Advances in Targeted and Systemic Therapy for Salivary Gland Carcinomas: Current Options and Future Directions
Bibliographic record
Abstract
Salivary gland carcinomas (SGCs) represent a rare and heterogeneous group of malignancies accounting for 3-6% of all head and neck cancers. While surgical resection and radiotherapy remain the standard for locoregional control, systemic treatment is indicated for recurrent or metastatic disease. Advances in molecular profiling have identified actionable targets such as NTRK gene fusions, HER2, immune checkpoint regulators, androgen receptors, and RET receptors. These have facilitated the development of targeted therapies, including TRK inhibitors, HER2-directed agents, and androgen receptor modulators, as well as emerging combinations of immunotherapy and chemotherapy. Despite these advancements, challenges such as resistance mechanisms and limited therapeutic efficacy persist. Overall response rates remain relatively low across most systemic therapies, reflecting a persistent unmet clinical need. This review discusses the current landscape of treatment options and explores promising clinical trials and future directions to enhance outcomes for patients with SGCs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".