Secretory carcinoma: The eastern Canadian experience and literature review
Bibliographic record
Abstract
BACKGROUND: Secretory Carcinoma (SC) is a recently described malignancy affecting salivary glands of the head and neck, with a paucity of evidence regarding the natural history, morbidity, and mortality. This study aimed to investigate the current treatment options utilized for SC, as well as its presentation and outcomes. METHODS: This study is a retrospective case series and includes patients diagnosed with SC at four Maritime Canadian institutions. Literature review of patient outcomes following treatment of SC is also included. RESULTS: Thirteen patients were identified. Parotid was the most common subsite (69%), followed by minor salivary gland (23%) and submandibular gland (8%). All patients were S100 positive and had at least one additional positive confirmatory stain, including mammaglobin, CK7, or vimentin. Two patients had N2b disease. All patients were treated with primary surgery, and four were offered adjuvant radiotherapy. There was one instance of locoregional recurrence, and one of metastasis. Three patients displayed perineural invasion on pathology, and one patient displayed lymphovascular invasion. CONCLUSION: Secretory Carcinoma remains understudied regarding its natural history, presentation, and treatment options. This study is the largest single case series in Canada, and highlights the young age and possible aggressiveness of SC. As well, we provide the most comprehensive literature review to date, with a focus on treatment and outcomes for this disease entity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".