ArticleFrontiers in oncology2025
Clinical prognosis evaluation of alpha-fetoprotein-positive gastric cancer: comprehensive analysis and development of a novel nomogram for survival prediction.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Circulating IGF2BP3 enables risk stratification and predicts treatment response in Ewing sarcoma.Scientific reports · 2026Article
- Recurrence of gastric cancer with Krukenberg tumor, presenting with a high alpha-fetoprotein level, a case report.Frontiers in oncology · 2026Article
- Molecular pathogenesis and novel therapeutic avenues in alpha-fetoprotein-producing gastric cancer.Frontiers in oncology · 2026Review
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Authors and funding
5 authors.
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Abstract
Background: Alpha-fetoprotein (AFP) is an established biomarker for liver cancer, but its role in gastric cancer (GC) remains unclear. This study evaluated AFP's prognostic value in GC and developed a survival prediction model incorporating AFP and other clinical factors. Methods: We analyzed 766 GC patients from Changzhou Traditional Chinese Medicine Hospital, categorizing them as AFP-positive (>20 ng/mL) or AFP-negative (≤20 ng/mL). Kaplan-Meier and Cox regression analyses assessed the association between AFP levels and overall survival (OS). A nomogram based on identified prognostic factors was created and evaluated using ROC curves, calibration curves, and decision curve analysis (DCA). Results: Among 766 gastric cancer (GC) patients, 3.3% (n=25) exhibited elevated AFP levels (>20 ng/mL). The AFP-positive group demonstrated significantly more aggressive clinicopathological features, including larger tumor size ( Conclusions: AFP is a significant independent prognostic factor in gastric cancer, and its inclusion in a multivariate model enhances survival prediction. The prognostic nomogram developed in this study offers clinicians a valuable tool for predicting patient outcomes and guiding treatment decisions. Further validation and prospective studies are necessary to confirm the model's clinical applicability.
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