A preliminary validation of a family history assessment form to select women at risk for breast or ovarian cancer for referral to a genetics center
Bibliographic record
Abstract
The medical community and general population have become aware that genetic testing is available to look for BRCA1 and BRCA2 mutations. However, criteria for who should be referred for genetic counseling and possible subsequent testing have yet to be determined, and many genetics centers have been overwhelmed by the demand for service. We set out to develop a family history assessment tool (FHAT) that could be used by physicians to select individuals for genetic counseling. Arbitrarily, we chose individuals who would have an approximate doubling of their lifetime risk for breast or ovarian cancer. The FHAT was then applied to 184 unrelated families, with an index patient who had breast or ovarian cancer and who had accepted the offer of BRCA1 BRCA2 testing. Data were compiled to compare the number of individuals who would have been referred for genetic counseling and the number of mutation-positive individuals who would have been screened out from counseling using FHAT, the tables from Claus, and the BRCAPRO system. In this population, FHAT was effective in minimizing both the number of referrals and the likelihood of missing women who were later found to be mutation-positive.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".