A256 SURVEILLANCE OF SMALL, NON-FUNCTIONING, ASYMPTOMATIC PANCREATIC NEUROENDOCRINE TUMORS: THE BRITISH COLUMBIA EXPERIENCE
Bibliographic record
Abstract
Abstract Background Expert consensus surrounding surveillance for small, non-functioning, asymptomatic pancreatic neuroendocrine tumors (PNETs) remains conflicting. Recent observational studies have shown that surveillance is a safe strategy while large database studies show superior overall survival with surgical resection. Aims To describe the growth of small (<2cm), non-functioning, asymptomatic PNETs undergoing surveillance at a tertiary hospital in British Columbia. Methods We conducted a retrospective case series of patients with biopsy-proven, non-functioning, asymptomatic PNETs which were <2cm by RECIST criteria at diagnosis, who were followed through active surveillance at Vancouver General Hospital, British Columbia from February 1, 2011-February 1, 2021. Patients were included if serial imaging, whether by endoscopic ultrasound or cross-sectional imaging, was available for a minimum of 24 months. Results Of the 57 patients with pathology-proven PNETs that were identified, 14 cases were included after excluding those with resection within 1 year (n=17), lost to follow up (n=13), metastatic disease (n=6), size greater than 2cm at diagnosis (n=4), and with concurrent cancer (n=3). Included patients were predominantly female (n=10, 71%), Caucasian (n=8, 57%), and had a mean Charlson comorbidity index of 3.14. Mean PNET size at diagnosis was 12mm with standard deviation of 4.26mm. Tumors were located in the pancreatic head (n=4, 29%), body (n=6, 42%), and tail (n=4, 29%). Of 8 patients who had Ki67 stains, all were <3%, and of 11 patients with mitotic index, all had <2 mitotic figures. As such, of the 8 patients with available WHO grading, all were grade 1. The average follow-up was 49.6 months with an average tumor growth of 0.82mm per year. When grouping these tumors by growth, 9 (62%) tumors exhibited no growth, 2 tumors grew <1mm per year, 2 tumors grew 1-1.5mm per year, and 1 tumor grew 7.7mm per year. Two cases (14%) of PNETs underwent surgical resection due to size surpassing 2 cm. No patients undergoing surveillance developed metastatic disease. Conclusions To our knowledge, we have performed the first Canadian series of small, low-grade PNETS and demonstrated that active surveillance is a safe strategy with most tumors exhibiting no growth of several years. Of the subset of PNETs which demonstrate progression, the preceding surveillance strategy did not disadvantage patients in terms of progression to metastases and allowed for delay of potentially morbid surgery. Further research with prospective studies and larger samples should be conducted. Funding Agencies CAG
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".