Proffered papers 14.00–15.00 Tuesday 16 September 2003 8 Ampullary, pancreatic and biliary duct exfoliative brush cytology prepared by the thinprep method: performance and morphology
Bibliographic record
Abstract
Background ERCP‐directed brush cytology is used to sample lesions of the pancreatic and biliary ducts and the ampulla of Vater. With conventional preparations, the sensitivity and specificity range from 44% to 63% and 80% to 98%, respectively, and increased N : C ratio, nuclear molding and loss of honeycombing are reliable features of malignancy. The performance and morphology of specimens prepared by ThinPrep, a liquid‐based cytology technique is mostly unknown. Methods The laboratory information system was searched for all cases prepared by ThinPrep. Patient disease classification of benign or malignant was determined by linkage with the provincial cancer registry and was the gold standard against which sensitivity, specificity, positive (PPV) and negative predictive values (NPV) were calculated. True positives and negatives were reviewed to identify predictive cytomorphologic features. Results Between 1996 and 2001, there were 149 ThinPrep specimens; 55 (37%) were reported as positive for malignancy and 94 (63%) as negative. Disease was classified as malignant in 86 (58%) patients and benign in 63 (42%). There were 42 false negative, 11 false positive, 52 true negative, and 44 true positive cytology results. Sensitivity was 51.2% (CI; 40.2 : 62.0), specificity 82.5% (CI; 70.5 : 90.6), and PPV and NPV 80.0% (CI; 66.6 : 89) and 55.3% (CI; 44.7 : 65.5), respectively. Cell groups with crowded, enlarged, irregular nuclei and nuclear features of vesicular chromatin and large, multiple irregular nucleoli correlated with malignant disease, while monolayered sheets of uniform columnar cells, regular nuclei and a finely granular chromatin correlated with benign disease. Conclusions The performance of ThinPrep brushings from this anatomic site equals conventional preparations. Cytomorphologic features of malignancy are more frequent and pronounced with ThinPrep.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.861 | 0.765 |
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".