ArticleJournal of gastrointestinal oncology2020
The incidence, risk factors and predictive nomograms for early death among patients with stage IV gastric cancer: a population-based study.
Article in Journal of gastrointestinal oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Prediction-model development and temporal validation for six-month cancer-specific mortality inJournal of gastrointestinal oncology · 2026Article
- A prognostic nomogram to predict the cancer-specific survival of patients with initially diagnosed metastatic gastric cancer: a validation study in a Chinese cohort.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- Survival and Treatment Outcomes in Gastric Cancer Patients with Brain Metastases: A Systematic Review and Meta-Analysis.Cancers · 2024Review
- Risk of early death in adolescents and young adults with cancer: a population-based study.Journal of the National Cancer Institute · 2023Article
- Prognostic factors and predictive nomogram models for early death in elderly patients with hepatocellular carcinoma: a population-based study.Frontiers in molecular biosciences · 2023Article
- Nomogram for predicting postoperative cancer-specific early death in patients with epithelial ovarian cancer based on the SEER database: a large cohort study.Archives of gynecology and obstetrics · 2022Article
- A predictive model for early death in elderly patients with gastric cancer: A population-based study.Frontiers in oncology · 2022Article
- Development and validation of a nomogram prediction model for early mortality in patients with primary malignant cardiac tumors.Annals of translational medicine · 2021Article
- Article
- Nomogram Predicting Cancer-Specific Death in Parotid Carcinoma: a Competing Risk Analysis.Frontiers in oncology · 2021Article
- A Competing Risk Nomogram for Predicting Cancer-Specific Death of Patients With Maxillary Sinus Carcinoma.Frontiers in oncology · 2021Article
- Models for Predicting Early Death in Patients With Stage IV Esophageal Cancer: A Surveillance, Epidemiology, and End Results-Based Cohort Study.Cancer control : journal of the Moffitt Cancer CenterArticle
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3 authors.
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Abstract
backgroundAlthough advances in the treatment of stage IV gastric cancer (GC) patients, some patients were observed to die within 3 months of initial diagnosis. The present study aimed to explore the early mortality and risk factors for stage IV GC and further develop nomograms.
methodsA total of 2,174 eligible stage IV GC patients were selected from the Surveillance, Epidemiology, and End Results database. Logistic regression analyses were used to determine the risk factors and develop the nomograms to predict all-cause early death and cancer-specific early death. The predictive performance of the nomograms was assessed by receiver operating characteristic curves (ROC), calibration plots and decision curve analyses (DCA) in both training and validation cohorts.
resultsOf 2,174 patients enrolled, 708 died within 3 months of initial diagnosis (n=668 for cancer-specific early death). Early mortality remained stable from 2010-2015. Non-Asian or Pacific Islander (API) race, poorer differentiation, middle sites of the stomach, no surgery, no radiotherapy, no chemotherapy, lung metastases and liver metastases were associated with high risk of both all-causes early death and cancer-specific early death. The nomograms constructed based on these factors showed favorable sensitivity, with the area under the ROC range of 0.816-0.847. The calibration curves and DCAs also exhibited adequate fit and ideal net benefit in prediction and clinical application.
conclusionsApproximately one-third of stage IV GC patients experienced early death. These associated risk factors and predictive nomograms may help clinicians identify the patients at high risk of early death and be the reference for treatment choices.
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