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: | , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/b68b5d3cbb7e47ea88a62d29a32f7d6b |
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| Sumario: | 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. |
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