Factors associated with use of hormone therapy after preventive oophorectomy in BRCA mutation carriers
Bibliographic record
Abstract
OBJECTIVE: Bilateral salpingo-oophorectomy (oophorectomy) is recommended to women with a germline BRCA1 or BRCA2 mutation before natural menopause to prevent ovarian and fallopian tube cancer. The adverse effects of early surgical menopause are well established. Although many of the side effects can be ameliorated by the use of hormone therapy (HT); use of HT in this group of predominantly young patients remains suboptimal. The goal of this study was to identify the frequency of HT use, as well as predictors of HT uptake in BRCA mutation carriers who underwent preventive oophorectomy before natural menopause. METHODS: Eligible participants were identified from a longitudinal study of BRCA mutation carriers. We included premenopausal women with no personal history of cancer who underwent oophorectomy before age 50 and who had a minimum of 2 years of follow-up. Detailed information on HT use and other important variables was collected by a research questionnaire every 2 years. Descriptive statistics were used to evaluate the use of HT in various subgroups. RESULTS: A total of 793 women with a BRCA1 or BRCA2 mutation were included in this analysis. The mean age at oophorectomy was 42 years (range 28-49). Sixty-one percent of the women reported using HT after oophorectomy. Factors associated with HT use included young age at surgery, a high level of education and preventive mastectomy. CONCLUSIONS: The uptake of HT after oophorectomy in women with a BRCA1 or BRCA2 mutation varies by age, education, and surgical history. Clinician and patient awareness may lead to better utilization of HT in women who undergo oophorectomy at an early age to help mitigate the adverse effects associated with surgical menopause.
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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 | 0.003 |
| 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) | 0.002 | 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".