The relationship of human papillomavirus positivity with tumor characteristics in an Irish penile cancer population
Bibliographic record
Abstract
Introduction: Penile cancer is a rare malignancy, with a European-wide annual incidence rate of 1/100 000 males. Approximately one-third of cases are attributable to human papillomavirus (HPV) infection. p16INK4a is a recognized surrogate marker for HPV infection in penile cancer. University Hospital Waterford (UHW) is the national referral center for penile cancer in Ireland. We report the prevalence of HPV infection and histological characteristics of an Irish penile cancer cohort using p16INK4a as a surrogate marker. Methods: Patients who attended UHW for penile cancer surgery between June 2015 and November 2020 were entered into a prospectively maintained database. Clinical, histopathological, and outcome data were collected. Results: Over the study period, 70 patients with a histological diagnosis of penile squamous cell carcinoma had staining for p16INK4a, of whom 64% were positive. p16INK4a positive patients were significantly younger at diagnosis, with a mean age of 61±15 years compared to 68±12 (p <0.05). Of note, 97% of tumors with high-risk histology were p16INK4a positive (p<0.001). p16INK4a positivity was more prevalent among higher-grade tumors (p<0.02). Interestingly, p16INK4a status was not associated with recurrence-free or overall survival. Conclusions: Our data is representative of the Irish landscape in penile cancer over the last five years. Using p16INK4a staining, we demonstrate a high rate of HPV prevalence in penile cancer cases in our patient cohort, which is associated with prognostically worse tumor subtypes. This would suggest that HPV vaccination of adolescent boys is a useful public health intervention in preventing penile cancer in the Irish male population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".