Choices for cancer prevention for women with a BRCA1 mutation? a personal view
Bibliographic record
Abstract
With widespread testing for susceptibility genes, increasing numbers of women are being identified to carry a mutation in one of many genes which renders them susceptible to cancer. The first gene to be identified (in 1994) was BRCA1 which increases a woman's risk for breast cancer (70%) and ovarian cancer (40%). The prevalence of BRCA1 gene mutations has been studied widely and in many countries, mostly in women affected with cancer. In many settings testing is offered routinely to women with serous ovarian cancer or early-onset or triple-negative breast cancer. It is preferable to identify a mutation in a healthy women prior to the diagnosis of cancer. The basic strategies for prevention include surgical prevention, chemoprevention and screening (early detection). Much progress has been made in the past two decades evaluating the benefits of these three approaches. In this commentary I provide my personal views regarding these various interventions in the context of counselling a newly diagnosed health woman with a BRCA1 mutation.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.041 | 0.049 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".