Predictors of Contralateral Prophylactic Mastectomy in Women With a <i>BRCA1</i> or <i>BRCA2</i> Mutation: The Hereditary Breast Cancer Clinical Study Group
Bibliographic record
Abstract
PURPOSE: To evaluate the rate of prophylactic contralateral mastectomy in an international cohort of women with hereditary breast cancer and to evaluate the predictors of uptake of preventive surgery. PATIENTS AND METHODS: Women with a BRCA1 or BRCA2 mutation who had been diagnosed with unilateral breast cancer were followed prospectively for a minimum of 1.5 years. Information was collected on prophylactic surgery, tamoxifen use, and the occurrence of contralateral breast cancer. RESULTS: Nine hundred twenty-seven women were included in the study; of these, 253 women (27.3%) underwent a contralateral prophylactic mastectomy after the initial diagnosis of breast cancer. There were large differences in uptake of contralateral prophylactic mastectomy by country, ranging from 0% in Norway to 49.3% in the United States. Among women from North America, those who had a prophylactic contralateral mastectomy were significantly younger at breast cancer diagnosis (mean age, 39 years) than were those without preventive surgery (mean age, 43 years). Women who initially underwent breast-conserving surgery were less likely to undergo contralateral prophylactic mastectomy than were women who underwent a mastectomy (12% v 40%; P < 10(-4)). Women who had elected for a prophylactic bilateral oophorectomy were more likely to have had their contralateral breast removed than those with intact ovaries (33% v 18%; P < 10(-4)). CONCLUSION: Age, type of initial breast cancer surgery, and prophylactic oophorectomy are all predictive of prophylactic contralateral mastectomy in women with breast cancer and a BRCA mutation. The acceptance of contralateral preventive mastectomy was much higher in North America than in Europe.
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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 | 0.000 | 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".