A population-based analysis of the epidemiology of penile cancer in Newfoundland and Labrador
Bibliographic record
Abstract
INTRODUCTION: Penile cancers are a rare subset of carcinomas accounting for <1% of all diagnosed malignancies. There have been recent reports of increasing incidence globally; however, there is limited Canadian literature pertaining to these neoplasms. The province of Newfoundland and Labrador (NL ) represents an important entity to study, possessing the highest national incidence of cancer, along with a plethora of relevant risk factors for penile cancer. METHODS: A retrospective chart analysis of all patients with a diagnosis of penile cancer in NL between the years of 2006 and 2018 was conducted. The main outcomes included overall incidence, proportion with metastatic disease, tumor demographics, and overall survival (OS ). Incidence among the male population was calculated using Statistics Canada annual reports. RESULTS: An identified 81 cases satisfied the inclusion criteria, with a median age at diagnosis of 65 (interquartile range 20) years. Crude incidence of penile cancer ranged from 1.20-4.27/100 000 males in 2007 and 2010, respectively, while the average age-standardized incidence was 2.34/100 000 males across the study timeframe. Metastatic disease was noted in 17 (21.0%) patients, with a five-year OS of 74% for all penile malignancies, decreasing to 66% in those with invasive squamous cell carcinoma. CONCLUSIONS: The incidence of penile cancer in our population was higher than reported Western jurisdictions and showed frequent rates of metastatic spread. These observations are likely multifactorial, resultant of chronic inflammation paired with high rates of modifiable risk factors and diagnostic delays. An evident need for greater examination and improved reporting of these malignancies in the province was identified.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".