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Record W4220963054 · doi:10.1093/jjco/hyac037

International variations in lymphoma incidence in children and adolescents

2022· article· en· W4220963054 on OpenAlexaboutno aff
Tomohiro Matsuda, Hadrien Charvat

Bibliographic record

VenueJapanese Journal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIncidence (geometry)PediatricsLymphomaOncologyInternal medicine

Abstract

fetched live from OpenAlex

To compare the subtype distribution of lymphoma and reticuloendothelial neoplasms in children and adolescents between Japan and other countries, we extracted information on cancer incidence in children and adolescents from the third volume of the International Incidence of Childhood Cancer series (IICC-3) (1). The IICC-3 reports the number or incidence rates of cancers occurring in childhood and adolescence, collected from cancer registries (regional or national) worldwide. We analyzed lymphoma and reticuloendothelial neoplasms incidence in four countries in Asia (Japan, China, the Republic of Korea and Thailand), two countries in Africa (Egypt and Uganda), four countries in the Americas [North: the United States of America (USA) and Canada, Latin and Caribbean: Brazil and Colombia], three countries in Europe [the United Kingdom (UK), France and Germany] and two countries in Oceania (Australia and New Zealand). Information from the Republic of Korea, USA, UK, Australia and New Zealand were obtained at the national level, and those from the other countries were from one or multiple regional cancer registries. The years of incidence to be collected varied from country to country, but ranged from 1990 to 2014, with the shortest being 12 years (Egypt: 1999–2010, UK: 2000–2011) and the longest being 24 years (Japan and China: both 1990–2013). In this study, we compared the incidence and proportional distribution of lymphoma subtype in children (0–14 years old) and adolescents (15–19 years old) between these countries. The age-standardized lymphoma and reticuloendothelial neoplasms incidence rates in children (0–14 years old) were the highest in Africa, followed by Latin America. North America, Europe and Oceania had similar levels of incidence, and Asia had lower incidence rates than these regions. In adolescents (15–19 years old), the incidence was higher in North America, Europe and Oceania, followed by Africa and Latin America. The incidence in Asia was low, as in children (Table 1). Incidence rates of lymphoma and reticuloendothelial neoplasms in children and adolescents (per 1 000 000 person-years) aAge-standardized incidence rate. Proportional distribution of subtype of lymphoma and reticuloendothelial neoplasms in children (0–14 years old). Proportional distribution of subtype of lymphoma and reticuloendothelial neoplasms in adolescents (15–19 years old). The subtype distribution of lymphoma and reticuloendothelial neoplasms in children and adolescents varied widely by region in the world. Figure 1 shows the proportional distribution of subtypes of lymphoma and reticuloendothelial neoplasms in children aged 0–14 years by country. In general, the proportion of Hodgkin’s lymphoma in children was about 30–40% in Europe, North America, Latin America and Oceania, whereas it was <20% in Asia and Africa except Egypt. In contrast, the proportion of non-Hodgkin’s lymphoma was slightly lower in Europe and the United States than in Asia and Africa. Burkitt lymphoma tended to be more common in Europe, the United States and Africa, and less common in Asia. Especially in Uganda, more than half of the patients had Burkitt lymphoma. Figure 2 shows the proportional distribution of subtype of lymphoma and reticuloendothelial neoplasms in adolescents aged 15–19 years. In adolescents, the trend seen in children was more pronounced, with Hodgkin’s lymphoma accounting for about 60% of cases in Europe, North America, South America and Oceania, whereas in Asia and Africa except Egypt, the proportion was 20–30%. Non-Hodgkin’s lymphoma was less common in Europe, North America and Oceania, and more common in Asia, Africa and Latin America. There was no large variability in the proportion of Burkitt lymphoma and lymphoreticular lymphoma between countries. Note: Data were extracted from the third volume of the IICC-3 (1). The table and figures are prepared by the authors of this article, and the responsibility for this presentation and its interpretation lies with the authors of this article. None declared.

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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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.400
Teacher spread0.365 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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