ArticleWorld journal of gastrointestinal oncology2024
Epidemiology and prognostic nomogram for locally advanced gastric signet ring cell carcinoma: A population-based study.
Article in World journal of gastrointestinal oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Development and validation of nomograms for predicting overall survival and cancer-specific survival in female gastric signet-ring cell carcinoma: a SEER database analysis.Translational cancer research · 2026Article
- Explainable Machine Learning Model for Predicting Postoperative Survival in Patients With Locally Advanced Gastric Cancer.Cancer medicine · 2025Article
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5 authors.
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Abstract
backgroundGastric signet ring cell carcinoma (GSRC) represents a specific subtype of gastric cancer renowned for its contentious epidemiological features, treatment principles, and prognostic factors.
aimTo investigate the epidemiology of GSRC and establish an improved model for predicting the prognosis of patients with locally advanced GSRC (LAGSRC) after surgery.
methodsThe annual rates of GSRC incidence and mortality, covering the years 1975 to 2019, were extracted from the Surveillance, Epidemiology, and End Results (SEER) database to explore the temporal trends in both disease incidence and mortality rates using Joinpoint software. The clinical data of 3793 postoperative LAGSRC patients were collected from the SEER database for the analysis of survival rates. The Cox regression model was used to explore the independent prognostic factors for overall survival (OS). The risk factors extracted were used to establish a prognostic nomogram.
resultsThe overall incidence of GSRC increased dramatically between 1975 and 1998, followed by a significant downward trend in incidence after 1998. In recent years, there has been a similarly optimistic trend in GSRC mortality rates. The trend in GSRC showed discrepancies based on age and sex. Receiver operating characteristic curves, calibration curves, and decision curve analysis for 1-year, 3-year, and 5-year OS demonstrated the high discriminative ability and clinical utility of this nomogram. The area under the curve indicated that the performance of the new model outperformed that of the pathological staging system.
conclusionThe model we established can aid clinicians in the early prognostication of LAGSRC patients, resulting in improved clinical outcomes by modifying management strategies and patient health care.
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