Trends of incidence and survival in squamous-cell carcinoma of the anal canal in France
Bibliographic record
Abstract
Data on anal cancer epidemiology are rare. The aim of this study was to report on trends of incidence and survival for anal cancer in France before the implementation of the human papilloma virus vaccine. This analysis was carried out on 1150 squamous-cell carcinomas of the anal canal diagnosed from 1989 to 2004 in a population of 5.7 million people covered by eight population-based cancer registries. Time trends in incidence were modeled using an age-period-cohort model. Net survival rates were obtained using the recently validated unbiased Pohar-Perme estimator. The incidence of squamous-cell carcinoma of the anal canal increased from 0.2 to 0.5/100 000 person-years among men and from 0.7 to 1.3/100 000 person-years among women from 1982 to 2012. Among women, the increase peaked after 2005, with an annual percentage change of +3.4% between 2005 and 2012, as compared with +2.6% among men. The net survival was 56% (95% confidence interval, 49-64) at 5 years and 48% (33-70) at 10 years among men. It was higher among women, at 65% (61-69) and 56% (50-63) at 5 and 10 years, respectively. The prognosis improved between 1989-1997 and 1998-2004. This improvement was slightly greater for men than for women, thus progressively reducing the gap between sexes. The incidence of squamous-cell anal canal cancer increased slightly among both sexes, but the increase was more marked among women than among men. The potential benefit of prophylactic female human papilloma virus vaccination against cervical cancer in France should be further evaluated.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".