ArticleCancers2025
Multi-Steroid Profiling and Machine Learning Reveal Androgens as Candidate Biomarkers for Endometrial Cancer Diagnosis: A Case-Control Study.
Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Steroid hormone profiling reveals altered adrenal androgen production in endometriosis.European journal of endocrinology · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objectiveTo evaluate the diagnostic and prognostic potential of preoperative serum steroid levels in endometrial cancer (EC) alone and in combination with clinical parameters and biomarkers CA-125 and HE4.
methodsThis single-center observational study included 62 patients with EC and 70 controls with benign uterine conditions who underwent surgery between June 2012 and February 2020. Preoperative serum levels of classic androgens, 11-oxyandrogens, glucocorticoids and mineralocorticoids were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Machine learning was used to assess their diagnostic and prognostic value alone and combined with clinical parameters and tumor biomarkers.
resultsPatients with EC had significantly higher serum levels of classic androgens (androstenedione, testosterone), 11-oxyandrogens (11β-hydroxy-androstenedione, 11β-hydroxy-testosterone) and glucocorticoids (17α-hydroxy-progesterone, 11-deoxycortisol) compared to controls. While individual steroids had limited diagnostic value, a multivariate model including classic androgens, CA-125, HE4, BMI and parity achieved an AUC 0.87, 79.1% sensitivity and 74.7% specificity in distinguishing EC from benign uterine condition. This model outperformed our previously published model based on CA-125, HE4 and BMI (AUC: 0.81,
conclusionsPatients with EC exhibit distinct steroid hormone profiles. While steroids alone offer modest diagnostic and prognostic value, integrating them into multivariate models improves diagnostic accuracy.
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