Improving Access to Hereditary Testing in Pancreatic Ductal Carcinoma
Bibliographic record
Abstract
PURPOSE Approximately 5%-10% of patients with pancreatic ductal adenocarcinoma (PDAC) have an inherited basis, yet uptake of genetic testing remains low and subject to disparities. This study compared two genetic testing pathways available to patients referred to a provincial cancer center, BC Cancer: a traditional hereditary cancer clinic–initiated testing (HCT) pathway and a new oncology clinic–initiated testing (OCT) pathway. METHODS Study subjects were patients with confirmed PDAC referred for genetic testing through the HCT or OCT pathway between June 1, 2020, and February 1, 2022. Charts were retrospectively reviewed for patient characteristics and testing outcomes. RESULTS The study population was 397 patients (HCT, n = 279 and OCT, n = 118). OCT patients were more likely to have non-European ethnicity compared with HCT patients (41.9% v 25.6%, P = .004), to have earlier-stage disease ( P = .012), and to have better Eastern Cooperative Oncology Group performance status than the HCT group ( P = .001). A total of 306 patients completed testing (77%). OCT patients had higher test completion rates than HCT patients (odds ratio, 3.74 [95% CI, 1.66 to 9.62]). Median time for results was shorter in OCT than in HCT (53 days [IQR, 44-76] v 107 days [IQR, 63.8-158.3]). Pancreatic cancer susceptibility pathogenic gene variants were identified in 8.5% (26/306). CONCLUSION The real-world observations in our study show that oncology clinic–initiated hereditary testing is more effective and faster than testing through hereditary cancer clinic referrals and reaches a more ethnically diverse population. This has important implications for publicly funded environments with limited resources for genetic counseling.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".