Increased cancer risks for relatives of very early-onset breast cancer cases with and without BRCA1 and BRCA2 mutations
Bibliographic record
Abstract
BACKGROUND: Little is known regarding cancer risks for relatives of women with very early-onset breast cancer. METHODS: We studied 2208 parents and siblings of 504 unselected population-based Caucasian women with breast cancer diagnosed before age 35 years (103 from USA, 124 from Canada and 277 from Australia), 41 known to carry a mutation (24 in BRCA1, 16 in BRCA2 and one in both genes). Cancer-specific standardised incidence ratios (SIRs) were estimated by comparing the number of affected relatives (50% verified overall) with that expected based on incidences specific for country, sex, age and year of birth. RESULTS: For relatives of carriers, the female breast cancer SIRs were 13.13 (95% CI 6.57-26.26) and 12.52 (5.21-30.07) for BRCA1 and BRCA2, respectively. The ovarian cancer SIR was 12.38 (3.1-49.51) for BRCA1 and the prostate cancer SIR was 18.55 (4.64-74.17) for BRCA2. For relatives of non-carriers, the SIRs for female breast, prostate, lung, brain and urinary cancers were 4.03 (2.91-5.93), 5.25 (2.50-11.01), 7.73 (4.74-12.62), 5.19 (2.33-11.54) and 4.35 (1.81-10.46), respectively. For non-carriers, the SIRs remained elevated and were statistically significant for breast and prostate cancer when based on verified cancers. CONCLUSION: First-degree relatives of women with very early-onset breast cancer are at increased risk of cancers not explained by BRCA1 and BRCA2 mutations.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".