HPV Prevalence and Prognostic Value in a Prospective Cohort of 255 Patients with Locally Advanced HNSCC: A Single-Centre Experience
Bibliographic record
Abstract
Background. HPV is a positive prognostic factor in HNSCC. We studied the prevalence and prognostic impact of HPV on survival parameters and treatment toxicity in patients with locally advanced HNSCC treated with concomitant chemoradiation therapy. Methods. Data on efficacy and toxicity were available for 560 patients. HPV was detected by PCR. Analysis was performed using Kaplan-Meier survival curves, Fisher's test for categorical data, and log-rank statistics for failure times. Results. Median follow-up was 4.7 years. DNA extraction was successful in 255 cases. HPV prevalence was 68.6%, and 53.3% for HPV 16. For HPV+ and HPV-, median LRC was 8.9 and 2.2 years (P = 0.0002), median DFS was 8.9 and 2.1 years (P = 0.0014), and median OS was 8.9 and 3.1 years (P = 0.0002). Survival was different based on HPV genotype, stage, treatment period, and chemotherapy regimen. COX adjusted analysis for T, N, age, and treatment remained significant (P = 0.004). Conclusions. Oropharyngeal cancer is increasingly linked to HPV. This study confirms that HPV status is associated with improved prognosis among H&N cancer patients receiving CRT and should be a stratification factor for clinical trials including H&N cases. Toxicity of CRT is not modified for the HPV population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".