Neoadjuvant Capecitabine in Operable HPV‐Negative Head and Neck Cancer: Fortuitous Findings in a Resource Constrained Setting
Bibliographic record
Abstract
OBJECTIVE: Limited progress has occurred in treating operable human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC). Accessing timely care remains challenging in public health care systems, potentially resulting in disease progression before treatment initiation. STUDY DESIGN: A prospective cohort of patients receiving neoadjuvant capecitabine (NC) was compared to stage-matched patients undergoing standard of care (SC). SETTING: This study was performed at 2 academic centers in Montreal, Canada. METHODS: To ascertain the effect of 2 cycles of NC in operable HPV-negative HNSCC patients on clinical-to-pathologic stage migration. Comparison to an SC group was performed to site and TNM stage matched patients. Pathologic treatment response was measured using the modified Ryan score. RESULTS: We compared 16 NC patients (11 oral cavity, 3 skin, 2 larynx) with 32 SC patients. Ten NC patients exhibited a pathologic response (1 complete, 3 major, 6 minor). Clinical-to-pathologic stage migration differed significantly between NC and SC groups: downstage (6 vs 1), upstage (3 vs 14), no change (7 vs 17, P = .0047). There was no severe treatment toxicity related to capecitabine. All patients in the NC group underwent surgery. CONCLUSION: NC followed by surgery demonstrates measurable pathologic response in HPV-negative HNSCC, suggesting potential utility in resource-limited health care settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 source (direct Gemma or distilled Codex), 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".