ArticleJournal of gastric cancer2023
A Nomogram for Predicting Extraperigastric Lymph Node Metastasis in Patients With Early Gastric Cancer.
Article in Journal of gastric cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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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.
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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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Risk prediction models for lymph node metastasis in early gastric cancer patients: a systematic review and meta-analysis.BMC gastroenterology · 2025Pooled it
- Assessing Lymph Node Metastasis Risk in Patients With Mucosal Gastric Cancer: A Comparison of the WHO and Japanese Criteria and Implications for Endoscopic Submucosal Dissection.JGH open : an open access journal of gastroenterology and hepatology · 2026Article
- Analysis of influencing factors of lymph node metastasis in elderly patients with early gastric cancer and establishment of a prediction model.Discover oncology · 2026Article
- Application and progress of nomograms in gastric cancer.Frontiers in medicine · 2025Review
- Risk Factors for Lymph Node Metastasis in a Western Series of Patients with Distal Early Gastric Cancer.Journal of clinical medicine · 2024Article
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Corrections and comments
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Authors and funding
8 authors at 6 institutions in 2 countries.
Funding
Abstract
backgroundThere are no clear guidelines to determine whether to perform D1 or D1+ lymph node dissection in early gastric cancer (EGC). This study aimed to develop a nomogram for estimating the risk of extraperigastric lymph node metastasis (LNM). MATERIALS AND
methodsBetween 2009 and 2019, a total of 4,482 patients with pathologically confirmed T1 disease at 6 affiliated hospitals were included in this study. The basic clinicopathological characteristics of the positive and negative extraperigastric LNM groups were compared. The possible risk factors were evaluated using univariate and multivariate analyses. Based on these results, a risk prediction model was developed. A nomogram predicting extraperigastric LNM was used for internal validation.
resultsMultivariate analyses showed that tumor size (cut-off value 3.0 cm, odds ratio [OR]=1.886, P=0.030), tumor depth (OR=1.853 for tumors with sm2 and sm3 invasion, P=0.010), cross-sectional location (OR=0.490 for tumors located on the greater curvature, P=0.0303), differentiation (OR=0.584 for differentiated tumors, P=0.0070), and lymphovascular invasion (OR=11.125, P<0.001) are possible risk factors for extraperigastric LNM. An equation for estimating the risk of extraperigastric LNM was derived from these risk factors. The equation was internally validated by comparing the actual metastatic rate with the predicted rate, which showed good agreement.
conclusionsA nomogram for estimating the risk of extraperigastric LNM in EGC was successfully developed. Although there are some limitations to applying this model because it was developed based on pathological data, it can be optimally adapted for patients who require curative gastrectomy after endoscopic submucosal dissection.
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