Age‐specific incidence rates for breast cancer in carriers of BRCA1 mutations from Norway
Bibliographic record
Abstract
Incidence rates of breast cancer among women with a BRCA1 mutation vary according to their reproductive histories and country of residence. To measure cancer incidence, it is best to follow-up cohort of healthy women prospectively. We followed up a cohort of 675 women with a BRCA1 mutation who did not have breast or ovarian cancer before inclusion and who had a normal clinical examination and mammography at first visit. After a mean of 7.1 years, 98 incident cases of breast cancer were recorded in the cohort. Annual cancer incidence rates were calculated, and based on these, a penetrance curve was constructed. The average annual cancer risk for the Norwegian women from age 25 to 70 was 2.0%. Founder mutations had lower incidence rate (1.7%) than less frequent mutations (2.5%) (p = 0.03). The peak incidence (3.1% annual risk) was observed in women from age 50 to 59. The age-specific annual incidence rates and penetrance estimate were compared with published figures for women from North America and from Poland. The risk of breast cancer to age 70 was estimated to be 61% for women from Norway, compared with 55% for women from Poland and 69% for women from North America.
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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".