ArticleEuropean journal of medical research2025
Establishment and validation of a novel prognostic nomogram for gallbladder cancer patients.
Article in European journal of medical research, 2025. 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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Who cites it
2 citing papers in PubMed.
- Development and validation of a novel nomogram for predicting long-term survival in gallbladder cancer: a large population-based study using the SEER database.Journal of gastrointestinal oncology · 2026Article
- Development and validation of a nomogram for predicting postoperative survival in gallbladder cancer.Translational gastroenterology and hepatology · 2026Article
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7 authors.
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Abstract
backgroundGallbladder cancer (GBC) arises from the malignant transformation of epithelial cells that line the gallbladder mucosa. The likelihood of developing GBC escalates with advancing age, and the condition generally presents a dismal prognosis. Despite this, there is a limited amount of research focusing on the prognostic determinants linked to GBC. As a result, this study sought to create a nomogram for evaluating GBC prognostic factors.
methodsIn this investigation, a total of 8,615 cases of GBC from the Surveillance, Epidemiology, and End Results (SEER) database spanning from 2000 to 2020 were collected. In a 7:3 ratio, these instances were randomly assigned to one of two groups: training or internal validation. To assess the impact of clinical variables on overall survival (OS) in patients with GBC, both univariate and multivariate Cox regression analyses were utilized. The clinical criteria established were used to develop a nomogram. The effectiveness of the nomogram was evaluated through several approaches, such as receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, and Kaplan-Meier (KM) analysis.
resultsTo predict the prognosis of GBC patients, a nomogram was created based on the following criteria: sex, rural-urban continuum, marital status, nodes, histology, radiation, chemotherapy, metastasis, age, surgery, and grade. The training set had an area under the curve for 1-year, 3-year, and 5-year OS of 0.79, 0.78, and 0.78, respectively. The DCA curves demonstrated that the model was clinically useful and well-corrected. Patients with GBC were categorized into high-risk and low-risk groups based on the median risk score. KM curves revealed a significantly lower survival rate for the high-risk group in comparison with the low-risk group (P < 0.001).
conclusionsOur model demonstrated strong predictive capabilities for the prognosis of GBC patients, thereby aiding in the refinement of treatment strategies for these individuals.
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