Breast cancer survival in carriers of BRCA1 and BRCA2 mutations
Bibliographic record
Abstract
10552 Background: The characteristic pathologic features of breast cancers in women with a BRCA1 mutation suggest that women with hereditary breast cancer might have a worse than expected prognosis, but the results of clinical studies have been inconsistent. The current study is a national population-based study of Israeli women aimed at evaluating the impact of the inheritance of a BRCA1 or a BRCA2 mutation on breast cancer prognosis. Methods: All incident cases of invasive breast cancer diagnosed in Israel from January 1, 1987 to December 31, 1988 were identified. Paraffin-embedded tumor blocks or unstained slides and pathology and oncology records were requested for all patients. DNA was extracted from each paraffin block and was analyzed for three founder Jewish mutations in BRCA1 and BRCA2. Of 2,514 diagnosed cases, a pathology sample was retrieved from 1,794 (71.4%) and the medical record was retrieved for 1,545 of these (86.1%). Results: A BRCA1 or BRCA2 mutation was identified in 10% of Ashkenazi women with breast cancer, including 18% of women diagnosed below the age of 50. The adjusted hazard ratio for breast cancer-specific survival was not different for non-carriers and carriers of a BRCA1 (HR = 0.8, 95% CI: 0.5 - 1.3, p = 0.3) or BRCA2 (HR = 1.3, 95% CI: 0.8 - 2.2, p = 0.3) mutation. Among women who were treated with CMF/CAF chemotherapy, BRCA1 carriers experienced better survival than non-carriers (HR = 0.5; 95% CI 0.2–1.2) but the difference did not reach statistical significance (p = 0.1). Tumor size (>2 cm) was a significant predictor of breast cancer specific mortality in non-carriers (HR = 2.8; 95%CI: 2.2 to 3.5) but not in BRCA1 carriers (HR = 1.1; 95% CI 0.5 to 2.8). ER status also did not play a significant predictive role in survival of carriers. Conclusions: Compared to non-carriers, women with breast cancer who carry a founder Jewish mutation in one of the BRCA genes experience similar or possibly even lower breast cancer-specific mortality rate, in spite of a bad profile of prognostic factors. No significant financial relationships to disclose.
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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 | 0.001 |
| 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) | 0.002 | 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".