Profiling of Endogenous Estrogens, Their Precursors, and Metabolites in Endometrial Cancer Patients: Association with Risk and Relationship to Clinical Characteristics
Bibliographic record
Abstract
BACKGROUND: Endometrial cancer (EC) predominantly occurs after menopause and is strongly related to steroid hormones, particularly estrogens. However, the relationship between these hormones and clinical characteristics remains unaddressed. EXPERIMENTAL DESIGN: We analyzed the circulating levels of 18 steroids including adrenal precursors, androgens, estrogens, and their glucuronide metabolites, using specific and validated methods based on tandem mass spectrometry. Our goals were to compare circulating levels in postmenopausal women with EC (n = 126) with those of healthy postmenopausal women (n = 110) and to investigate how these hormonal levels relate to clinical characteristics. RESULTS: After adjustment for potential confounders, most hormones were significantly elevated in EC patients compared with healthy controls. In women with type I cancer, estrogen levels were up to 3-fold those of healthy women (P < 0.05). These higher levels were associated with an increased risk of cancer, particularly estrogens and their direct precursors, testosterone and androstenedione (odds ratios ranging from 4.4 to 13.3; P ≤ 0.0003). Elevated circulating levels of estrogens and their metabolites were found in cancer cases with type I endometrioid cancer and low-grade and noninvasive tumor, suggesting an association between these hormones and the tumoral estrogenic activity. In addition, levels of estrone-sulfate in EC patients with relapse were 2-fold over levels of EC patients without relapse (P < 0.05), and 4.5-fold over those of healthy women (P < 0.001). CONCLUSIONS: Circulating levels of steroids were associated with increased risk of EC. Estrogens may represent novel biomarkers predictive of clinical characteristics, including evidence for an increased risk of relapse.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".