ArticleTechnology in cancer research & treatment
Development and Validation of Prognostic Nomograms Based on Lymph Node Ratio for Young Patients with Gastric Cancer: A SEER-Based Study.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Association of lymph node ratio with perioperative outcomes and survival in patients with early-onset gastric cancer: a multicenter retrospective cohort study.Updates in surgery · 2026Article
- Machine Learning-Based Survival Prediction Models for Young Patients With Gastric Cancer: Model Development and Validation Study.JMIR cancer · 2026Article
- Development of a Prognostic Nomogram for Overall Survival in Gastric Cancer Patients Who Underwent Adjuvant Chemoradiotherapy.Journal of gastrointestinal cancer · 2025Article
- Prognostic modeling of early-onset nondistal gastric cancer identifiesFrontiers in immunology · 2025Article
- A prognostic nomogram for predicting overall survival in gastric signet ring cell carcinoma patients: a SEER database and Chinese registry analysis.Frontiers in molecular biosciences · 2025Article
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6 authors.
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Abstract
purposeTo investigate the role of lymph node ratio (LNR) in young patients with gastric cancer (GC) and develop nomograms to predict the survival of young GC patients.
methodsThis retrospective study enrolled stage I-III GC patients before the age of 40 between 2010 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database. Cox proportional hazards models were used to determine the prognosticators and create the nomograms incorporating LNR to predict overall survival (OS) and cancer-specific survival (CSS). The discriminating superiority of the nomograms was examined using calibration curves, C-index, receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and integrated discrimination improvement (IDI) by comparing with the TNM staging. The performance of the nomograms for risk stratification was analyzed by the Kaplan-Meier method.
resultsBased on the significant prognosticators identified in multivariate survival analysis, the nomograms were established and showed LNR as the third strongest predictor. The C-index of the nomograms for OS and CSS were higher than those of the TNM staging (OS: 0.773 vs 0.665; CSS: 0.769 vs 0.666). The ROC curves for the nomograms to predict survival exhibited superior sensitivity and specificity when compared with the TNM staging. The calibration plots, DCA curves, and IDI values of the nomograms also demonstrated adequate fit and ideal net benefit in prediction and clinical utility. The Kaplan-Meier analysis observed remarkable differences in patients divided into different risk subgroups (
conclusionsThese results found the clinical outperformance of the LNR-based nomograms for predicting survival in young stage I-III GC patients. Our nomograms may improve accuracy of survival risk prediction and facilitate individualized care of young stage I-III GC patients.
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