Impact of elective neck dissection on the outcome of oral squamous cell carcinomas arising in the maxillary alveolus and hard palate
Bibliographic record
Abstract
BACKGROUND: Whether elective lymph neck dissection (ELND) is associated with improved survival in oral squamous cell carcinomas (SCC) of the maxillary alveolus/hard palate is not known. METHODS: One hundred ninety-nine patients presenting de novo and receiving treatment for clinically node negative SCC of the maxillary alveolus/hard palate at 2 cancer centers between 1985 and 2011 were analyzed. RESULTS: Forty-two patients (21%) received ELND. Occult nodal metastases were present in 29% of the dissected necks. The ELND group had more T3 to T4 status tumors (62% vs 34%; p < .001) and positive-margin resections (59% vs 38%; p = .019). Patients undergoing ELND experienced lower rates of neck recurrence (6% vs 21%; p = .031), superior 5-year recurrence-free survival (68% vs 45%; p = .026), and overall survival (86% vs 62%; p = .043). ELND was associated with a 2-fold decrease in risk of recurrence in multivariable analysis. CONCLUSION: ELND was associated with lower rates of recurrence and improved survival in SCC of the maxillary alveolus/hard palate. © 2015 Wiley Periodicals, Inc. Head Neck 38: E1688-E1694, 2016.
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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".