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A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is characterized clinically by frequent recurrence, leading to a poor prognosis after radical surgery. The aim of this study was to identify a prognostic nomogram to predict the post-progression survival (PPS) of ESCC patients based on the featur...

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Autores principales: Leng, Changsen, Cui, Yingying, Chen, Junying, Wang, Kexi, Yang, Hong, Wen, Jing, Fu, Jianhua, Liu, Qianwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300830/
https://www.ncbi.nlm.nih.gov/pubmed/35875105
http://dx.doi.org/10.3389/fonc.2022.925685
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author Leng, Changsen
Cui, Yingying
Chen, Junying
Wang, Kexi
Yang, Hong
Wen, Jing
Fu, Jianhua
Liu, Qianwen
author_facet Leng, Changsen
Cui, Yingying
Chen, Junying
Wang, Kexi
Yang, Hong
Wen, Jing
Fu, Jianhua
Liu, Qianwen
author_sort Leng, Changsen
collection PubMed
description BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is characterized clinically by frequent recurrence, leading to a poor prognosis after radical surgery. The aim of this study was to identify a prognostic nomogram to predict the post-progression survival (PPS) of ESCC patients based on the features of primary tumor and recurrence. METHODS: A total of 234 ESCC patients who underwent recurrence after radical surgery were enrolled in this study. The independent prognostic factors screened by the univariate and multivariate Cox regression analysis were subsequently used to construct a nomogram. The predictive performance of the nomogram was evaluated with the concordance index (C-index), decision curve, and the area under the receiver operating characteristic curve (AUC) and validated in two validation cohorts. The Kaplan-Meier curves of different recurrence patterns were analyzed. RESULTS: The prognostic nomogram of PPS was established by integrating independent prognostic factors, including age, body mass index, number of lymph node dissection, recurrence pattern, and recurrence treatment. The nomogram demonstrated good performance, with C-index values of 0.756, 0.817, and 0.730 for the training and two validation cohorts. The 1-year AUC values were 0.773, 0.798, and 0.735 and 3-year AUC values were 0.832, 0.871, and 0.791, respectively. Furthermore, we found that patients with bone metastasis displayed the worst PPS compared to other isolated recurrence patterns. CONCLUSION: We constructed a nomogram to reliably predict PPS, which would be valuable to provide individual managements for ESCC patients after radical surgery.
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spelling pubmed-93008302022-07-22 A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection Leng, Changsen Cui, Yingying Chen, Junying Wang, Kexi Yang, Hong Wen, Jing Fu, Jianhua Liu, Qianwen Front Oncol Oncology BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is characterized clinically by frequent recurrence, leading to a poor prognosis after radical surgery. The aim of this study was to identify a prognostic nomogram to predict the post-progression survival (PPS) of ESCC patients based on the features of primary tumor and recurrence. METHODS: A total of 234 ESCC patients who underwent recurrence after radical surgery were enrolled in this study. The independent prognostic factors screened by the univariate and multivariate Cox regression analysis were subsequently used to construct a nomogram. The predictive performance of the nomogram was evaluated with the concordance index (C-index), decision curve, and the area under the receiver operating characteristic curve (AUC) and validated in two validation cohorts. The Kaplan-Meier curves of different recurrence patterns were analyzed. RESULTS: The prognostic nomogram of PPS was established by integrating independent prognostic factors, including age, body mass index, number of lymph node dissection, recurrence pattern, and recurrence treatment. The nomogram demonstrated good performance, with C-index values of 0.756, 0.817, and 0.730 for the training and two validation cohorts. The 1-year AUC values were 0.773, 0.798, and 0.735 and 3-year AUC values were 0.832, 0.871, and 0.791, respectively. Furthermore, we found that patients with bone metastasis displayed the worst PPS compared to other isolated recurrence patterns. CONCLUSION: We constructed a nomogram to reliably predict PPS, which would be valuable to provide individual managements for ESCC patients after radical surgery. Frontiers Media S.A. 2022-07-07 /pmc/articles/PMC9300830/ /pubmed/35875105 http://dx.doi.org/10.3389/fonc.2022.925685 Text en Copyright © 2022 Leng, Cui, Chen, Wang, Yang, Wen, Fu and Liu 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
Leng, Changsen
Cui, Yingying
Chen, Junying
Wang, Kexi
Yang, Hong
Wen, Jing
Fu, Jianhua
Liu, Qianwen
A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection
title A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection
title_full A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection
title_fullStr A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection
title_full_unstemmed A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection
title_short A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection
title_sort nomogram model to predict post-progression survival in esophageal squamous cell carcinoma patients with recurrence after radical resection
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300830/
https://www.ncbi.nlm.nih.gov/pubmed/35875105
http://dx.doi.org/10.3389/fonc.2022.925685
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