The diagnostic value of cytology in parotid Warthin's tumors: international multicenter series
Bibliographic record
Abstract
INTRODUCTION: Warthin's tumor (WT) is a common benign salivary gland neoplasm with a negligible risk of malignant transformation. However, there is a risk of malignant tumors being misdiagnosed as WT on cytology and inappropriately managed conservatively. METHODS: Patients from nine centers in Italy and the United Kingdom undergoing parotid surgery for cytologically diagnosed WT were included in this multicenter retrospective series. Definitive histology was compared with preoperative cytological diagnoses. Surgical complications were recorded. RESULTS: A total of 496 tumors were identified. In 88.9%, the final histological diagnosis was WT. In 21 cases (4.2%) a malignant neoplasm was diagnosed, which had been incorrectly labeled as WT on cytology. CONCLUSIONS: The risk of undiagnosed malignancy should be balanced against surgical risks when considering the management of WT. Although nonsurgical management remains an appropriate option, there may be a rationale for serial clinical or radiological evaluation if surgical excision is not performed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".