Histopathological Analysis of Nodal Disease After Chemoradiation Reveals Viable Tumor Cells as the most Important Prognostic Factor in Head and Neck Squamous Cell Carcinoma
Bibliographic record
Abstract
BACKGROUND: In head and neck squamous cell carcinoma (HNSCC), salvage neck dissection (ND) is required after primary chemoradiation in case of residual nodal disease. Upon histopathological examination, viability of tumor cells is assessed but little is known about other prognostic histopathological features. In particular, the presence of swirled keratin debris and its prognostic value is controversial. The aim of this study is to examine histopathological parameters in ND specimens and correlate them with patient outcome to determine the relevant parameters for histopathological reporting. MATERIALS AND METHODS: Salvage ND specimen from a cohort of n = 75 HNSCC (oropharynx, larynx, hypopharynx) patients with prior (chemo) radiation were evaluated on H&E stains for the following parameters: viable tumor cells, necrosis, swirled keratin debris, foamy histiocytes, bleeding residues, fibrosis, elastosis, pyknotic cells, calcification, cholesterol crystals, multinucleated giant cells, perineural, and vascular invasion. Histological features were correlated with survival outcomes. RESULTS: Only the presence / amount (area) of viable tumor cells correlated with a worse clinical outcome (local and regional recurrence-free survival, (LRRFS), distant metastasis-free survival, disease-specific survival, and overall survival, p < 0.05) in both the univariable and multivariable analyses. CONCLUSION: We could confirm the presence of viable tumor cells as a relevant negative prognostic factor after (chemo) radiation. The amount (area) of viable tumor cells further substratified patients with worse LRRFS. None of the other parameters correlated with a distinctive worse outcome. Importantly, the presence of (swirled) keratin debris alone should not be considered viable tumor cells (ypN0).
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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 | 0.001 |
| 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".