Screening for Founder Mutations in <i>BRCA1</i> and <i>BRCA2</i> in Unselected Jewish Women
Bibliographic record
Abstract
PURPOSE: There are two mutations in BRCA1 and one mutation in BRCA2 that are present in up to 2.5% of Ashkenazi Jewish women. Current guidelines for testing stipulate that a personal or family history of cancer be present to be eligible for testing. To date, population screening in this population has not been suggested. However, this may be rational. Little is known about the appropriateness of testing guidelines for the Jewish population or the level of interest in testing. METHODS: Eligible subjects were women who self-identified as Jewish, who were between the ages of 25 and 80 years, and who resided in Ontario. Subjects were recruited through an article in a national newspaper. Women were asked to complete a study questionnaire and a family history questionnaire and to provide a blood or saliva sample. The risk of carrying a BRCA mutation was estimated for each woman. Results A total of 2,080 women were enrolled onto the study. The overall mutation prevalence was 1.1% (0.5% for BRCA1 and 0.6% for BRCA2). Among the 22 mutation carriers, the mean estimate of carrying a BRCA mutation was 3.9%. Ten (45%) of the 22 women met the current Ontario Ministry of Health Guidelines criteria for testing. CONCLUSION: There is considerable interest for genetic testing among Jewish women at low risk of carrying a mutation. However, many women with mutations are ineligible for genetic testing under current guidelines. Approximately 1% of Jewish women carry a BRCA mutation, and these women should be considered to be candidates for genetic testing.
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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 | 0.001 |
| 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 | 0.000 |
| 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".