Analysis of variables associated with surgery versus observation in patients with pancreatic cystic lesions referred for endoscopic ultrasound
Bibliographic record
Abstract
See also: Commentaire de travail de A. V. Sahai et al., pp. 591 Endoscopy 2011; 43(07): 647-647 DOI: 10.1055/s-0031-1291784 Introduction Pancreatic cystic lesions are usually pseudocysts or cystic neoplasms. Cystic neoplasms of the pancreas constitute about 10 % of all pancreatic cystic lesions and may be classified as malignant, premalignant, or benign [ 1 ]. Cystic lesions with malignant potential include mucinous cystic neoplasms, intraductal papillary mucinous neoplasms, papillary cystic neoplasms, and cystic islet cell tumors. Serous cyst adenomas are usually benign [ 2 ]. In surgical candidates, EUS with EUS-guided cyst puncture is often requested for cyst fluid analysis (CFA). The hope is that morphological features seen at EUS combined with the results of CFA (for cytology, pancreatic enzymes, and cyst fluid tumor markers) will help decide which patients require surgery, as opposed to conservative management (i. e. “operate versus observe”). There are numerous studies suggesting that EUS and CFA may (or may not) reliably distinguish benign from malignant or premalignant cysts [ 4 ] [ 5 ] [ 6 ] [ 7 ] [ 8 ]. However, no studies have assessed whether and to what extent EUS findings alone or in conjunction with EUS CFA findings actually affect the decision to operate (or to observe). We hypothesized that, despite the fact that EUS with CFA may appear to be a clinically useful tool in this clinical context, it is infrequently a strong determinant of whether operation or observation is chosen as the clinical management strategy. Other variables such as patient age, presence of symptoms, and cyst size, etc., may be stronger determinants of surgery versus observation. If this is the case, one may wonder if the inherent risks (e. g. hemorrhage, cyst infection) and costs of EUS with CFA are truly justified for this indication. This study was not designed to determine the accuracy of EUS and CFA for diagnosing pancreatic cysts; rather, it was designed to study whether EUS and CFA results actually affect the decision to operate on such lesions. The specific aim of this study was to determine the variables associated with surgery (versus observation) in patients with pancreatic cysts in whom EUS-FNA for CFA was requested.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".