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Record W3200978041 · doi:10.1093/jjco/hyab011

Age-specific bladder cancer incidence rate in the world

2021· article· en· W3200978041 on OpenAlexaboutno aff
Ayako Okuyama, Megumi Hori

Bibliographic record

VenueJapanese Journal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancerIncidence (geometry)OncologyBladder cancerInternal medicine

Abstract

fetched live from OpenAlex

In order to make a comparison of the age-specific colorectal 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, the Republic of Korea and Thailand), three countries in America (the United States of America, Canada and Brazil), two countries in Oceania (Australia and New Zealand) and 4 countries in Europe (the United Kingdom, France, Germany and Italy). Some countries have plural cancer registries and we aggregated the 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. Bladder cancer was coded as C67 based on ICD-10. Figure 1 shows the age-specific incidence rates of bladder cancer in male by countries. The age-specific incidence rates in European countries, in particular Italy and Germany, tend to be higher than other countries in Asia, America and Oceania. The age-specific incidence rates continued to increase with age in most of the studied countries. The incidence rate exceeded 1 per 100 000 in the late 20s to 30s, whereas in Italy the incidence rate exceeded 1 per 100 000 in the late teens. The age-specific incidence rates in Asia except Japan tend to be lower than in America and Oceania. In Asia, Japan shows the highest incidence rates of bladder cancer. The incidence rate in Japan up to the age of 30 is almost the same as that in China and the Republic of Korea, but after that the incidence rates increased with age, and the difference from the incidence rates in other Asian countries became large. Age-specific bladder cancer incidence rate per 100 000 people in male. Age-specific bladder cancer incidence rate per 100 000 people in male. Figure 2 shows the age-specific incidence rates of bladder cancer in female by countries. The incidence rate for female was lower than that for male in all studied countries. In the age-specific incidence rate for female, the incidence rates in Europe, especially Italy and Germany, tend to be higher than in other countries. With the exception of Japan, the incidence rates in Asian countries tend to be lower than in other countries. In the Republic of Korea, China and Thailand, the incidence rate remained almost constant after the 80s, while in Japan, as in Europe, America and Oceania, the incidence rate continued to increase with age. Age-specific bladder cancer incidence rate per 100 000 people in female. Age-specific bladder cancer incidence rate 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.144
GPT teacher head0.475
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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