Human Papillomavirus and Overall Survival After Progression of Oropharyngeal Squamous Cell Carcinoma
Bibliographic record
Abstract
PURPOSE: Risk of cancer progression is reduced for patients with human papillomavirus (HPV) -positive oropharynx cancer (OPC) relative to HPV-negative OPC, but it is unknown whether risk of death after progression is similarly reduced. PATIENTS AND METHODS: Patients with stage III-IV OPC enrolled onto Radiation Therapy Oncology Group trials 0129 or RTOG 0522 who had known tumor p16 status plus local, regional, and/or distant progression after receiving platinum-based chemoradiotherapy were eligible for a retrospective analysis of the association between tumor p16 status and overall survival (OS) after disease progression. Rates were estimated by Kaplan-Meier method and compared by log-rank; hazard ratios (HRs) were estimated by Cox models. Tests and models were stratified by treatment protocol. RESULTS: A total of 181 patients with p16-positive (n = 105) or p16-negative (n = 76) OPC were included in the analysis. Patterns of failure and median time to progression (8.2 v 7.3 months; P = .67) were similar for patients with p16-positive and p16-negative tumors. After a median follow-up period of 4.0 years after disease progression, patients with p16-positive OPC had significantly improved survival rates compared with p16-negative patients (2-year OS, 54.6% v 27.6%; median, 2.6 v 0.8 years; P < .001). p16-positive tumor status (HR, 0.48; 95% CI, 0.31 to 0.74) and receipt of salvage surgery (HR, 0.48; 95% CI; 0.27 to 0.84) reduced risk of death after disease progression whereas distant versus locoregional progression (HR, 1.99; 95% CI, 1.28 to 3.09) increased risk, after adjustment for tumor stage and cigarette pack-years at enrollment. CONCLUSION: Tumor HPV status is a strong and independent predictor of OS after disease progression and should be a stratification factor for clinical trials for patients with recurrent or metastatic OPC.
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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".