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Construction and validation of a nomogram model to predict the overall survival rate of esophageal cancer patients receiving neoadjuvant chemotherapy: A population-based study

INTRODUCTION: The development of neoadjuvant chemotherapy(nCT) improves the overall survival (OS) of patients with esophageal cancer(EC). The aim of this study was to determine the independent prognostic factors of EC patients receiving nCT, and to construct a nomogram model for predicting OS. METHO...

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Autores principales: Yang, Ying, He, Changjin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894093/
https://www.ncbi.nlm.nih.gov/pubmed/36743892
http://dx.doi.org/10.3389/fsurg.2022.1066092
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author Yang, Ying
He, Changjin
author_facet Yang, Ying
He, Changjin
author_sort Yang, Ying
collection PubMed
description INTRODUCTION: The development of neoadjuvant chemotherapy(nCT) improves the overall survival (OS) of patients with esophageal cancer(EC). The aim of this study was to determine the independent prognostic factors of EC patients receiving nCT, and to construct a nomogram model for predicting OS. METHOD: This retrospective analysis was conducted from the National Cancer Institute's Surveillance Epidemiology and End Results, Clinicopathological data of patients with EC who received nCT from 2004 to 2015. The included patients were randomly divided into the training cohort and the validation cohort. Univariate and multivariate Cox proportional hazards models were used to analyze the patients in the training cohort to determine the independent prognostic factors. Based on the independent prognostic variables, nomogram models for 1-year, 2-year and 3-year OS were constructed. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the discriminative ability. The calibration curves, decision curve analysis (DCA) and Kaplan-Meier (K-M) survival analysis were used to evaluate the predictive accuracy and clinical application value. RESULTS: A total of 2,493 patients were enrolled, with 1,748 patients in the training cohort and 745 patients in the validation cohort. Gender, marital status, tumor pathological grade, T stage, N stage, and M stage were identified as independent prognostic factor (P < 0.05). A novel nomogram model was constructed. ROC curve analysis revealed that the model had moderate predictive performance, which was better than that of the AJCC TNM staging system.The calibration curves showed a high agreement between the actual observed values and the predicted values. The DCA suggested that the newly constructed prediction model had good clinical application value. K-M survival analysis showed that the model was helpful to accurately distinguish the prognosis of patients with different risk levels. CONCLUSIONS: Gender, tumor pathological grade, marital status, T stage, N stage and M stage were identified as independent prognostic factors for overall survival of patients with esophageal cancer who received neoadjuvant chemotherapy. A nomogram prediction model was established, which was helpful to accurately and reliably predict the overall survival rate of patients with esophageal cancer who received neoadjuvant chemotherapy at 1, 2 and 3 years.
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spelling pubmed-98940932023-02-03 Construction and validation of a nomogram model to predict the overall survival rate of esophageal cancer patients receiving neoadjuvant chemotherapy: A population-based study Yang, Ying He, Changjin Front Surg Surgery INTRODUCTION: The development of neoadjuvant chemotherapy(nCT) improves the overall survival (OS) of patients with esophageal cancer(EC). The aim of this study was to determine the independent prognostic factors of EC patients receiving nCT, and to construct a nomogram model for predicting OS. METHOD: This retrospective analysis was conducted from the National Cancer Institute's Surveillance Epidemiology and End Results, Clinicopathological data of patients with EC who received nCT from 2004 to 2015. The included patients were randomly divided into the training cohort and the validation cohort. Univariate and multivariate Cox proportional hazards models were used to analyze the patients in the training cohort to determine the independent prognostic factors. Based on the independent prognostic variables, nomogram models for 1-year, 2-year and 3-year OS were constructed. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the discriminative ability. The calibration curves, decision curve analysis (DCA) and Kaplan-Meier (K-M) survival analysis were used to evaluate the predictive accuracy and clinical application value. RESULTS: A total of 2,493 patients were enrolled, with 1,748 patients in the training cohort and 745 patients in the validation cohort. Gender, marital status, tumor pathological grade, T stage, N stage, and M stage were identified as independent prognostic factor (P < 0.05). A novel nomogram model was constructed. ROC curve analysis revealed that the model had moderate predictive performance, which was better than that of the AJCC TNM staging system.The calibration curves showed a high agreement between the actual observed values and the predicted values. The DCA suggested that the newly constructed prediction model had good clinical application value. K-M survival analysis showed that the model was helpful to accurately distinguish the prognosis of patients with different risk levels. CONCLUSIONS: Gender, tumor pathological grade, marital status, T stage, N stage and M stage were identified as independent prognostic factors for overall survival of patients with esophageal cancer who received neoadjuvant chemotherapy. A nomogram prediction model was established, which was helpful to accurately and reliably predict the overall survival rate of patients with esophageal cancer who received neoadjuvant chemotherapy at 1, 2 and 3 years. Frontiers Media S.A. 2023-01-06 /pmc/articles/PMC9894093/ /pubmed/36743892 http://dx.doi.org/10.3389/fsurg.2022.1066092 Text en © 2023 Yang and He. 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) (https://creativecommons.org/licenses/by/4.0/) . 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 Surgery
Yang, Ying
He, Changjin
Construction and validation of a nomogram model to predict the overall survival rate of esophageal cancer patients receiving neoadjuvant chemotherapy: A population-based study
title Construction and validation of a nomogram model to predict the overall survival rate of esophageal cancer patients receiving neoadjuvant chemotherapy: A population-based study
title_full Construction and validation of a nomogram model to predict the overall survival rate of esophageal cancer patients receiving neoadjuvant chemotherapy: A population-based study
title_fullStr Construction and validation of a nomogram model to predict the overall survival rate of esophageal cancer patients receiving neoadjuvant chemotherapy: A population-based study
title_full_unstemmed Construction and validation of a nomogram model to predict the overall survival rate of esophageal cancer patients receiving neoadjuvant chemotherapy: A population-based study
title_short Construction and validation of a nomogram model to predict the overall survival rate of esophageal cancer patients receiving neoadjuvant chemotherapy: A population-based study
title_sort construction and validation of a nomogram model to predict the overall survival rate of esophageal cancer patients receiving neoadjuvant chemotherapy: a population-based study
topic Surgery
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894093/
https://www.ncbi.nlm.nih.gov/pubmed/36743892
http://dx.doi.org/10.3389/fsurg.2022.1066092
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