wu, Yan
Zhou, Hong
Wu, Chaorui
Zhang, Xiaojie
Chen, Yingtai
Zhao, Dongbing
Development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a SEER population-based study and external validation
title Development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a SEER population-based study and external validation
title_full Development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a SEER population-based study and external validation
title_fullStr Development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a SEER population-based study and external validation
title_full_unstemmed Development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a SEER population-based study and external validation
title_short Development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a SEER population-based study and external validation
title_sort development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a seer population-based study and external validation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836166/
https://www.ncbi.nlm.nih.gov/pubmed/33499821
http://dx.doi.org/10.1186/s12876-021-01618-7
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