Metastatic renal cell carcinoma to the head and neck: summary of 21 cases.
Bibliographic record
Abstract
OBJECTIVE: Metastasis of renal cell carcinoma (RCC) to the head and neck is a relatively uncommon phenomenon, but such lesions can be the initial presentation of disease. RCC should be considered a source for lesions in this region, especially in patients who have received a previous diagnosis of RCC. METHODS: In this study, we review the presentation, management, and outcomes for 21 patients with documented metastasis of RCC to the head and neck outside the central nervous system. This study is a retrospective review of cases ascertained during a 17-year period from a large teaching hospital. RESULTS: Of the 21 patients observed, 10 were found to have metastatic disease at the time of RCC diagnosis, involving the head and neck in 5 cases. The most common sites of head and neck metastasis were to bone (n = 6), skin and subcutaneous tissue (n = 6), and lymph nodes (n = 5). CONCLUSIONS: This study is a reminder to consider a renal primary tumour for metastatic disease identified in the head and neck, particularly metastases with a "clear cell" histologic pattern. A head and neck metastasis may occasionally be the presenting sign in a patient with RCC, or it may follow the primary diagnosis by many years.
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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 | 0.000 |
| 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".