Prognostic implications of mandibular invasion in oral cancer
Bibliographic record
Abstract
BACKGROUND: Mandibular invasion alters the clinical staging and management of oral epidermoid carcinoma on the assumption that underresection of mandibular bone invaded by tumor can result in disease progression and poor outcome. METHODS: Cox's proportional hazard model was used to assess the effect of mandibular invasion on recurrence-free survival in 107 patients with squamous cell carcinoma of the oral cavity after controlling for the potential confounding effect of positive margins, tumor size, nodal status, and type of resection. RESULTS: Mandibular invasion was characterized as none (n = 59), focal (n = 25), or deep (n = 23). Relapse-free survival at 60 months by the Kaplan Meier product limit method for the none, focal, and deep invasion groups was 61%, 73%, and 46% respectively (p =.28). Variables influencing disease recurrence were positive margins, size >2 cm, N2 and N3 nodal disease, and marginal vs segmental mandibular resection. Mandibular invasion was not a significant risk factor for disease recurrence with an adjusted hazard ratio for deep invasion vs focal or no invasion of 1.0 (95% CI = 0.5, 2.2; p = 1.00). CONCLUSIONS: Detection of bone invasion, particularly in small tumors, may not be as critical to surgical planning as previously expected. The necessity for and extent of bone resection should be determined by the objective of achieving an adequate surgical margin and not the presence of bone invasion per se.
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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) | 0.001 | 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".