Genetic testing for <i>RAD51C</i> mutations: in the clinic and community
Bibliographic record
Abstract
Much of the observed familial clustering of breast and ovarian cancer cannot be explained by mutations in BRCA1 and BRCA2. Several other cancer susceptibility genes have been identified, but their value in routine clinical genetic testing is still unclear. Germline mutations in RAD51C have been identified in about 1% of hereditary breast and ovarian cancer families. RAD51C mutations are predominantly found in families with a history of ovarian cancer and are rare in families with a history of breast cancer alone. RAD51C is primarily an ovarian cancer susceptibility gene. A mutation is present in approximately 1% of unselected ovarian cancers. Among mutation carriers, the lifetime risk of ovarian cancer is approximately 9%. The average age at onset is approximately 60 years; this suggests that preventive oophorectomy can be delayed until after natural menopause. Under current guidelines, genetic testing for RAD51C is expected to have a limited impact on ovarian cancer incidence at a population level. This is because the penetrance is 9% to age 80; the great majority of families with mutations would be represented by a single case of ovarian cancer, these are potentially preventable through population screening but not through screening of established ovarian cancer families.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".