Women with <i>BRCA</i> mutation have better survival rates after double mastectomy
Bibliographic record
Abstract
Women who are diagnosed with early-stage breast cancer and carry a mutation on the BRCA breast cancer gene have a significantly lower chance of dying if they undergo a double mastectomy versus having only 1 breast removed, according to research published in the British Medical Journal.1 Researchers from both the United States and Canada reviewed the 20-year survival of 390 women (from 290 families) with early-stage breast cancer, diagnosed between 1975 and 2009. They were either known carriers of the BRCA1 or BRCA2 mutations or were likely to be carriers and initially were treated with either a single (346 women) or double (44 women) mastectomy. Among the group treated with a single (unilateral) mastectomy, 137 patients went on to have the other breast removed at a later date. The average time from diagnosis to second (contralateral) mastectomy was 2 years. During the 20-year span, 79 women died of breast cancer: 18 women in the double-mastectomy group and 61 women in the singlemastectomy group. The findings indicated that double mastectomy was associated with a 48% reduction in breast cancer death compared with having only 1 breast removed over a 20-year period. As a result, researchers predict that of 100 women treated with double mastectomy, 87 will be alive at 20 years compared with 66 women who have been treated with a single mastectomy. The authors of the study note that double mastectomy should be discussed as an option for young women with a BRCA mutation and early-onset breast cancer; however, they add that further research is needed to confirm their results because of the small number of women in this group. They also suggest that women with newly diagnosed breast cancer may benefit from knowing if they carry a BRCA mutation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".