Breast Cancer Prognosis in <i>BRCA1</i> and <i>BRCA2</i> Mutation Carriers: An International Prospective Breast Cancer Family Registry Population-Based Cohort Study
Bibliographic record
Abstract
PURPOSE: To compare breast cancer prognosis in BRCA1 and BRCA2 mutation carriers with that in patients with sporadic disease. PATIENTS AND METHODS: An international population-based cohort study was conducted in Canada, the United States, and Australia of 3,220 women with incident breast cancer diagnosed between 1995 and 2000 and observed prospectively. Ninety-three had BRCA1 mutations; 71, BRCA2 mutations; one, both mutations; 1,550, sporadic breast cancer; and 1,505, familial breast cancer (without known BRCA1 or BRCA2 mutation). Distant recurrence and death were analyzed. RESULTS: Mean age at diagnosis was 45.3 years; mean follow-up was 7.9 years. Risks of distant recurrence and death did not differ significantly between BRCA1 mutation carriers and those with sporadic disease in univariable and multivariable analyses. Risk of distant recurrence was higher for BRCA2 mutation carriers compared with those with sporadic disease in univariable analysis (hazard ratio [HR], 1.63; 95% CI, 1.02 to 2.60; P = .04). Risk of death was also higher in BRCA2 carriers in univariable analysis (HR, 1.81; 95% CI, 1.15 to 2.86; P = .01). After adjustment for age, tumor stage and grade, nodal status, hormone receptors, and year of diagnosis, no differences were observed for distant recurrence (HR, 1.00; 95% CI, 0.62 to 1.61; P = 1.00) or death (HR, 1.12; 95% CI, 0.70 to 1.79; P = .64). CONCLUSION: Outcomes of BRCA1 mutation carriers were similar to those of patients with sporadic breast cancer. Worse outcomes in BRCA2 mutation carriers in univariable analysis seem to reflect the presence of more adverse tumor characteristics in these carriers. Similar outcomes were identified in BRCA2 carriers and those with sporadic disease in multivariable analyses.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".