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Development and validation of nomograms to intraoperatively predict metastatic patterns in regional lymph nodes in patients diagnosed with esophageal cancer

BACKGROUND: An accurate intraoperative prediction of lymph node metastatic risk can help surgeons in choosing precise surgical procedures. We aimed to develop and validate nomograms to intraoperatively predict patterns of regional lymph node (LN) metastasis in patients with esophageal cancer. METHOD...

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Autores principales: Zhao, Fei, Lu, Rong-Xin, Liu, Jin-Yuan, Fan, Jun, Lin, Hao-Ran, Yang, Xiao-Yu, You, Shu-Hui, Wu, Qian-Ge, Qin, Xue-Yun, Liu, Yi, Zhen, Fu-Xi, Luo, Jin-Hua, Wang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7786479/
https://www.ncbi.nlm.nih.gov/pubmed/33402129
http://dx.doi.org/10.1186/s12885-020-07738-9
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author Zhao, Fei
Lu, Rong-Xin
Liu, Jin-Yuan
Fan, Jun
Lin, Hao-Ran
Yang, Xiao-Yu
You, Shu-Hui
Wu, Qian-Ge
Qin, Xue-Yun
Liu, Yi
Zhen, Fu-Xi
Luo, Jin-Hua
Wang, Wei
author_facet Zhao, Fei
Lu, Rong-Xin
Liu, Jin-Yuan
Fan, Jun
Lin, Hao-Ran
Yang, Xiao-Yu
You, Shu-Hui
Wu, Qian-Ge
Qin, Xue-Yun
Liu, Yi
Zhen, Fu-Xi
Luo, Jin-Hua
Wang, Wei
author_sort Zhao, Fei
collection PubMed
description BACKGROUND: An accurate intraoperative prediction of lymph node metastatic risk can help surgeons in choosing precise surgical procedures. We aimed to develop and validate nomograms to intraoperatively predict patterns of regional lymph node (LN) metastasis in patients with esophageal cancer. METHODS: The prediction model was developed in a training cohort consisting of 487 patients diagnosed with esophageal cancer who underwent esophagectomy with complete LN dissection from January 2016 to December 2016. Univariate and multivariable logistic regression were used to identify independent risk factors that were incorporated into a prediction model and used to construct a nomogram. Contrast-enhanced computed tomography reported LN status and was an important comparative factor of clinical usefulness in a validation cohort. Nomogram performance was assessed in terms of calibration, discrimination, and clinical usefulness. An independent validation cohort comprised 206 consecutive patients from January 2017 to December 2017. RESULTS: Univariate analysis and multivariable logistic regression revealed three independent predictors of metastatic regional LNs, three independent predictors of continuous regional LNs, and two independent predictors of skipping regional LNs. Independent predictors were used to build three individualized prediction nomograms. The models showed good calibration and discrimination, with area under the curve (AUC) values of 0.737, 0.738, and 0.707. Application of the nomogram in the validation cohort yielded good calibration and discrimination, with AUC values of 0.728, 0.668, and 0.657. Decision curve analysis demonstrated that the three nomograms were clinically useful in the validation cohort. CONCLUSION: This study presents three nomograms that incorporate clinicopathologic factors, which can be used to facilitate the intraoperative prediction of metastatic regional LN patterns in patients with esophageal cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-020-07738-9.
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spelling pubmed-77864792021-01-07 Development and validation of nomograms to intraoperatively predict metastatic patterns in regional lymph nodes in patients diagnosed with esophageal cancer Zhao, Fei Lu, Rong-Xin Liu, Jin-Yuan Fan, Jun Lin, Hao-Ran Yang, Xiao-Yu You, Shu-Hui Wu, Qian-Ge Qin, Xue-Yun Liu, Yi Zhen, Fu-Xi Luo, Jin-Hua Wang, Wei BMC Cancer Research Article BACKGROUND: An accurate intraoperative prediction of lymph node metastatic risk can help surgeons in choosing precise surgical procedures. We aimed to develop and validate nomograms to intraoperatively predict patterns of regional lymph node (LN) metastasis in patients with esophageal cancer. METHODS: The prediction model was developed in a training cohort consisting of 487 patients diagnosed with esophageal cancer who underwent esophagectomy with complete LN dissection from January 2016 to December 2016. Univariate and multivariable logistic regression were used to identify independent risk factors that were incorporated into a prediction model and used to construct a nomogram. Contrast-enhanced computed tomography reported LN status and was an important comparative factor of clinical usefulness in a validation cohort. Nomogram performance was assessed in terms of calibration, discrimination, and clinical usefulness. An independent validation cohort comprised 206 consecutive patients from January 2017 to December 2017. RESULTS: Univariate analysis and multivariable logistic regression revealed three independent predictors of metastatic regional LNs, three independent predictors of continuous regional LNs, and two independent predictors of skipping regional LNs. Independent predictors were used to build three individualized prediction nomograms. The models showed good calibration and discrimination, with area under the curve (AUC) values of 0.737, 0.738, and 0.707. Application of the nomogram in the validation cohort yielded good calibration and discrimination, with AUC values of 0.728, 0.668, and 0.657. Decision curve analysis demonstrated that the three nomograms were clinically useful in the validation cohort. CONCLUSION: This study presents three nomograms that incorporate clinicopathologic factors, which can be used to facilitate the intraoperative prediction of metastatic regional LN patterns in patients with esophageal cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-020-07738-9. BioMed Central 2021-01-05 /pmc/articles/PMC7786479/ /pubmed/33402129 http://dx.doi.org/10.1186/s12885-020-07738-9 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
Zhao, Fei
Lu, Rong-Xin
Liu, Jin-Yuan
Fan, Jun
Lin, Hao-Ran
Yang, Xiao-Yu
You, Shu-Hui
Wu, Qian-Ge
Qin, Xue-Yun
Liu, Yi
Zhen, Fu-Xi
Luo, Jin-Hua
Wang, Wei
Development and validation of nomograms to intraoperatively predict metastatic patterns in regional lymph nodes in patients diagnosed with esophageal cancer
title Development and validation of nomograms to intraoperatively predict metastatic patterns in regional lymph nodes in patients diagnosed with esophageal cancer
title_full Development and validation of nomograms to intraoperatively predict metastatic patterns in regional lymph nodes in patients diagnosed with esophageal cancer
title_fullStr Development and validation of nomograms to intraoperatively predict metastatic patterns in regional lymph nodes in patients diagnosed with esophageal cancer
title_full_unstemmed Development and validation of nomograms to intraoperatively predict metastatic patterns in regional lymph nodes in patients diagnosed with esophageal cancer
title_short Development and validation of nomograms to intraoperatively predict metastatic patterns in regional lymph nodes in patients diagnosed with esophageal cancer
title_sort development and validation of nomograms to intraoperatively predict metastatic patterns in regional lymph nodes in patients diagnosed with esophageal cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7786479/
https://www.ncbi.nlm.nih.gov/pubmed/33402129
http://dx.doi.org/10.1186/s12885-020-07738-9
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