ArticleBMC cancer2021
A nomogram to predict lymph node metastasis risk for early esophageal squamous cell carcinoma.
Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06256185 (Machine Learning to Predict Lymph Node Metastasis in T1 Esophageal Squamous Cell Carcinoma), which is not on this map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Machine Learning to Predict Lymph Node Metastasis in T1 Esophageal Squamous Cell Carcinoma: A Multicenter Study
Who cites it
15 citing papers in PubMed.
- Incidence of lymph node metastases in pT1 chemo- and radiotherapy-naïve esophageal and gastric cancer in the Nordic countries: a retrospective multinational cohort analysis.Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus · 2026Observational
- Accuracy of machine learning in detecting lymph node metastasis of esophageal cancer: a systematic review and meta-analysis.Translational cancer research · 2026Article
- Machine learning to predict distant metastasis risk and prognostic analysis in T1-2 esophageal cancer: a study based on the SEER database.Journal of thoracic disease · 2026Article
- Next step after endoscopic resection for superficial esophageal squamous cell carcinoma: metastatic risk assessment and management of non-curative resection cases.Clinical endoscopy · 2026Review
- Individual risk stratification to predict metastasis for ESD of superficial esophageal squamous cell carcinoma.Esophagus : official journal of the Japan Esophageal Society · 2025Article
- Deep learning-based prediction of enhanced CT scans for lymph node metastasis in esophageal squamous cell carcinoma.Japanese journal of radiology · 2025Article
- Lymphatic Metastasis of Esophageal Squamous Cell Carcinoma: The Role of NRF2 and Therapeutic Strategies.Cancers · 2025Review
- Transcriptome analysis and artificial intelligence for predicting lymph node metastasis of esophageal squamous cell carcinoma.Journal of thoracic disease · 2025Article
- Comprehensive pathological evaluation of risk factors for metastasis after endoscopic resection of superficial esophageal squamous cell carcinoma.Journal of gastroenterology · 2025Article
- Establishment of a nomogram model to predict malignant risk in patients with ocular surface squamous neoplasia and ocular surface squamous epithelial tumors.Frontiers in oncology · 2025Article
- Latest guideline of endoscopic submucosal dissection of early gastric cancer may not be suitable for Chinese patients: retrospective study findings from two centers.Surgical endoscopy · 2024Article
- Clinical models to predict lymph nodes metastasis and distant metastasis in newly diagnosed early esophageal cancer patients: A population-based study.Cancer medicine · 2023Article
- Lymphatic Drainage System and Lymphatic Metastasis of Cancer Cells in the Mouse Esophagus.Digestive diseases and sciences · 2023Article
- A Machine Learning-Based Predictive Model for Predicting Lymph Node Metastasis in Patients With Ewing's Sarcoma.Frontiers in medicine · 2022Article
- Prognostic Model and Nomogram for Early-Onset Adenoid Cystic Carcinoma of Head and Neck: A Retrospective SEER-Based Analysis.Technology in cancer research & treatmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA nomogram was developed to predict lymph node metastasis (LNM) for patients with early-stage esophageal squamous cell carcinoma (ESCC).
methodsWe used the clinical data of ESCC patients with pathological T1 stage disease who underwent surgery from January 2011 to June 2018 to develop a nomogram model. Multivariable logistic regression was used to confirm the risk factors for variable selection. The risk of LNM was stratified based on the nomogram model. The nomogram was validated by an independent cohort which included early ESCC patients underwent esophagectomy between July 2018 and December 2019.
resultsOf the 223 patients, 36 (16.1%) patients had LNM. The following three variables were confirmed as LNM risk factors and were included in the nomogram model: tumor differentiation (odds ratio [OR] = 3.776, 95% confidence interval [CI] 1.515-9.360, p = 0.004), depth of tumor invasion (OR = 3.124, 95% CI 1.146-8.511, p = 0.026), and tumor size (OR = 2.420, 95% CI 1.070-5.473, p = 0.034). The C-index was 0.810 (95% CI 0.742-0.895) in the derivation cohort (223 patients) and 0.830 (95% CI 0.763-0.902) in the validation cohort (80 patients).
conclusionsA validated nomogram can predict the risk of LNM via risk stratification. It could be used to assist in the decision-making process to determine which patients should undergo esophagectomy and for which patients with a low risk of LNM, curative endoscopic resection would be sufficient.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.