Ureteroscopic Biopsy of Upper Tract Urothelial Carcinoma: Comparison of Basket and Forceps
Bibliographic record
Abstract
PURPOSE: To compare two different biopsy devices for upper tract urothelial carcinoma (UTUC) and evaluate the pathologic result obtained by these devices. PATIENTS AND METHODS: From January 2008 to December 2010, 414 ureteroscopies were performed and 504 biopsies were taken for evaluation of UTUC. Two biopsy devices were compared: 2.4F stainless steel flat wire basket and 3F cup biopsy forceps. The effect of the biopsy device on obtaining an adequate pathologic specimen was evaluated using univariate and multivariate binary logistic regression analysis. We also investigated whether tumor grade determination was affected by the biopsy device among patients with a diagnostic biopsy. RESULTS: Diagnosis was successful in 63% and 94% in the forceps and basket groups, respectively (P < 0.0001). Among biopsies with a definite diagnosis of UTUC, specific grade was determined in 80% and 93% in the forceps and basket groups, respectively (P = 0.033). In subgroup analysis of tumors larger than 10 mm in diameter, diagnosis was obtained in 80% and 94% in the forceps and basket groups, respectively (P = 0.037). Cytologic evaluation was found to increase diagnostic rates. CONCLUSIONS: The stainless steel flat wire basket was shown to be superior to the 3F cup biopsy forceps in terms of obtaining tissue diagnosis and providing specific grade.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".