Pancreaticobiliary Cytology Practice in 2021: Results of a College of American Pathologists Survey
Bibliographic record
Abstract
CONTEXT.—: The College of American Pathologists (CAP) surveys provide national benchmarks of pathology practice. OBJECTIVE.—: To investigate pancreaticobiliary cytology practice in domestic and international laboratories in 2021. DESIGN.—: We analyzed data from the CAP Pancreaticobiliary Cytology Practice Supplemental Questionnaire that was distributed to laboratories participating in the 2021 CAP Nongynecologic Cytopathology Education Program. RESULTS.—: Ninety-three percent (567 of 612) of respondent laboratories routinely evaluated pancreaticobiliary cytology specimens. Biliary brushing (85%) was the most common pancreaticobiliary cytology specimen evaluated, followed by pancreatic fine-needle aspiration (79%). The most used sampling methods reported by 235 laboratories were 22-gauge needle for fine-needle aspiration (62%) and SharkCore needle for fine-needle biopsy (27%). Cell block was the most used slide preparation method (76%), followed by liquid-based cytology (59%) for pancreatic cystic lesions. Up to 95% (303 of 320) of laboratories performed rapid on-site evaluation (ROSE) on pancreatic solid lesions, while 56% (180 of 320) performed ROSE for cystic lesions. Thirty-six percent (193 of 530) of laboratories used the Papanicolaou Society of Cytopathology System for Reporting Pancreaticobiliary Cytology in 2021. Among all institution types, significant differences in specimen volume, specimen type, ROSE practice, and case sign-out were identified. Additionally, significant differences in specimen type, slide preparation, and ROSE practice were found. CONCLUSIONS.—: This is the first survey from the CAP to investigate pancreaticobiliary cytology practice. The findings reveal significant differences among institution types and between domestic and international laboratories. These data provide a baseline for future studies in a variety of practice settings.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".