The Risk of Breast Cancer According to Mutation Type and Position in Carriers of a Pathogenic Variant in BRCA1
Bibliographic record
Abstract
Background: Carriers of a pathogenic variant (PV) in BRCA1 face a high risk of breast cancer. This study estimated the risk of developing breast cancer according to mutation type and location. Methods: BRCA1 carriers with no personal history of breast cancer or bilateral mastectomy were included. Detailed information on clinical and family history was collected by questionnaire. Survival analysis was used to estimate 15-year cumulative risk according to PV type and location. Results: A total of 3677 BRCA1 carriers were followed for a mean of 7.2 years (range 0.1–15.0 years); 481 incident breast cancers were documented. Overall, the 15-year cumulative incidence was 25%. Risk estimates varied by exon, ranging from 9% (exon 21) to 19% (exon 12) to 36% (exon 15); however, strata were small. Carriers of four founder mutations common in Eastern Europe (c.5263_5264insC, c.181T > G, c.66_67delAG and c.4034delA) experienced a lower-than-expected cancer risk (15.9–24.4%) compared to other PVs (28.8%) (p = 0.02). Conclusions: Although our data suggests some variability in penetrance based on specific BRCA1 PV, this was based on a large number of founder mutations. Breast cancer management strategies should continue to be based on comprehensive risk assessment.
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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 | 0.001 | 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".