Quality of surveillance in patients with completely resected gastroenteropancreatic neuroendocrine tumors.
Bibliographic record
Abstract
591 Background: The incidence and prevalence of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are increasing worldwide. Surgery remains the only curative modality. Because of limited data on patterns of recurrence, real-world surveillance practices and duration vary widely. In 2018, the Commonwealth Neuroendocrine Tumour Research Collaboration (CommNETs) published consensus surveillance guidelines for patients with completely resected GEP-NETs. Our aim was to assess adherence to the CommNETs guidelines for surveillance practices for this patient population at our center. Methods: We conducted a retrospective cohort study of patients with GEP-NETs seen for a new patient appointment at Princess Margaret Cancer Centre (PMCC) from 2019-2022. Patients were included if they had a completely resected GEP-NET and followed on surveillance at our center. Demographic and tumor characteristics, surveillance practices, and clinical outcomes were abstracted. Summary statistics and a descriptive comparison of surveillance practices were completed. Results: Out of the 374 new patient appointments, 87 met the inclusion criteria. The main reasons for exclusion were metastatic disease at presentation (n=128), primary tumor not resected (n=58), and patients not followed at PMCC (n=49) so their surveillance practices cannot be determined from our records. The primary tumor sites were pancreatic (n=50, 57%), appendiceal (n=15, 17%), small bowel (n=11, 13%), rectal (n=10, 12%), and colon (n=1, 1%). Thirty-eight patients (44%) had stage 1 disease, 21 patients (24%) had stage 2, and 28 patients (32%) had stage 3. Forty-six patients (53%) had a WHO tumor grade of 1, 36 patients (41%) had grade 2, and 5 patients (6%) had grade 3. The median duration of follow-up was 18.2 months. Adherence to ordering the recommended surveillance investigations was 23% (20/87). Within the adherent cases, there was a higher number of appendiceal, WHO grade 1, and stage 1 tumors. Sixty-six patients (76%) had at least one test that was not recommended by the guidelines. The most frequent unnecessary tests were CT chest in all patient groups and CT pelvis in pancreatic NETs (Table). Six patients were lost to follow up and none discharged from surveillance. Conclusions: Adherence to the CommNETs consensus guidelines was low at our center, suggesting the guidelines had a minor impact on surveillance practices and providing an area for improvement in process of care and resource utilization. [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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".