The first 10 years experience with genetic testing (GT) for BRCA1/2 mutations in a publicly funded program at a tertiary care teaching hospital in Ontario, Canada.
Bibliographic record
Abstract
1550 Background: Publicly funded testing for BRCA1/2 mutations in Ontario has been available for high-risk individuals since 2000. The criteria are based on personal and/or family cancer history and ethnicity. We reviewed the results of the first 10 yrs of testing at our institution, a regional cancer centre in an academic, tertiary care teaching hospital. Methods: This REB-approved, retrospective study included individuals who had GT from 2001-2011. Sociodemographic, clinical, and GT results were collected. Results: 2,305 individuals met criteria and underwent GT between Jan. 2001and Dec. 2011. Of all tested subjects, 93% were female, median age was 55 yrs., 23% were of Ashkenazi Jewish (AJ) ancestry and 80% lived in an area with family income $50-100K/yr. BRCA1/2 mutations were present in 16%, 8% had unclassified variant (UCV), 76% had normal sequence. We excluded 460 individuals who had predictive GT for a familial mutation, and results are shown in the Table. For each carrier, an average of four additional relatives had GT. The most common criteria for GT was at least three cases of ovarian or breast cancer at any age on the same side of the family. BRCA mutations were most common among those AJ, Italian, Asian Oriental and English ancestry. Wait time for GT result improved from 107 wks. in 2001 to 8 wks. in 2011. Conclusions: In our tested population, the prevalenceof BRCA1/2 mutations was high. Over time wait times improved and more relatives were tested. [Table: see text]
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".