Evaluation of family history in individuals with heterozygous BRCA pathogenic variants diagnosed with breast or ovarian cancer in a single center in Italy
Bibliographic record
Abstract
BACKGROUND: BRCA1 and BRCA2 gene mutations are responsible for 5% of breast cancer (BC) and 10-15% of ovarian cancer (EOC). The presence of a germline mutation and therefore the identification of subjects at high risk of developing cancer should ideally precede the onset of the disease, so that appropriate surveillance and risk-reducing treatments can be proposed. In this study, we revisited the family history (FH) of women who tested positive for BRCA mutations after being diagnosed with BC or EOC. METHODS: The National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines in Oncology (NCCN Guidelines®), and the Italian Association of Medical Oncology (AIOM) guidelines were applied to the FH of 157 women who were referred to San Gerardo Hospital for genetic counseling. RESULTS: Almost 85% of women had an FH of BRCA-related cancer. 63.7% and 52.2% of women could have undergone genetic testing according to NCCN and AIOM testing criteria (p < .05) before tumor diagnosis. An FH of EOC was the most frequent NCCN criterion, followed by BC diagnosed <45 years old. Sixty-five percent of deceased women could have undergone genetic testing before developing cancer. CONCLUSIONS: FH is a powerful tool to identify high-risk individuals eligible for genetic counseling and testing. Testing of healthy individuals should be considered when an appropriately affected family member is unavailable for testing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".