Article Abstract

A nomogram prediction model for recurrent laryngeal nerve lymph node metastasis in thoracic oesophageal squamous cell carcinoma

Authors: Yu Liu, Zhi-Qiang Zou, Juan Xiao, Mei Zhang, Lei Yuan, Xiao-Gang Zhao

Abstract

Background: The metastasis rate to the recurrent laryngeal nerve lymph node (RLN LN) is high, but resection of it is challenging and increases complications. This study explored the risk factors for the RLN LN metastasis in thoracic oesophageal squamous cell carcinoma and developed a novel scoring system to predict it.
Methods: We retrospectively analysed the clinicopathological data of 265 patients between 2015 and 2018. Univariate and multivariate analyses were performed to screen for risk factors and establish a logistic regression model to predict the risk of RLN LN metastasis. A nomogram was constructed accordingly. Further analyses were conducted regarding right and left RLN LN metastasis alone.
Results: (I) The metastatic rates of the left and right RLN LN were 15.1% and 20.4%, respectively. (II) Multivariate logistic regression analysis showed that the short axis diameter of the left RLN LN, short axis diameter of the right RLN LN, maximum diameter of the tumor, tumor location, subcarinal lymph node status and paraoesophageal lymph node status were all independent risk factors for RLN LN metastasis. (III) Multivariate logistic regression analysis showed that the short axis diameter of right RLN LN, tumor location and subcarinal lymph node status were independent risk factors for right RLN LN metastasis. (IV) Multivariate logistic regression analysis showed that short axis diameter of left RLN LN was an independent risk factor for left RLN LN metastasis.
Conclusions: The metastatic rates of the left and right RLN LNs were high and can be predicted according to these nomograms.

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