Penile Invasive Squamous Cell Carcinoma: Analysis of Incidence, Mortality Trends, and Geographic Distribution in Canada
Bibliographic record
Abstract
BACKGROUND: Penile invasive squamous cell carcinoma (SCC) is a rare disease with several known risk factors. However, few studies have assessed its incidence, mortality, and temporal trends. OBJECTIVE: Our objectives are to analyze the epidemiology of penile SCC in Canada and to examine patient distribution with this cancer across Canada in order to elucidate population risk factors. METHODS: Three independent cancer registries were used to retrospectively analyze demographic data from Canadian men diagnosed with penile invasive SCC between 1992 and 2010. The Canadian Census of Population was used to calculate incidence and mortality rates at the province and Forward Sortation Area levels. RESULTS: The overall age-adjusted incidence rate was 6.08 cases per million males. Four provinces with statistically significantly higher incidence rates were identified. The national crude incidence rates increased linearly between 1992 and 2010, whereas the age-adjusted incidence rates showed no significant increase during this time period. The overall age-adjusted mortality rate was 1.88 deaths per million males per year. The province of Saskatchewan had significantly higher mortality rates. There was no increase in crude or age-adjusted mortality rates between 1992 and 2010. There was a significant positive correlation between incidence rates and obesity, Caucasian ethnicity, and lower socioeconomic status. CONCLUSION: This study was able to establish geographic variation for this malignancy at the provincial level. Although there are many established risk factors for penile SCC, our results suggest that the increase in crude incidence rates observed is largely due to the aging 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| 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) | 0.001 | 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".