ArticlePeerJ2018
A gene expression-based risk model reveals prognosis of gastric cancer.
Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Comprehensive Multiomics Analyses Establish the Optimal Prognostic Model for Resectable Gastric Cancer : Prognosis Prediction for Resectable GC.Annals of surgical oncology · 2024Article
- ISLR interacts with MGAT5 to promote the malignant progression of human gastric cancer AGS cells.Iranian journal of basic medical sciences · 2023Article
- Recognition of DNA Methylation Molecular Features for Diagnosis and Prognosis in Gastric Cancer.Frontiers in genetics · 2021Article
- Single-center versus multi-center data sets for molecular prognostic modeling: a simulation study.Radiation oncology (London, England) · 2020Article
- NOTCH3 is a Prognostic Factor and Is Correlated With Immune Tolerance in Gastric Cancer.Frontiers in oncology · 2020Article
- Article
- A 21‑gene Support Vector Machine classifier and a 10‑gene risk score system constructed for patients with gastric cancer.Molecular medicine reports · 2020Article
- Integrated Analysis Identifies an Immune-Based Prognostic Signature for the Mesenchymal Identity in Gastric Cancer.BioMed research international · 2020Article
- Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma.Cancer cell international · 2020Article
- [Expression of PSMA 7 and its effect on proliferation, invasion, migration and tumorigenesis of gastric cancer].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2019Article
- Development and Validation of a Scoring System Based on 9 Glycolysis-Related Genes for Prognosis Prediction in Gastric Cancer.Technology in cancer research & treatmentArticle
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Authors and funding
4 authors.
Funding
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Abstract
backgroundThe prognosis of gastric cancer is difficult to determine, although clinical indicators provide valuable evidence.
methodsIn this study, using screened biomarkers of gastric cancer in combination with random forest variable hunting and multivariable Cox regression, a risk score model was developed to predict the survival of gastric cancer. Survival difference between high/low-risk groups were compared. The relationship between risk score and other clinicopathological indicators was evaluated. Gene set enrichment analysis (GSEA) was used to identify pathways associated with risk scores.
resultsThe patients with high risk scores (median overall survival: 20.2 months, 95% CI [16.9-26.0] months) tend to exhibit early events compared with those with low risk scores (median survival: 70.0 months, 95% CI [46.9-101] months,
conclusionThe risk score model successfully predicted the survival of 1,294 gastric cancer samples from four independent datasets and is among the most important indicators in clinical clinicopathological information for the prognosis of gastric cancer. To our knowledge, it is the first report to predict the survival of gastric cancer using optimized expression panel.
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