Associations between Reproductive and Menstrual Factors and Postmenopausal Androgen Concentrations
Bibliographic record
Abstract
BACKGROUND: Reproductive and menstrual characteristics, as well as high circulating estrogen and androgen concentrations, are associated with the risk of breast and ovarian cancer in postmenopausal women. To explore possible etiological relationships between menstrual and reproductive characteristics and cancer risk, we examined associations between menstrual and reproductive factors and serum concentrations of total testosterone, free testosterone, androstenedione, dehydroepiandrosterone (DHEA), and dehydroepiandrosterone sulfate (DHEA-S). METHODS: This study was conducted in 167 postmenopausal women, using data from the pre-randomization visit of an exercise clinical trial. Participants were sedentary, overweight/ obese, and not on hormone therapy. RESULTS: DHEA-S concentrations were 42% higher, total testosterone concentrations were 35% lower, and free testosterone concentrations were 23% lower in women with both ovaries removed compared with those with both remaining (p = 0.01, p = 0.01, and p = 0.03, respectively). Women who had used herbal therapy in the past had, on average, 25% higher concentrations of total and free testosterone than women who had never used these herbal therapies (p = 0.03 and p = 0.004, respectively). No other significant associations were detected. CONCLUSIONS: Overall, this study does not support the hypothesis that reproductive or menstrual factors, with the exception of oophorectomy status, are associated with postmenopausal androgen concentrations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".