ArticleWorld journal of gastrointestinal oncology2023
Nomogram established using risk factors of early gastric cancer for predicting the lymph node metastasis.
Article in World journal of gastrointestinal oncology, 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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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 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
- VPS9D1-AS1: a critical oncogenic long non-coding RNA in human malignancies.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- 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
- Combining biomarkers to construct a novel predictive model for predicting preoperative lymph node metastasis in early gastric cancer.Frontiers in oncology · 2025Article
- Early gastric cancer recurrence after endoscopic submucosal dissection: Not to be ignored!World journal of gastrointestinal oncology · 2024Article
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFor the prognosis of patients with early gastric cancer (EGC), lymph node metastasis (LNM) plays a crucial role. A thorough and precise evaluation of the patient for LNM is now required.
aimTo determine the factors influencing LNM and to construct a prediction model of LNM for EGC patients.
methodsClinical information and pathology data of 2217 EGC patients downloaded from the Surveillance, Epidemiology, and End Results database were collected and analyzed. Based on a 7:3 ratio, 1550 people were categorized into training sets and 667 people were assigned to testing sets, randomly. Based on the factors influencing LNM determined by the training sets, the nomogram was drawn and verified.
resultsBased on multivariate analysis, age at diagnosis, histology type, grade, T-stage, and size were risk factors of LNM for EGC. Besides, nomogram was drawn to predict the risk of LNM for EGC patients. Among the categorical variables, the effect of grade (well, moderate, and poor) was the most significant prognosis factor. For training sets and testing sets, respectively, area under the receiver-operating characteristic curve of nomograms were 0.751 [95% confidence interval (CI): 0.721-0.782] and 0.786 (95%CI: 0.742-0.830). In addition, the calibration curves showed that the prediction model of LNM had good consistency.
conclusionAge at diagnosis, histology type, grade, T-stage, and tumor size were independent variables for LNM in EGC. Based on the above risk factors, prediction model may offer some guiding implications for the choice of subsequent therapeutic approaches for EGC.
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