Bibliographic record
Abstract
In order to make a comparison of the age-specific skin cancer incidence rate between Japan and other countries, we abstracted cancer incidence rate from the Cancer Incidence in Five Continents Vol. XI (CI5) (1). The International Agency for Research on Cancer provides the CI5 databases on the incidence of cancer recorded by cancer registries (regional and national) worldwide. We used cancer incidence rate in five countries in Asia (China, India, Japan, Republic of Korea and Thailand), three countries in America (the USA, Canada and Brazil), two countries in Oceania (Australia and New Zealand) and four countries in Europe (the UK, France, Germany and Italy). Some countries have plural cancer registries and we aggregated all registries to calculate the incidence rate in the countries from the CI5-XI database. The period of years at cancer diagnosis was from 2008 to 2012. Larynx cancer was coded as C32 based on ICD-10. The figures show the age-specific incidence rates of laryngeal cancer by 5-year age groups for the selected countries in males (Fig. 1), and in females (Fig. 2). From a general point of view, the pattern of incidence is very similar across countries and gender: laryngeal cancer is very rare in the first two decades of life; its incidence rises steeply to reach a peak in late adulthood and then plateaus or decreases slightly in extreme age categories. Age-specific larynx cancer incidence rate per 100 000 person-years at risk in male. For men, the curves are very similar within each world region. In Asia, the peak, varying from 18.5 to 32.3 cases per 100 000 person-years at risk, is generally reached in the 75–79- or 80–84-year age groups, with slightly higher incidence rates observed in India. For America and Oceania, the peak is generally observed in the same age groups and varies from 20.0 to 44.4 cases per 100 000 person-years at risk; Brazil has consistently higher incidence rates and reaches its peak sooner than the other countries of the region. In Europe, the phase of steep increase in the incidence rate is homogeneous across the selected countries. The peak, varying between 26.0 and 43.8 cases per 100 000 person-years at risk, is reached sooner than in the other two world region, in the 65–69- or 70–74-year age groups, and the incidence rates subsequently tend to plateau until ages 85 years and over. Italy exhibits higher incidence rates than the other countries in older age categories. The pattern of incidence for women is comparable to that of men but the rates are much smaller, with a maximum ranging from 1.4 and 5.0 per 100 000 person-years at risk in Asia, from 3.3 to 6.0 for America and Oceania and from 3.4 to 4.9 in Europe. The shapes of the age-specific incidence curves are very similar to those observed in men. In Asia, the incidence rates begin to plateau from the 60–64-year age group, and India shows higher incidence rates consistently across the age categories. For America and Oceania, there is some heterogeneity in the age-incidence curves between countries with the USA and Brazil showing consistently higher incidence rates. The peak is usually reached in the 65–69 or 70–74-year age groups and the incidence rates then decrease in older age groups. In Europe, as for men, the phase of steep increase of the age-specific incidence rate is very similar between countries. The curves then tend to reach a plateau from the 50–54-year age group, with the UK and Italy showing slightly higher incidence rates than France and Germany. Note: Data were downloaded from the Global Cancer Observatory (GCO), which is an interactive web-based platform presenting global cancer statistics (https://gco.iarc.fr/). Responsibility for this presentation and interpretation lies with the authors of this article. Age-specific larynx cancer incidence rate per 100 000 person-years at risk in female. The authors declare no conflict of interest.
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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 | 0.005 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".