Survival Outcomes in Upstaged Cutaneous Head and Neck Melanoma With Negative Sentinel Lymph Node Biopsy: A Retrospective Analysis
Bibliographic record
Abstract
BACKGROUND: Biopsy is required to stage cutaneous head and neck melanomas (cHNM), but cHNM can be pathologically upstaged following surgical resection. Here, we evaluated whether upstaged cHNM with negative sentinel lymph node biopsy (SLNB) impacts survival and time to cHNM recurrence. METHODS: We retrospectively analyzed cHNM patients with negative SLNB treated from 2007 to 2014. We included adult cHNM patients with T2a-4a disease at biopsy who underwent SLNB-negative and wide local excision. We extracted patient demographics, treatment details, and survival outcomes. Melanoma-specific survival (MSS) and cHNM recurrence outcomes were analyzed using Cox regression analysis and 95% confidence intervals (95% CI). RESULTS: Overall, 87 patients met inclusion criteria, 17 of whom were upstaged after definitive treatment. No significant baseline demographic or cHNM differences were observed between groups. Excisional biopsies were most performed (n = 57, 65.5%), yet upstaged patients more frequently underwent shave or punch biopsies. Most cHNM lesions were found on the face (n = 35, 40.2%). Univariable Cox regression revealed significant association between upstaged pathology (unadjusted hazard ratio: 3.20, 95% CI: 1.12-9.16), close margins (unadjusted hazard ratio: 4.95, 95% CI: 1.61-15.20), and worse MSS; however, multivariable Cox regression did not demonstrate any relationship between upstaged pathology or margin status and MSS. CONCLUSION: Among patients with pT2-4a, SLNB-negative cHNM, pathological upstaging does not independently predict MSS when adjusted for margin status, but large multicenter prospective cohort studies are needed to further validate these findings.
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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 | 0.001 | 0.001 |
| 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".