Development and validation of nomogram models for predicting overall survival and cancer-specific survival in gastric cancer patients with liver metastases: a cohort study based on the SEER database
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed nomogram models to predict survival for gastric cancer liver metastasis patients. These models show improved accuracy over current staging systems for better clinical decisions.
Area Of Science
- Oncology
- Biostatistics
- Cancer Research
Background
- Gastric cancer liver metastasis (GCLM) presents a significant challenge in cancer care.
- Accurate prognostic prediction is crucial for effective treatment planning and patient management.
Purpose Of The Study
- To develop and validate nomogram models for predicting overall survival (OS) and cancer-specific survival (CSS) in GCLM patients.
- To compare the predictive performance of the developed nomograms against the established American Joint Committee on Cancer (AJCC) staging system.
Main Methods
- Analysis of 5,451 GCLM patients from the SEER database (2010-2015) for model development and internal validation.
- External validation using patient data from two Chinese hospitals (2016-2018).
- Multivariable Cox regression identified eight independent prognostic factors, including age, histology, grade, tumor size, surgery, chemotherapy, and metastasis sites.
Main Results
- The developed nomogram models demonstrated superior predictive accuracy for 1-, 2-, and 3-year OS and CSS compared to the AJCC TNM staging system.
- Internal validation showed significantly better performance metrics for the nomograms (e.g., 1-year OS: 0.801 vs. 0.593, P < 0.001).
Conclusions
- Novel nomogram models have been successfully developed and validated for predicting survival in GCLM patients.
- These nomograms offer enhanced prognostic accuracy, providing a valuable tool for clinical decision-making and patient counseling.
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