Treatment Patterns of Pancreatic Neuroendocrine Tumor (pNET) Patients at Two Canadian Cancer Centres
Bibliographic record
Abstract
Pancreatic neuroendocrine tumors (pNETs) are rare but increasingly prevalent malignancies with varied prognoses and a diverse range of treatment options, including surgery, somatostatin analogues (SSAs), chemotherapy, targeted therapy, and peptide receptor radionuclide therapy (PRRT). This retrospective cohort study analyzed treatment patterns among 189 pNET patients treated between January 2010 and June 2021 at two Canadian cancer centres: the Verspeeten Family Cancer Centre (VFCC), which offers PRRT, and the Ottawa Hospital Cancer Centre (TOHCC), which does not at the time of the study. Data on demographics, tumor characteristics, and treatment modalities were collected, and statistical analyses were conducted using chi-square, Fisher's exact test, and the Kruskal-Wallis test. Among eligible patients, 53% presented with stage IV disease. Surgical resection was the most common treatment, followed by SSAs, chemotherapy, PRRT, and targeted therapy. Stage IV patients at VFCC were significantly more likely to receive PRRT (60%) compared to TOHCC (6%) and underwent more PRRT cycles, with a higher prevalence of well-differentiated tumors observed at VFCC. With these differences it was clear that the non-PRRT centre was unable to provide patients with the same level of PRRT access during the study period compared to patients seen at the PRRT site. The findings underscore the critical role of PRRT availability in influencing treatment patterns and highlight the need for equitable access to specialized therapies across Canada to optimize outcomes for pNET patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".