ArticleTherapeutics and clinical risk management2024
A Nomogram Based on Clinicopathological Characteristics for Estimating the Risk of Brain Metastasis from Advanced Gastric Cancer: A Multi-Center Retrospective Clinical Study.
Article in Therapeutics and clinical risk management, 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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Who cites it
2 citing papers in PubMed.
- Imaging Characteristics and Clinical Outcomes in Gastric Cancer with Brain Metastasis: A Propensity Score-Matched Study.Journal of gastrointestinal cancer · 2025Article
- Prediction of tumor deposits in stage I-III gastric cancer: a clinically applicable nomogram integrating clinicopathology outcomes.Frontiers in medicine · 2025Article
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6 authors.
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Abstract
Purpose: Although brain metastasis (BM) from gastric cancer (GC) is relatively uncommon, its incidence has been increasing owing to advancements in treatment modalities. Unfortunately, patients diagnosed with BM from gastric cancer have poor life expectancy. Our study aims to establish a predictive model for brain metastasis in advanced gastric cancer patients, thus enabling the timely diagnosis of brain metastasis. Patients and Methods: The clinicopathological features of a cohort which included 40 GC patients with brain metastasis, 32 of whom from the First Affiliated Hospital of Nanchang University, 2 from Gaoxin Branch of the First Affiliated Hospital of Nanchang University, remaining 6 from Anyang District Hospital, and 80 non-metastatic advanced GC patients from the First Affiliated Hospital of Nanchang University between 2018 and 2022. Data were retrospectively analyzed. Results: Age, tumor size, differentiation, lymph node grade, tumor location, Lauren classification, liver metastasis, carbohydrate antigen 199 (CA199), lactate dehydrogenase (LDH), and human epidermal growth factor receptor 2 (Her-2) were associated with BM. A nomogram integrated with nine risk factors (tumor size, differentiation, lymph node grade, tumor location, Lauren classification, liver metastasis, CA-199, LDH, and Her-2) showed good performance (Area Under Curve 0.95, 95% CI: 0.91-0.98). Conclusion: We developed and validated a nomogram that achieved individualized prediction of the possibility of BM from GC. This model enables personalized imaging review schedules for timely brain metastasis detection in advanced gastric cancer patients.
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