A prospective study of breast cancer risk in relatives of BRCA1/BRCA2 mutation carriers.
Bibliographic record
Abstract
The BRCA1 and BRCA2 genes were discovered in 1994 and 1995.1,2 Studies have shown that around 5–10% of breast cancer cases are due to a mutation in one of these genes.3 Once a mutation has been identified in a family, it is possible to unambiguously assign mutation status to unaffected female relatives; this is the basis for predictive genetic counselling. The risk of developing breast cancer up to the age of 70 years among women with a positive BRCA1 test is estimated to be from 45–87%.4,5 In contrast, women from a family with a BRCA1 or BRCA2 mutation, but who themselves test negative for the familial mutation, are considered to have the normal population risk for breast and ovarian cancer, which in Canada is around 7% up to 70 years of age. Women with a negative test result are generally advised to undergo the regular breast cancer screening practices, typically consisting of an annual mammograms and a clinical breast examination. There is some question as to whether the risk of breast cancer in these mutation-negative women is in fact raised. Two recent studies reported an increase in breast and ovarian cancer risk for these women. Smith et al reported that 24% of 118 relatives with breast cancer or ovarian cancer cases in 277 families with a BRCA mutation were phenocopies, and they estimated the risk of breast cancer in mutation-negative women to be five times greater than expected.6 Gronwald et al studied unselected cases of breast cancer in Poland, 7 and found that only one of 17 …
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.003 | 0.001 |
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".