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 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 | 0.001 |
| 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 | 0.001 |
| 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".