Perineural Invasion in T1 Oral Squamous Cell Carcinoma Indicates the Need for Aggressive Elective Neck Dissection
Bibliographic record
Abstract
Observation or elective neck dissection (END) for cN0 neck remains controversial for the treatment of T1-2 oral squamous cell carcinoma (OSCC). Perineural invasion (PNI) has been recognized as a poor prognostic factor for OSCC. However, its significance in T1 OSCC remains unclear. A detailed histologic reevaluation of PNI was carried out in 307 patients with T1-2 OSCC who received surgical treatment between June 2001 and January 2009. We found that the presence of PNI correlated with cervical lymph node metastasis in both T1 and T2 OSCC, with a lower PNI-positive rate in T1 (17.1% vs. 36.6%; P<0.001). Importantly, observation for cN0 neck was used twice as often in T1 than in T2 patients (47.4% vs. 22.8%; P<0.001). Although patients with T1 OSCC achieved significantly better outcomes, PNI correlated with neck recurrence and poor disease-specific survival (DSS) only in T1 (P<0.001 and P<0.0001) but not in T2 patients (P=0.399 and 0.1478). Of the 146 patients with T1 OSCC, PNI independently predicted cervical lymph node metastasis, neck recurrence, and poor DSS. END significantly reduced neck recurrence of T1 OSCC in PNI-positive (P=0.001) but not in PNI-negative (P=0.114) patients. In addition, END improved the 5-year DSS of T1 OSCC more in PNI-positive than in PNI-negative patients (16.2% vs. 5.4%). Our results indicate that PNI independently predicts a poor prognosis in T1 OSCC patients who are potentially curable but tend to be treated conservatively. For its efficacy in improving treatment outcomes, aggressive END is indicated for T1 OSCC patients at the presence of PNI.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".