Diverging incidence trends of oral tongue cancer compared to other head and neck cancers in young adults in France
Bibliographic record
Abstract
While head and neck cancer incidence decreased worldwide due to reduced tobacco and alcohol consumption, oral tongue cancer (OTC) incidence has been reported to be increasing in several countries. Our study examines the incidence trends of OTC in France from 1990 to 2018, globally and by age; and compares the incidence trends with the evolution of the incidence of other human papilloma virus-unrelated head and neck squamous cell carcinoma, that is, cancers of the remaining subsites of the oral cavity (RSOCC) and laryngeal cancers for the period 1990 to 2018. World age-standardized incidence rates of oral tongue cancers (C02), cancers of the remaining subsites of the oral cavity (RSOCC, C03-06) and laryngeal cancers (C32) were estimated using the French National Network of Cancer Registries for the period 1990 to 2018. Trends in national incidence rates were estimated from a mixed-effect Poisson model including age and year effects using penalized splines and a district-random effect. In women aged 30 and 40, a significant increase in OTC incidence was observed, while ROSCC showed a nonsignificant incidence decrease. In young men aged 25, a marginally significant increase of OTC incidence years was observed, while incidence rates of RSOCC significantly declined. The results suggest a tendency towards diverging incidence trends for OTC compared to RSOCC and laryngeal cancer in young adults. The observed trends may reflect changes in underlying exposures or emerging exposures not yet identified, and stress the need to further investigate the etiology of oral tongue cancers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".