ArticleCancer medicine2023
Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population-based study.
Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A migration/invasion-related prognostic signature identifies and functionally validates SLC25A5 as a hub associated with spliceosome programs and invasive phenotypes in esophageal squamous cell carcinoma.Functional & integrative genomics · 2026Article
- Development and validation of nomograms integrating electrolyte, nutritional, and inflammatory indicators to predict survival in advanced esophageal cancer undergoing immunotherapy or radioimmunotherapy.Journal of thoracic disease · 2026Article
- Therapeutic outcomes of different treatment approaches for T1a-M3/T1b esophageal cancer and development of a prognostic prediction model.NPJ digital medicine · 2025Article
- Machine learning-based model for predicting distant lymph node metastasis in esophageal cancer.Journal of thoracic disease · 2025Article
- Deep learning-based prediction of enhanced CT scans for lymph node metastasis in esophageal squamous cell carcinoma.Japanese journal of radiology · 2025Article
- CT-Based Habitat Radiomics Combining Multi-Instance Learning for Early Prediction of Post-Neoadjuvant Lymph Node Metastasis in Esophageal Squamous Cell Carcinoma.Bioengineering (Basel, Switzerland) · 2025Article
- Development and validation of a prognostic model for patients with cT1-4N1-3M1 esophageal squamous cell carcinoma: based on the SEER database and the Chinese cohort study.Frontiers in oncology · 2025Article
- Prediction of lymph node metastasis in early esophageal cancer.World journal of gastrointestinal surgery · 2023Article
- Machine learning was used to predict risk factors for distant metastasis of pancreatic cancer and prognosis analysis.Journal of cancer research and clinical oncology · 2023Article
- Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population-based study.Cancer medicine · 2023Article
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9 authors.
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Abstract
backgroundPatients with early esophageal cancer (EC) receive individualized therapy based on their lymph node metastasis (LNM) and distant metastasis (DM) status; however, deficiencies in current clinical staging techniques and the issue of cost-effectiveness mean LNM and DM often go undetected preoperatively. We aimed to develop three clinical models to predict the likelihood of LNM, DM, and prognosis in patients with early EC.
methodThe Surveillance, Epidemiology, and End Results database was queried for T1 EC patients from 2004 to 2015. Multivariable logistic regression and Cox proportional hazards models were used to recognize the risk factors of LNM and DM, predict overall survival (OS), and develop relevant nomograms. Receiver operating characteristic (ROC)/concordance index and calibration curves were used to evaluate the discrimination and accuracy of the three nomograms. Decision curve analyses (DCAs), clinical impact curves, and subgroups based on model scores were used to determine clinical practicability.
resultsThe area under the curve of the LNM and DM nomograms were 0.668 and 0.807, respectively. The corresponding C-index of OS nomogram was 0.752. Calibration curves and DCA showed an effective predictive accuracy and clinical applicability. In patients with T1N0M0 EC, surgery alone (p < 0.01) proved a survival advantage. Chemotherapy and radiotherapy indicated a better prognosis in the subgroup analysis for T1 EC patients with LNM or DM.
conclusionsWe created three nomograms to predict the likelihood of LNM, DM, and OS probability in patients with early EC using a generalizable dataset. These useful visual tools could help clinical physicians deliver appropriate perioperative care.
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