Endogenous sex steroids in premenopausal women and risk of breast cancer: the ORDET cohort
Bibliographic record
Abstract
INTRODUCTION: Previous studies showed that higher testosterone levels are associated with greater risk of breast cancer in premenopausal women, but the literature is scant and inconsistent. METHODS: In a prospective nested case-control study of 104 premenopausal women with incident breast cancer and 225 matched controls, all characterized by regular menstrual cycles throughout their lifetime, we measured the concentration of estradiol, total and free testosterone (FT), progesterone, sex hormone-binding globulin (SHBG), follicle-stimulating hormone (FSH), and luteinizing hormone (LH) in blood samples collected on days 20 through 24 of their cycles. RESULTS: In logistic regression models, the multivariate odds ratios (ORs) of invasive breast cancer for women in the highest tertile of circulating FT compared with the lowest was 2.43 (95% confidence interval (95% CI), 1.15 to 5.10; Ptrend = 0.03), whereas for total testosterone, the association had the same direction but was not statistically significant (OR, 1.27; 95% CI, 0.62 to 2.61; Ptrend = 0.51). Endogenous progesterone was not statistically associated with breast cancer (OR, 1.16; 95% CI, 0.60 to 2.27; Ptrend = 0.75), nor were the other considered hormones. CONCLUSIONS: Consistent with previous prospective studies in premenopausal women and our own earlier investigation, we observed that higher levels of FT are positively associated with breast cancer risk in women with regular menstrual cycles throughout their lifetimes. No evidence of risk was found associated with the other endogenous sex steroids.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".