A Risk‐Adapted Approach for Elective Neck Dissection in Salvage Total Laryngectomy: Revisiting the Role of Tumor Subsite and Occult Nodal Disease
Bibliographic record
Abstract
BACKGROUND: The role of elective neck dissection (END) during salvage total laryngectomy (STL) in clinically node-negative (cN0) patients remains controversial due to variable risks of occult nodal metastasis and surgical morbidity. METHODS: We conducted a multicenter retrospective study of 178 cN0 patients undergoing STL after radiotherapy (RT) or chemoradiotherapy (CRT). Rates of occult nodal disease, survival outcomes, and predictive factors were analyzed. RESULTS: Occult nodal metastases were found in 19.7% of cases, highest in hypopharyngeal (35.7%) and supraglottic (24.5%) tumors. Tumor subsite and lymphovascular invasion were independent predictors of nodal positivity, while prior chemotherapy reduced risk. Patients with occult nodal disease had significantly worse three-year overall and disease-specific survival. CONCLUSIONS: A risk-adapted approach to END in STL is recommended, particularly for supraglottic and hypopharyngeal tumors. Routine END may be unnecessary in low-risk subsites like glottic tumors. Prospective studies are needed to refine management strategies.
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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".