Clinicopathologic Features and Survival Trends for Acinic Cell Carcinoma of the Major Salivary Glands: A Surveillance, Epidemiology, and End Results Population Analysis
Bibliographic record
Abstract
BACKGROUND: We analyzed a population-based national registry to identify the most influential patient pretreatment and treatment factors affecting overall survival (OS) and cause-specific survival (CSS) in patients diagnosed with acinic cell carcinoma (ACC) of the major salivary glands. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER) database of the US National Cancer Institute (NCI) related to survival, a total of 1,254 patients with diagnosed ACC of the major salivary glands from 1975 to 2016 met inclusion criteria. Factors significant for OS and CSS were determined using univariate and multivariate analysis with the Cox proportional hazards model. RESULTS: Univariate OS analysis demonstrated that surgery favorably influenced longer survival compared to no surgery (hazard ratio (HR) 2.35, P < 0.05). Patient age was found to be highly predictive of superior OS (divided into 10-year age bands, P < 0.0001, younger age better). In multivariate OS analysis, there were statistically significant worse outcomes for men (HR 1.54, P < 0.05), grades III/IV (HR 2.5, P < 0.05), and distant disease (HR 3.55, P < 0.05) or regional disease (HR 1.22, P < 0.05). Patients diagnosed during years 1996 - 2016 had better OS when compared to earlier decades 1975 - 1995 (HR 1.38, P < 0.05). In univariate analysis, the mean CSS for grades I, II, and III/IV were 429 months (95% confidence interval (CI), ± 38.39), 426 months (95% CI, ± 25.73) and 198 months (95% CI, ± 66.38). Multivariate analysis of CSS further demonstrated that there were statistically significant worse outcomes for men (HR 1.68, P < 0.05), grade III/IV (HR 3.2, P < 0.05), tumor size greater than 40 mm (P < 0.001), and distant disease (HR 4.48, P < 0.05) or regional disease (HR 1.84, P < 0.05). CONCLUSIONS: To our knowledge, this is the largest population-based study of OS and CSS of major salivary gland ACC. We found that the patient pretreatment and treatment factors including younger age at diagnosis, female sex, early stage, lower grade, surgical excision, and recent year of diagnosis are associated with improved survival in patients diagnosed with ACC of the major salivary glands. We hope that this information will aid in construction of further research projects that better refine optimal treatment protocol of individualized patient care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".