Family History of Cancer and Cancer Risks in Women with BRCA1 or BRCA2 Mutations
Bibliographic record
Abstract
Women who carry a deleterious mutation in BRCA1 or BRCA2 have high lifetime risks of breast and ovarian cancers. However, the influence of a family history of these cancers on these risks in women with BRCA mutations is unclear. We calculated cancer incidence rates for a multinational cohort comprising 3011 women with BRCA1 or BRCA2 mutations who were followed up for a mean of 3.9 years, during which time 243 incident breast or ovarian cancers were recorded. The 10-year cumulative risks of breast cancer were 18.1% (95% confidence interval [CI] = 13.3% to 22.8%) for women with a BRCA1 mutation and 15.2% (95% CI = 9.1% to 21.2%) for women with a BRCA2 mutation. Among women with a BRCA1 mutation, the risk of breast cancer increased by 1.2-fold for each first-degree relative with breast cancer before age 50 years (hazard ratio [HR] = 1.21; 95% confidence interval [CI] = 0.94 to 1.57) and the risk of ovarian cancer increased by 1.6 fold for each first- or second-degree relative with ovarian cancer (HR = 1.61; 95% CI = 1.21 to 2.14). Among women with a BRCA2 mutation, the risk of breast cancer increased by 1.7-fold for each first-degree relative younger than 50 years with breast cancer (HR = 1.67; 95% CI = 1.04 to 2.07).
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".