A269 EUS-GUIDED ROSE FNA AND CNB FOR THE DIAGNOSIS OF PANCREATIC CANCER: A COMPARATIVE ANALYSIS
Bibliographic record
Abstract
Abstract Background Endoscopic ultrasound-guided fine-needle aspiration with Rapid On Site Evaluation (ROSE EUS-FNA) and endoscopic ultrasound-guided core-needle biopsy (EUS-CNB) are widely used for the diagnosis of pancreatic tumors. There is no known published randomized control trial that compares between the two modalities. Given the aggressive nature of pancreatic cancer, it is crucial to make a prompt diagnosis in order to initiate treatment in a timely fashion. Aims This study compares the diagnostic performance of ROSE EUS-FNA and EUS-CNB for diagnosis of pancreatic cancer. Methods A retrospective review was performed for patients who underwent ROSE EUS-FNA and/ or EUS-CNB for solid pancreatic lesion. Diagnostic yield (defined as percentage of diagnostic samples), diagnostic accuracy (defined as percentage of correct diagnosis), sensitivity and specificity for malignancy were compared between ROSE EUS- FNA and EUS- CNB. Baseline characteristics for both patients and lesions were also obtained. Results A total of 82 patients with solid pancreatic lesions were reviewed. 84 EUS with 61 FNA and 74 CNB were performed. The diagnostic yield was 42/61 (69%) and 59/74 (79.7%) for FNA and CNB respectively (P 0.166). The diagnostic accuracy was 33/61 (54%) and 53/74 (71%) for FNA and CNB respectively (P 0.0326). 50 patients underwent both FNA and CNB during the same EUS. The calculated diagnostic yield among this subgroup was 33/50 (66%) and 39/50 (78%) for FNA and CNB respectively (P 0.265); with diagnostic accuracy of 26/50 (52%) for FNA and 34/50 (68%) for CNB (P 0.152). The diagnostic accuracy after combining both techniques was 40/50 (80%). The incremental increase in diagnostic yield by combining both methods was 12/50 (24%) and 6/50 (12%) relative to FNA and CNB respectively. The sensitivity for the diagnosis of malignancy for FNA and CNB was 60.8% and 92.7%, respectively. The specificity was 100% for both methods. Conclusions EUS-guided CNB is a superior method of assessing solid pancreatic lesion and pancreatic malignancy with better diagnostic yield and accuracy and higher sensitivity than ROSE EUS-FNA. Funding Agencies None
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".