Genetics Consultation Rates Following a Diagnosis of High-Grade Serous Ovarian Carcinoma in the Canadian Province of Ontario
Bibliographic record
Abstract
OBJECTIVE: In 2001, the province of Ontario expanded cancer genetic testing eligibility to include all women with high-grade serous ovarian carcinoma (HGSC) of the ovary, fallopian tube, and peritoneum. The aim of this study was to determine the proportion of women who attended genetics counseling for consideration of BRCA1/2 gene analysis. We also sought to examine if regional differences in consultation rate exist across administrative health regions in the province of Ontario. METHODS: We identified all women with a pathological diagnosis of HGSC in the province of Ontario between 1997 until 2011. Our primary outcome was the 2-year rate of genetics consultation following a diagnosis of HGSC. We compared consultation rates over time and geographical regions and applied multiple logistic regression to identify predictors of genetics consultation. RESULTS: Of the 5412 women with a diagnosis of HGSC over the study period, 6.6% were seen for genetics consultation within 2 years of diagnosis. Factors predictive of genetics consultation included history of breast cancer (odds ratio [OR], 3.56; 95% confidence interval [CI], 1.87-6.78), era of diagnosis (2009-2011 vs 1997-2000; OR, 10.59; 95% CI, 5.02-22.33), and younger age at diagnosis (OR, 0.95; 95% CI, 0.94-0.97 for each additional year). No regional differences in consultation rate were seen. CONCLUSIONS: Despite an increasing rate across eras, a small proportion of women with HGSC undergo genetics consultation. Efforts are required to increase cancer genetics consultation in patients with HGSC in the province of Ontario.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".