Correlation of <scp>p</scp>16 status, hypoxic imaging using [18<scp>F</scp>]‐misonidazole positron emission tomography and outcome in patients with loco‐regionally advanced head and neck cancer
Bibliographic record
Abstract
INTRODUCTION: We investigated the relationship between hypoxia, human papillomavirus (HPV) status and outcome in head and neck squamous cell carcinoma. METHODS: Patients with stage III and IV head and neck squamous cell carcinoma treated on phase I and II chemoradiation trials with 70-Gy radiation combined with tirapazamine/cisplatin or cisplatin/fluorouracil (5FU), hypoxic imaging using [18F]-misonidazole positron emission tomography and known HPV status (by p16 immunohistochemistry) were included in this sub-study. Separate analyses were conducted to consider the impact of tirapazamine on HPV-negative tumours in the phase II trial. RESULTS: Both p16-positive oropharyngeal tumours and p16-negative head and neck squamous cell carcinoma tumours had a high prevalence of tumour hypoxia; 14/19 (74%) and 35/44 (80%), respectively. The distribution of hypoxia (primary, nodal) was similar. On phase II, trial patients with p16-negative hypoxic tumours had worse loco-regional control with cisplatin and 5FU compared with tirapazamine and cisplatin (P < 0.001) and worse failure-free survival (hazard ratio = 5.18; 95% confidence interval, 1.98-13.55; P = 0.001). Only 1 out of 14 p16-positive patients on the phase II trial experienced loco-regional failure. CONCLUSION: Hypoxia, as assessed by [18F]-misonidazole positron emission tomography, is frequently present in both p16-positive and negative head and neck cancer. Further research is required to determine whether hypoxic imaging can be used to predict benefit from hypoxia-targeting therapies in patients with p16-negative tumours.
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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 | 0.001 |
| 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".