Comparison of the diagnostic accuracy of three current guidelines for the evaluation of asymptomatic pancreatic cystic neoplasms
Bibliographic record
Abstract
Asymptomatic pancreatic cysts are a common clinical problem but only a minority of these cases progress to cancer. Our aim was to compare the accuracy to detect malignancy of the 2015 American Gastroenterological Association (AGA), the 2012 International Consensus/Fukuoka (Fukuoka guidelines [FG]), and the 2010 American College of Radiology (ACR) guidelines.We conducted a retrospective study at 3 referral centers for all patients who underwent resection for an asymptomatic pancreatic cyst between January 2008 and December 2013. We compared the accuracy of 3 guidelines in predicting high-grade dysplasia (HGD) or cancer in resected cysts. We performed logistic regression analyses to examine the association between cyst features and risk of HGD or cancer.A total of 269 patients met inclusion criteria. A total of 228 (84.8%) had a benign diagnosis or low-grade dysplasia on surgical pathology, and 41 patients (15.2%) had either HGD (n = 14) or invasive cancer (n = 27). Of the 41 patients with HGD or cancer on resection, only 3 patients would have met the AGA guideline's indications for resection based on the preoperative cyst characteristics, whereas 30/41 patients would have met the FG criteria for resection and 22/41 patients met the ACR criteria. The sensitivity, specificity, positive predictive value, negative predictive value of HGD, and/or cancer of the AGA guidelines were 7.3%, 88.2%, 10%, and 84.1%, compared to 73.2%, 45.6%, 19.5%, and 90.4% for the FG and 53.7%, 61%, 19.8%, and 88% for the ACR guidelines. In multivariable analysis, cyst size >3 cm, compared to ≤3 cm, (odds ratio [OR] = 2.08, 95% confidence interval [CI] = 1.11, 4.2) and each year increase in age (OR = 1.07, 95% CI = 1.03, 1.11) were positively associated with risk of HGD or cancer on resection.In patients with asymptomatic branch duct-intraductal papillary mucinous neoplasms or mucinous cystic neoplasms who underwent resection, the prevalence rate of HGD or cancer was 15.2%. Using the 2015 AGA criteria for resection would have missed 92.6% of patients with HGD or cancer. The more "inclusive" FG and ACR had a higher sensitivity for HGD or cancer but lower specificity. Given the current deficiencies of these guidelines, it will be important to determine the acceptable rate of false-positives in order to prevent a single true-positive.
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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 | 0.013 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".