No Evidence of Excessive Cancer Screening in Female Noncarriers from BRCA1/2 Mutation–Positive Families
Bibliographic record
Abstract
Background: In families with a proven BRCA1/2 mutation, women not carrying the familial mutation should follow the cancer screening recommendations applying to women in the general population. In the present study, we evaluated the cancer screening practices of unaffected noncarriers from families with a proven BRCA mutation, and we assessed the role of family history in their screening practices. Methods: Self-report data were provided retrospectively by 220 unaffected female noncarriers for periods of up to 10 years (mean: 4.3 years) since disclosure of their BRCA1/2 genetic test result. A ratio for the annual frequency of breast and ovarian cancer screening exams (mammography, breast ultrasonography, breast magnetic resonance imaging, transvaginal or pelvic ultrasound, cancer antigen 125 testing) was calculated as number of screening exams divided by the number of years in the individual observation period. Results: The annual average for mammography exams was 0.15, 0.4, 0.56, and 0.71 in women 30–39, 40–49, 50–59, and 60–69 years of age respectively. The uptake of other breast and ovarian cancer screening exams was very low. Mammography and breast ultrasonography and magnetic resonance imaging were generally more frequent among participants with at least 1 first-degree relative affected by breast cancer. Conclusions: In most noncarriers, screening practices are consistent with the guidelines concerning women in the general population. When noncarriers adopt screening behaviours that are different from those that would be expected for average-risk women, those behaviours are influenced by their familial cancer history. Impact: Decision tools might help female noncarriers to be involved in their follow-up in accordance with their genetic status and their family history, while taking into account the benefits and disadvantages of cancer screening.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".