Salivary Duct Carcinoma of the Parotid
Bibliographic record
Abstract
OBJECTIVE: Salivary duct carcinoma (SDC) is a rare and aggressive malignancy for which an optimal treatment algorithm is lacking. We endeavored to assess the current treatment outcomes for SDC with a multimodality treatment approach combining surgery with adjuvant radiotherapy ± concurrent chemotherapy. STUDY DESIGN: Case series with chart review. SETTING: A National Cancer Institute-designated comprehensive cancer center. SUBJECTS AND METHODS: The clinical record of 17 patients with salivary duct carcinoma were analyzed to assess locoregional control, recurrence-free survival, and overall survival. RESULTS: All SDC cases (n = 17) were managed with surgical resection, followed by adjuvant radiotherapy (47.1%) or concurrent chemotherapy and radiotherapy (52.9%). Median patient follow up was 37 months. An aggressive disease course was generally observed, with 3-year recurrence-free survival and overall survival of 34.4% and 35.5%, respectively. The majority of recurrences were distant. Intensification with adjuvant concurrent chemotherapy was not associated with improved outcomes on univariate survival analysis. CONCLUSION: For salivary duct carcinoma, a multimodality treatment approach is associated with acceptable locoregional control rates but poor distant control and overall survival. Novel systemic therapies may be needed to optimize clinical outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".