Gastrointestinal Endoscopic Ultrasound-Guided Fine-Needle Aspiration Biopsy Specimens: Adequate Diagnostic Yield and Accuracy Can Be Achieved without On-Site Evaluation
Bibliographic record
Abstract
BACKGROUND: Endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA) is the preferred method for biopsying the gastrointestinal tract, and rapid on-site cytological evaluation is considered standard practice. Our institution does not perform on-site evaluation; this study analyzes our overall diagnostic yield, accuracy, and incidence of nondiagnostic cases to determine the validity of this strategy. DESIGN: Data encompassing clinical information, procedural records, and cytological assessment were analyzed for gastrointestinal EUS-FNA procedures (n = 85) performed at Vancouver General Hospital from January 2012 to January 2013. We compared our results with those of studies that had on-site evaluation and studies that did not have on-site evaluation. RESULTS: Eighty-five biopsies were performed in 78 patients, from sites that included the pancreas, the stomach, the duodenum, lymph nodes, and retroperitoneal masses. Malignancies were diagnosed in 45 (53%) biopsies, while 24 (29%) encompassed benign entities. Suspicious and atypical results were recorded in 8 (9%) and 6 (7%) cases, respectively. Only 2 (2%) cases received a cytological diagnosis of 'nondiagnostic'. Our overall accuracy was 72%, our diagnostic yield was 98%, and our nondiagnostic rate was 2%. Our results did not significantly differ from those of studies that did have on-site evaluation. CONCLUSION: Our study highlights that adequate diagnostic accuracy can be achieved without on-site evaluation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".