Renal clear cell carcinoma metastasis to salivary glands – a series of 9 cases: clinico-pathological study
Bibliographic record
Abstract
Metastatic tumors involving salivary glands arising from the non-head and neck area are very rare. Renal cell carcinoma (RCC) is known for its high propensity for metastasis to unusual localizations. RCC metastasis to the maxillofacial area is an uncommon event (16%), but metastasis to salivary glands is extremely rare. We report a series of 9 such cases retrieved from two institutions. The group included 6 females and 3 males. The age at diagnosis ranged from 60 to 97 years (mean 72.6 years). The tumors involved the parotid gland in 7 cases, and the submandibular and small salivary gland of the oral cavity in 1 case each. The size of tumors ranged from 0.4 to 5 cm. Total parotidectomy with selective neck dissection was performed in 4 cases, while superficial parotidectomy was performed in 1 case and simple resection in 3 cases. Histologically, all the tumors were clear cell renal cell carcinomas, and therefore the differential diagnosis mainly included clear cell variants of salivary gland carcinomas. The parotid gland was the initial manifestation of renal malignancy in 4 of the cases, while in the remaining 5 cases a history of RCC had been known. The salivary gland involvement developed from 11 months to 13 years after the time of diagnosis of the primary tumor. In 2 cases it was the first site of dissemination. Pathologists need to maintain a high index of suspicion for the possibility of metastasis when confronted with oncocytic or clear cell neoplasms developing in salivary glands. RCC, although rare, should be included in this differential diagnosis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".