Retrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma

Abstract This study aimed to identify the risk factors of lymph node metastasis (LNM) in superficial esophageal squamous cell carcinoma and use these factors to establish a prediction model. We retrospectively analyzed the data from training set (n = 280) and validation set (n = 240) underwent radic...

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Autores principales:	Rongwei Ruan, Shengsen Chen, Yali Tao, Jiangping Yu, Danping Zhou, Zhao Cui, Qiwen Shen, Shi Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b68b5d3cbb7e47ea88a62d29a32f7d6b
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spelling	oai:doaj.org-article:b68b5d3cbb7e47ea88a62d29a32f7d6b2021-12-02T15:10:46ZRetrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma10.1038/s41598-021-96088-y2045-2322https://doaj.org/article/b68b5d3cbb7e47ea88a62d29a32f7d6b2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96088-yhttps://doaj.org/toc/2045-2322Abstract This study aimed to identify the risk factors of lymph node metastasis (LNM) in superficial esophageal squamous cell carcinoma and use these factors to establish a prediction model. We retrospectively analyzed the data from training set (n = 280) and validation set (n = 240) underwent radical esophagectomy between March 2005 and April 2018. Our results of univariate and multivariate analyses showed that tumor size, tumor invasion depth, tumor differentiation and lymphovascular invasion were significantly correlated with LNM. Incorporating these 4 variables above, model A achieved AUC of 0.765 and 0.770 in predicting LNM in the training and validation sets, respectively. Adding macroscopic type to the model A did not appreciably change the AUC but led to statistically significant improvements in both the integrated discrimination improvement and net reclassification improvement. Finally, a nomogram was constructed by using these five variables and showed good concordance indexes of 0.765 and 0.770 in the training and validation sets, and the calibration curves had good fitting degree. Decision curve analysis demonstrated that the nomogram was clinically useful in both sets. It is possible to predict the status of LNM using this nomogram score system, which can aid the selection of an appropriate treatment plan.Rongwei RuanShengsen ChenYali TaoJiangping YuDanping ZhouZhao CuiQiwen ShenShi WangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Rongwei Ruan Shengsen Chen Yali Tao Jiangping Yu Danping Zhou Zhao Cui Qiwen Shen Shi Wang Retrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma
description	Abstract This study aimed to identify the risk factors of lymph node metastasis (LNM) in superficial esophageal squamous cell carcinoma and use these factors to establish a prediction model. We retrospectively analyzed the data from training set (n = 280) and validation set (n = 240) underwent radical esophagectomy between March 2005 and April 2018. Our results of univariate and multivariate analyses showed that tumor size, tumor invasion depth, tumor differentiation and lymphovascular invasion were significantly correlated with LNM. Incorporating these 4 variables above, model A achieved AUC of 0.765 and 0.770 in predicting LNM in the training and validation sets, respectively. Adding macroscopic type to the model A did not appreciably change the AUC but led to statistically significant improvements in both the integrated discrimination improvement and net reclassification improvement. Finally, a nomogram was constructed by using these five variables and showed good concordance indexes of 0.765 and 0.770 in the training and validation sets, and the calibration curves had good fitting degree. Decision curve analysis demonstrated that the nomogram was clinically useful in both sets. It is possible to predict the status of LNM using this nomogram score system, which can aid the selection of an appropriate treatment plan.
format	article
author	Rongwei Ruan Shengsen Chen Yali Tao Jiangping Yu Danping Zhou Zhao Cui Qiwen Shen Shi Wang
author_facet	Rongwei Ruan Shengsen Chen Yali Tao Jiangping Yu Danping Zhou Zhao Cui Qiwen Shen Shi Wang
author_sort	Rongwei Ruan
title	Retrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma
title_short	Retrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma
title_full	Retrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma
title_fullStr	Retrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma
title_full_unstemmed	Retrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma
title_sort	retrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b68b5d3cbb7e47ea88a62d29a32f7d6b
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Retrospective analysis of predictive factors for lymph node metastasis in superficial esophageal squamous cell carcinoma

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