366 CLINICAL NOMOGRAM MODEL FOR RECURRENT LARYNGEAL NERVE LYMPH NODE METASTASIS IN ESOPHAGEAL SQUAMOUS CELL CARCINOMA: A RETROSPECTIVE MULTICENTER STUDY. (14th September 2020)

• Record Type: Journal Article
• Authors: Tian, D; He, X; Yang, Y; Chen, L
• Is Part Of: Diseases of the esophagus. Volume 33(2020)Supplement 1
• Publication Date: 2020-09-14
• Subjects: Esophagus -- Diseases -- Periodicals; 616.32
• DOI: 10.1093/dote/doaa087.85
• Languages: English
• ISSNs: 1120-8694

Abstract

Abstract: : Recurrent laryngeal nerve lymph node metastasis (RLN LNM) is not rare in patients with esophageal cancer. We aimed to explore the risk factors for RLN LNM and to develop a nomogram predicting the likelihood of RLN LNM in esophageal squamous cell carcinoma (ESCC) patients. Methods: We retrospectively reviewed patients with ESCC who underwent esophagectomy as well as recurrent laryngeal nerve lymph node dissection between May 2015 and February 2019 at two different institutions. The patients were divided into negative and positive groups according to the presence of RLN LNM. Risk factors for RLN LNM were evaluated by univariate and multivariate analyses. A nomogram was constructed for presentation of the final model. Results: A total of 390 patients with ESCC were included in this study. The differences in tumor location, tumor differentiation, T stage, tumor size and carcinoembryonic antigen (CEA) between the negative (N = 270) and positive groups (N = 120) RLN LNM were significant (P < 0.05). Multivariate analysis indicated that the tumor location (OR = 0.520, 95% CI: 0.361–0.749, P < 0.001), tumor differentiation (OR = 2.279, 95% CI: 1.586–3.276, P < 0.001), T stage (OR = 1.436, 95% CI: 1.029–2.003, P = 0.033), tumor size (OR = 1.781, 95% CI: 1.021–3.106, P = 0.042) and CEA (OR = 1.206, 95% CI: 1.003–1.450, P = 0.046) were independent risk factors for RLN LNM. A nomogram with these variables had good predictive accuracy (c-index: 0.716). Conclusion: Tumor location, tumor differentiation, T stage, tumor size and CEA may predict the risk of RLN LNM. We created a nomogram predicting the likelihood of RLN LNM in patients with ESCC.