ArticleMedical science monitor : international medical journal of experimental and clinical research2020
A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Prediction-model development and temporal validation for six-month cancer-specific mortality inJournal of gastrointestinal oncology · 2026Article
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- Construction of a novel nomogram for predicting overall survival in patients with Siewert type II AEG based on LODDS: a study based on the seer database and external validation.Frontiers in oncology · 2024Article
- Construction of a nomogram with IrAE and clinic character to predict the survival of advanced G/GEJ adenocarcinoma patients undergoing anti-PD-1 treatment.Frontiers in immunology · 2024Article
- Development and validation of nomogram models to predict radiotherapy or chemotherapy benefit in stage III/IV gastric adenocarcinoma with surgery.Frontiers in oncology · 2023Article
- Risk factors and predictive nomograms for early death of patients with advanced hepatocellular carcinoma: a large retrospective study based on the SEER database.BMC gastroenterology · 2022Article
- A predictive model for early death in elderly patients with gastric cancer: A population-based study.Frontiers in oncology · 2022Article
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6 authors.
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Abstract
BACKGROUND The study was intended to establish predictive nomogram models for predicting total early mortality (the probability of surviving less than or equal to 3 months) and cancer-specific early mortality in patients with stage IV gastric cancer. This was the first study to establish prognostic survival in patients with stage IV gastric cancer. MATERIAL AND METHODS Patients from the SEER database were identified using inclusion and exclusion criteria. Their clinical characteristics were statistically analyzed. The Kaplan-Meier method and the log-rank test were used to compare the influences of different factors on survival time. Logistic regression models were conducted to explore the correlative factors of early mortality. A nomogram was established based on factors significant in the logistic regression model and an internal validation was performed. RESULTS Of the 11,036 eligible patients included in the study, 4932(44.7%) patients resulted in total early death (42.6% died of the cancer and 2.1% died of other reasons). Larger tumor size, poor differentiation, and liver metastasis were positively related to cancer-specific early mortality. Surgery was negatively related to total early mortality and cancer-specific early mortality, while cardia was only negatively associated with total early death. Predictive nomogram models for total early mortality and cancer-specific early mortality have been validated internally. The areas under the receiver operating characteristics curve were 73.5%, and 68.0%, respectively, and the decision curve analysis also proved the value of the models. CONCLUSIONS The nomogram models proved to be a suitable tool for predicting the early mortality in stage IV gastric cancer.
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