Impact of BRCA1 mutation on survival after early onset breast cancer
Bibliographic record
Abstract
3354 patients were enrolled in the study, of whom 234 (7.0%) were found to carry a BRCA1 founder mutation. The average age of diagnosis was 44 years (range 21 to 50 years). The ten-year survival for mutation carriers was 80.9% (95% CI 75.4% to 86.4%) and for non-carriers was 82.1% (95% CI 80.5% to 83.7%). After adjusting for other prognostic variables, the hazard ratio associated with carrying a BRCA1 mutation was 1.40 (95% CI: 0.99 to 1.99). Among BRCA1 mutation carriers, in the multivariable analysis, positive lymph node status was a strong predictor of mortality (HR = 4.6; 95% 2.1 to 10.0). Among BRCA1 carriers with a small (< 2 cm) node-negative breast cancer, the ten-year survival rate was 91.7% and tumour size was not predictive of survival (HR = 1.01 for 1-2 cm versus 0-1 cm tumors). Chemotherapy was associated with improved survival in BRCA1 carriers (adjusted HR = 0.31; 95% CI 0.10 – 1.00) but not in non-carriers (HR = 1.69; 95% CI 0.95 to 2.99). The interaction between chemotherapy, mutation status and survival was statistically significant (p = 0.009). The survival of women with breast cancer and a BRCA1 mutation is similar to that of patients without a BRCA1 mutation. For women with a small, node-negative breast cancer and a BRCA1 mutation, the ten-year survival rate was 91.7%. Among women with a BRCA1 mutation, survival was better for women who received chemotherapy than for women who did not receive chemotherapy. Future studies should investigate what is the optimum chemotherapy regimen.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".