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Nomogram for predicting survival after lymphatic metastasis in esophageal cancer: A SEER analysis

Lymphatic metastasis (LM) is a significant mechanism for the spread of esophageal cancer (EC) and predicts the poor prognosis of EC patients. This research aimed to assess the survival of patients with LM from EC by developing a nomogram. In this retrospective study, EC patients with LM from 2004 to...

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Detalles Bibliográficos
Autores principales: Sun, Shuo, Yang, Wenwen, Yang, Yanjiang, Fan, Mengmeng, Wang, Feng, He, Li, Han, Biao, Chen, Chang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402951/
https://www.ncbi.nlm.nih.gov/pubmed/37543759
http://dx.doi.org/10.1097/MD.0000000000034189
Descripción
Sumario:Lymphatic metastasis (LM) is a significant mechanism for the spread of esophageal cancer (EC) and predicts the poor prognosis of EC patients. This research aimed to assess the survival of patients with LM from EC by developing a nomogram. In this retrospective study, EC patients with LM from 2004 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were divided by year of diagnosis into a training cohort and a validation cohort. Univariate and multivariate Cox regression analyses were employed to determine the prognostic factors of LM, and a nomogram was constructed. The discrimination and calibration of the nomogram were compared by the C-index, area under the curve value, and calibration plots. The survival time difference was compared using Kaplan–Meier curves. A total of 11,695 patients with EC were included in this analysis. LM occurred in 56.5% (n = 6614) of EC patients. In the post-propensity score matching (PSM) cohort, patients with LM had significantly lower median overall survival (OS) than those without LM. Multivariate Cox regression was used to identify the eleven independent prognostic factors. The C-index was 0.709 in both the training and test sets, revealing the good predictive performance of the nomogram. Based on the results of calibration plots and the receiver operating characteristic (ROC) curve, we demonstrate the great performance of the prognostic model. The survival time of EC patients with LM was remarkably lower than that of EC patients without LM. The nomogram model established in this study can precisely predict the survival of EC patients with LM.