ArticleJournal of translational internal medicine2025
Associations between serum sex steroid hormone metabolites and gastric cancer and precancerous lesions in men: A 11.8-year prospective study.
Article in Journal of translational internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Article
- Serum Protein Profiling of Patients at Risk to Develop Gastric Disease Based on a DSC Test.International journal of molecular sciences · 2026Article
- Establishment of a Gastric Cancer Diagnostic Model Based on the Combined Evaluation of Peripheral Blood Immune-inflammatory Nutritional Indicators and Tumor Markers.Journal of cancer prevention · 2026Article
- Plasma fatty acid associated with risk of gastrointestinal cancer: a prospective cohort study from UK Biobank.Translational cancer research · 2026Article
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Authors and funding
12 authors.
Funding
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Abstract
Background and objectives: Sex steroid hormones have been hypothesized to be associated with the risk of gastric cancer (GC); however, it has not been widely validated in prospective studies. We aimed to investigate the associations between sex steroid hormone metabolites and the risk of gastric cancer and precancerous lesions in a prospective cohort of Chinese men. Methods: Using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and electrochemical luminescence immunoassay, we examined 20 sex steroid hormone metabolites and sex hormone-binding globulin (SHBG) in serum from 470 eligible men, including high-grade lesions or GC ( Results: In the cross-sectional analysis, androstenedione levels were potentially associated with IM risk and significantly associated with high-grade lesions or GC risk (OR Conclusions: Several sex hormone metabolites were significantly associated with gastric cancer and its precancerous lesions, indicating a role for sex hormones in gastric carcinogenesis and potentially providing novel biomarkers for the identification of high-risk populations and risk prediction for GC.
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