Outcome predictors in squamous cell carcinoma of the maxillary alveolus and hard palate
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Hard palate and maxillary alveolus are two commonly grouped oral cavity subsites due to their anatomic contiguity and oncologic disease behavior. Few studies have been conducted investigating clinical presentation, staging, prevalence of cervical metastases, and outcomes in this population. The primary objective of this study was to analyze predictors of disease-free survival (DFS) in surgically treated patients, particularly as it relates to the role of neck dissection. STUDY DESIGN: Cohort study with planned data collection. METHODS: This cohort study used planned data collection over 15 years (1994-2008) at a large tertiary care cancer center to study all patients presenting with squamous cell carcinoma of the maxillary alveolus and hard palate treated surgically. Univariate and multivariate Cox regression analyses were used to identify predictors of DFS. RESULTS: Ninety-seven patients met the inclusion criteria (54 male, 56%). The majority of patients (54, 56%) presented with locally advanced disease (cT3, cT4). Occult nodal metastases were noted in 26% (17 of 65) of patients clinically staged as N0. The 3-year DFS was 70% (95% confidence interval = 59%-78%) with a median time to failure of 1.1 years (range = 0.3-9.7 years). Cox regression multivariate model demonstrated that advanced pathologic T stage, hard palate tumor site, and poorly differentiated tumor grade were each independent predictors of DFS. CONCLUSIONS: A significant portion of the patients with hard palate and maxillary alveolus tumors harbor occult cervical metastases. Elective neck dissection in the high-risk patients may potentially be beneficial in providing more accurate staging and improving DFS. LEVEL OF EVIDENCE: 2b.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".