Age-specific incidence rate of brain and nervous system malignancy in the world
Bibliographic record
Abstract
In order to make a comparison of the age-specific incidence rate of brain and nervous system malignancy 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 the 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. Brain and nervous system malignancy were coded as C70–C72 based on ICD-10. Figure 1 shows the age-specific incidence rate of brain and nervous system malignancy in male by countries. Figure 2 shows the age-specific incidence rate of brain and nervous system malignancy in female by countries. Age-specific incidence rate of brain and nervous system malignancy per 100 000 people in male. The incidence rate was lower in Asia than in the three other regions showing more consistency altogether, with a higher incidence rate observed specifically above 75 years old in Australia, Brazil and Italy. In the Asia region, Japan sat in between the higher (China and Republic of Korea) and lower (Thailand and India) end of countries. In all countries, the incidence rate was higher for paediatric tumours in the range 0–10 years old than 15–20 years old, where a down peak was observed, whereas the incidence rate subsequently increased constantly up to 70 years old. Above 70 years old, the incidence rate tended to decrease in most countries, with a drastic drop in Thailand above 80 years old, except for Japan, New Zealand and Brazil, where the incidence rate respectively increased for both genders—males and females. Incidence rates for females and males were quite similar up to the late twenties/early thirties, with an increasing gap with age between genders (generally lower for females) in all observed countries including Japan, with the exception of China, where the curves mostly overlapped between males and females. Age-specific incidence rate of brain and nervous system malignancy per 100 000 people in female. 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.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".