A dynamic nomogram for predicting abdominal lymph node recurrence in patients with esophageal carcinoma

Patients with middle and lower thoracic esophageal carcinoma (TEC) after surgery are prone to develop abdominal lymph node recurrence (LNR). However, questions remain regarding the indications for postoperative abdominal radiotherapy. We aimed to identify the risk factors for abdominal LNR and to develop a dynamic nomogram for predicting abdominal LNR. We reviewed 1004 patients with middle and lower TEC treated with three-field lymph node dissection between January 2010 and December 2020 at two clinical centers. Risk factors for abdominal LNR were identified using least absolute shrinkage and selection operator (LASSO) logistic regression analysis. A dynamic nomogram was then developed. Performance was evaluated using receiver operating characteristic (ROC) curve , calibration curve and decision curve analysis. The rates of abdominal LNR in the training, internal test and external test cohorts were 25.91%, 23.40% and 23.98%, respectively. A dynamic nomogram was developed to predict the abdominal LNR in patients with middle and lower TEC. The main predictors included tumor location, pathologic N stage and number of preoperative abdominal LNM. The AUC of the training, internal test, and external test cohorts were 0.767 (95%CI 0.7263-0.8079), 0.763 (95%CI 0.7002-0.8258) and 0.802 (95%CI 0.7419-0.8629), respectively. Furthermore, The calibration curves and DCA analysis indicated a favorable fit and significant clinical applicability of the nomogram. The dynamic nomograms is available at https://prediction-of-abdiminal-lymph-node-metastasis-in-tec.shinyapps.io/DynNomapp/ . Tumor location, pathologic N stage and number of preoperative abdominal LNM were identified as risk factors for predicting abdominal LNR. The online dynamic nomograms showed good prediction performance and convenient clinical application, which may help clinicians identify patients who require adjuvant abdominal radiotherapy.

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Publication Details

Journal
Scientific Reports
Published
2025-04-18
DOI
https://doi.org/10.1038/s41598-025-97774-x
Primary Topic
Esophageal Cancer Research and Treatment
Type
article
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article

A dynamic nomogram for predicting abdominal lymph node recurrence in patients with esophageal carcinoma

Ming-Qiang Lin, Qing‐Hua Xu, Mei Qu, Bao-An Su et al.
Scientific Reports
Esophageal Cancer Research and Treatment
article

A dynamic nomogram for predicting abdominal lymph node recurrence in patients with esophageal carcinoma

Ming-Qiang Lin, Qing‐Hua Xu, Mei Qu, Bao-An Su, Ju-Hui Chen, Jiancheng Li, Zhi-Chen Xu
article en

Abstract

Patients with middle and lower thoracic esophageal carcinoma (TEC) after surgery are prone to develop abdominal lymph node recurrence (LNR). However, questions remain regarding the indications for postoperative abdominal radiotherapy. We aimed to identify the risk factors for abdominal LNR and to develop a dynamic nomogram for predicting abdominal LNR. We reviewed 1004 patients with middle and lower TEC treated with three-field lymph node dissection between January 2010 and December 2020 at two clinical centers. Risk factors for abdominal LNR were identified using least absolute shrinkage and selection operator (LASSO) logistic regression analysis. A dynamic nomogram was then developed. Performance was evaluated using receiver operating characteristic (ROC) curve , calibration curve and decision curve analysis. The rates of abdominal LNR in the training, internal test and external test cohorts were 25.91%, 23.40% and 23.98%, respectively. A dynamic nomogram was developed to predict the abdominal LNR in patients with middle and lower TEC. The main predictors included tumor location, pathologic N stage and number of preoperative abdominal LNM. The AUC of the training, internal test, and external test cohorts were 0.767 (95%CI 0.7263-0.8079), 0.763 (95%CI 0.7002-0.8258) and 0.802 (95%CI 0.7419-0.8629), respectively. Furthermore, The calibration curves and DCA analysis indicated a favorable fit and significant clinical applicability of the nomogram. The dynamic nomograms is available at https://prediction-of-abdiminal-lymph-node-metastasis-in-tec.shinyapps.io/DynNomapp/ . Tumor location, pathologic N stage and number of preoperative abdominal LNM were identified as risk factors for predicting abdominal LNR. The online dynamic nomograms showed good prediction performance and convenient clinical application, which may help clinicians identify patients who require adjuvant abdominal radiotherapy.

Scientific ReportsVol. 15(1)
Fujian Medical University (CN), Fujian Provincial Cancer Hospital (CN)
Good health and well-being
Openalex Percentile: Top 86%
Esophageal Cancer Research and Treatment
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