Effect of Prior Bilateral Oophorectomy on the Presentation of Breast Cancer in BRCA1 and BRCA2 Mutation Carriers
Bibliographic record
Abstract
PURPOSE: To compare the presentation of invasive breast cancer in BRCA1 and BRCA2 mutation carriers with and without prior bilateral oophorectomy. PATIENTS AND METHODS: Women with a BRCA1 or BRCA2 mutation with the diagnosis of invasive breast cancer were identified from ten cancer genetics clinics. The medical history, medical treatment records and pathology reports for the breast cancers were reviewed. Information was abstracted from medical charts, including history (and date) of oophorectomy, date of breast cancer diagnosis, stage of disease, and pathologic characteristics of the breast cancer. Women with prior bilateral oophorectomy were matched by age, year of diagnosis, and mutation with one or more women who had two intact ovaries at the time of breast cancer diagnosis. Characteristics of the breast tumours were compared between the two groups. RESULTS: Women with prior bilateral oophorectomy presented with smaller tumours on average compared to women without prior oophorectomy (mean size 1.50 cm vs. 1.95 cm; p = 0.01). Additionally, although not statistically significant, women with intact ovaries were more likely to have high-grade tumour (70% vs. 54%: p = 0.10) and to have positive lymph nodes (34% vs. 18%; p = 0.11) compared to women with prior bilateral oophorectomy. CONCLUSIONS: Bilateral oophorectomy prior to breast cancer appears to favourably influence the biological presentation of breast cancer in BRCA1 and BRCA2 mutation carriers.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".