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Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population‐based study

BACKGROUND: Patients with early esophageal cancer (EC) receive individualized therapy based on their lymph node metastasis (LNM) and distant metastasis (DM) status; however, deficiencies in current clinical staging techniques and the issue of cost‐effectiveness mean LNM and DM often go undetected pr...

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Autores principales: Chen, Hong, Wu, Junxian, Guo, Wanting, Yang, Lihang, Lu, Linbin, Lin, Yihong, Wang, Xuewen, Zhang, Yan, Chen, Xi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028124/
https://www.ncbi.nlm.nih.gov/pubmed/36205033
http://dx.doi.org/10.1002/cam4.5334
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author Chen, Hong
Wu, Junxian
Guo, Wanting
Yang, Lihang
Lu, Linbin
Lin, Yihong
Wang, Xuewen
Zhang, Yan
Chen, Xi
author_facet Chen, Hong
Wu, Junxian
Guo, Wanting
Yang, Lihang
Lu, Linbin
Lin, Yihong
Wang, Xuewen
Zhang, Yan
Chen, Xi
author_sort Chen, Hong
collection PubMed
description BACKGROUND: Patients with early esophageal cancer (EC) receive individualized therapy based on their lymph node metastasis (LNM) and distant metastasis (DM) status; however, deficiencies in current clinical staging techniques and the issue of cost‐effectiveness mean LNM and DM often go undetected preoperatively. We aimed to develop three clinical models to predict the likelihood of LNM, DM, and prognosis in patients with early EC. METHOD: The Surveillance, Epidemiology, and End Results database was queried for T1 EC patients from 2004 to 2015. Multivariable logistic regression and Cox proportional hazards models were used to recognize the risk factors of LNM and DM, predict overall survival (OS), and develop relevant nomograms. Receiver operating characteristic (ROC)/concordance index and calibration curves were used to evaluate the discrimination and accuracy of the three nomograms. Decision curve analyses (DCAs), clinical impact curves, and subgroups based on model scores were used to determine clinical practicability. RESULTS: The area under the curve of the LNM and DM nomograms were 0.668 and 0.807, respectively. The corresponding C‐index of OS nomogram was 0.752. Calibration curves and DCA showed an effective predictive accuracy and clinical applicability. In patients with T1N0M0 EC, surgery alone (p < 0.01) proved a survival advantage. Chemotherapy and radiotherapy indicated a better prognosis in the subgroup analysis for T1 EC patients with LNM or DM. CONCLUSIONS: We created three nomograms to predict the likelihood of LNM, DM, and OS probability in patients with early EC using a generalizable dataset. These useful visual tools could help clinical physicians deliver appropriate perioperative care.
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spelling pubmed-100281242023-03-22 Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population‐based study Chen, Hong Wu, Junxian Guo, Wanting Yang, Lihang Lu, Linbin Lin, Yihong Wang, Xuewen Zhang, Yan Chen, Xi Cancer Med RESEARCH ARTICLES BACKGROUND: Patients with early esophageal cancer (EC) receive individualized therapy based on their lymph node metastasis (LNM) and distant metastasis (DM) status; however, deficiencies in current clinical staging techniques and the issue of cost‐effectiveness mean LNM and DM often go undetected preoperatively. We aimed to develop three clinical models to predict the likelihood of LNM, DM, and prognosis in patients with early EC. METHOD: The Surveillance, Epidemiology, and End Results database was queried for T1 EC patients from 2004 to 2015. Multivariable logistic regression and Cox proportional hazards models were used to recognize the risk factors of LNM and DM, predict overall survival (OS), and develop relevant nomograms. Receiver operating characteristic (ROC)/concordance index and calibration curves were used to evaluate the discrimination and accuracy of the three nomograms. Decision curve analyses (DCAs), clinical impact curves, and subgroups based on model scores were used to determine clinical practicability. RESULTS: The area under the curve of the LNM and DM nomograms were 0.668 and 0.807, respectively. The corresponding C‐index of OS nomogram was 0.752. Calibration curves and DCA showed an effective predictive accuracy and clinical applicability. In patients with T1N0M0 EC, surgery alone (p < 0.01) proved a survival advantage. Chemotherapy and radiotherapy indicated a better prognosis in the subgroup analysis for T1 EC patients with LNM or DM. CONCLUSIONS: We created three nomograms to predict the likelihood of LNM, DM, and OS probability in patients with early EC using a generalizable dataset. These useful visual tools could help clinical physicians deliver appropriate perioperative care. John Wiley and Sons Inc. 2022-10-07 /pmc/articles/PMC10028124/ /pubmed/36205033 http://dx.doi.org/10.1002/cam4.5334 Text en © 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle RESEARCH ARTICLES
Chen, Hong
Wu, Junxian
Guo, Wanting
Yang, Lihang
Lu, Linbin
Lin, Yihong
Wang, Xuewen
Zhang, Yan
Chen, Xi
Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population‐based study
title Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population‐based study
title_full Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population‐based study
title_fullStr Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population‐based study
title_full_unstemmed Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population‐based study
title_short Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population‐based study
title_sort clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: a population‐based study
topic RESEARCH ARTICLES
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028124/
https://www.ncbi.nlm.nih.gov/pubmed/36205033
http://dx.doi.org/10.1002/cam4.5334
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