Small and Stable Pancreatic Cysts Are Reassuring During Surveillance: Results From the PACYFIC Trial
Bibliographic record
Abstract
BACKGROUND: Pancreatic cysts are increasingly discovered on imaging studies performed for unrelated conditions. Currently, surveillance of these lesions poses a substantial burden on patients, and health care recourses. We hypothesized that individuals with small and stable cysts have a diminutive risk of progressing to high-grade dysplasia (HGD) or pancreatic cancer (PC) that is similar to that in the general population. METHODS: This nested PACYFIC-study is a collaboration among 44 centers in Europe and Northern-America, and investigates the risk of HGD and PC for different cyst sizes and growth rates in participants without baseline worrisome features (WF) or high-risk stigmata (HRS). RESULTS: Of the 2369 PACYFIC participants, 975 met the inclusion criteria, with a mean age of 67 years (SD 13) and 65% being female. Of these, 438 individuals (45%) had a baseline small cyst size (< 15 mm), and 885 (91%) individuals had a slow growth rate (< 2.5 mm/year). During a median follow-up of 45 months (IQR 27), 20 individuals (2.1%) developed HGD, or PC. Individuals with small cysts had a 1.5-fold lower risk of developing WF or HRS (hazard ratio [HR] 0.7 [0.5-1.0], p = 0.03) than those with larger cysts but a similar risk of developing HGD or PC (p > 0.05). Slow growth was protective against the development of WF or HRS (HR 0.4 [0.2-0.6], p < 0.001) and HGD or PC (HR 0.04 [95% CI 0.02-0.12], p < 0.001). Individuals with small, stable sized cysts without baseline WF or HRS did not have a higher risk of HGD or PC than the general population (standardized incidence ratio [SIR] 1.13 [95% CI 0.01-6.30]). CONCLUSION: Cyst size < 15 mm and growth rate < 2.5 mm/year appear to be "reassuring" features associated with a negligible risk of developing WF or HRS and HGD or PC. For cysts with these characteristics-and without baseline WF or HRS-less intensive surveillance (than currently recommended) or even cessation may be appropriate.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".