Worldwide Trends in Incidence Rates for Oral Cavity and Oropharyngeal Cancers
Bibliographic record
Abstract
PURPOSE: Human papillomavirus (HPV) has been identified as the cause of the increasing oropharyngeal cancer (OPC) incidence in some countries. To investigate whether this represents a global phenomenon, we evaluated incidence trends for OPCs and oral cavity cancers (OCCs) in 23 countries across four continents. METHODS: We used data from the Cancer Incidence in Five Continents database Volumes VI to IX (years 1983 to 2002). Using age-period-cohort modeling, incidence trends for OPCs were compared with those of OCCs and lung cancers to delineate the potential role of HPV vis-à-vis smoking on incidence trends. Analyses were country specific and sex specific. RESULTS: OPC incidence significantly increased during 1983 to 2002 predominantly in economically developed countries. Among men, OPC incidence significantly increased in the United States, Australia, Canada, Japan, and Slovakia, despite nonsignificant or significantly decreasing incidence of OCCs. In contrast, among women, in all countries with increasing OPC incidence (Denmark, Estonia, France, the Netherlands, Poland, Slovakia, Switzerland, and United Kingdom), there was a concomitant increase in incidence of OCCs. Although increasing OPC incidence among men was accompanied by decreasing lung cancer incidence, increasing incidence among women was generally accompanied by increasing lung cancer incidence. The magnitude of increase in OPC incidence among men was significantly higher at younger ages (< 60 years) than older ages in the United States, Australia, Canada, Slovakia, Denmark, and United Kingdom. CONCLUSION: OPC incidence significantly increased during 1983 to 2002 predominantly in developed countries and at younger ages. These results underscore a potential role for HPV infection on increasing OPC incidence, particularly among men.
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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 | 0.003 | 0.004 |
| 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) | 0.003 | 0.001 |
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".