Menopausal hormone therapy and the risk of breast cancer in women with a pathogenic variant in <i>BRCA1</i> or <i>BRCA2</i>
Bibliographic record
Abstract
BACKGROUND: Women with a pathogenic variant in BRCA1 or BRCA2 are at high risk of developing ovarian cancer, and it is often recommended that they undergo bilateral salpingo-oophorectomy at an early age, resulting in surgical menopause. Menopausal hormone replacement therapy (HRT) is an effective way to mitigate the adverse outcomes of early menopause; however, the safety of menopausal HRT on breast cancer risk in this population has not been established. METHODS: We conducted a prospective matched analysis of HRT use following menopause and breast cancer risk in BRCA carriers. Women who initiated HRT were matched one-to-one with women who had not initiated menopausal HRT by gene, year of birth, and age at menopause, resulting in 676 matched pairs. Menopausal HRT use collected by questionnaire included formulation and mode of administration. RESULTS: After a mean of 5.6 years, there were 87 (12.9%) incident breast cancer cases in the 676 exposed women and 128 (18.9%) cases in the 676 unexposed women (P = .002). Compared with unexposed matched control individuals, women who used estrogen alone experienced a statistically significantly decreased risk of breast cancer (hazard ratio = 0.37, 95% CI = 0.24 to 0.57). No protective or adverse effect was associated with the use of estrogen plus progestogen (hazard ratio = 0.94, 95% CI = 0.54 to 1.63). CONCLUSIONS: Our findings suggest no substantial increase in the risk of breast cancer in BRCA carriers with the use of HRT and that estrogen alone might be protective.
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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 | 0.000 | 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) | 0.001 | 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".