The risks of cancer in older women with <i>BRCA</i> pathogenic variants: How far have we come?
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to estimate the cumulative risks of all cancers in women from 50 to 75 years of age with a BRCA1 or BRCA2 pathogenic variant. METHODS: Participants were women with BRCA1 or BRCA2 pathogenic variants from 85 centers in 16 countries. Women were eligible if they had no cancer before the age of 50 years. Participants completed a baseline questionnaire and follow-up questionnaires every 2 years. Women were followed from age 50 until a diagnosis of cancer, death, age 75, or last follow-up. The risk of all cancers combined from age 50 to 75 was estimated using the Kaplan-Meier method. RESULTS: There were 2211 women included (1470 BRCA1 and 742 BRCA2). There were 379 cancers diagnosed in the cohort between 50 and 75 years. The actuarial risk of any cancer from age 50 to 75 was 49% for BRCA1 and 43% for BRCA2. Breast (n = 186) and ovarian (n = 45) were the most frequent cancers observed. For women who had both risk-reducing mastectomy and bilateral salpingo-oophorectomy before age 50, the risk of developing any cancer between age 50 and 75 was 9%. CONCLUSION: Women with a BRCA1 or BRCA2 pathogenic variant have a high risk of cancer between the ages of 50 and 75 years and should be counselled appropriately.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".