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Record W2976164237 · doi:10.1002/cncr.32498

Prostate cancer in young men: An emerging young adult and older adolescent challenge

2019· article· en· W2976164237 on OpenAlexaff
Archie Bleyer, Filippo Spreafico, Ronald D. Barr

Bibliographic record

VenueCancer · 2019
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsMcMaster UniversityMcMaster Children's Hospital
Fundersnot available
KeywordsOverdiagnosisMedicineProstate cancerIncidence (geometry)EpidemiologyDiseaseCancerGerontologyDemographyObesityMortality rateYoung adultInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Recent observations suggest that prostate cancer is an increasing disease among older adolescents and young adults. METHODS: Incidence, mortality, and survival data were obtained from the US National Cancer Institute Surveillance, Epidemiology, and End Results program and the Institute for Health Metrics and Evaluation Global Burden of Disease database. RESULTS: Worldwide, the incidence of prostate cancer has increased in all groups between ages 15 and 40 years and increased globally at a steady rate averaging 2% per year since 1990 (P < .01). In the United States, this age group was >6 times more likely than older men to have distant disease at diagnosis. Stage for stage, their survival rate improved less than in older men. Whereas the overall 5-year relative survival rate in the United States for men diagnosed between ages 40 and 80 years was between 95% and 100%, it was 30% in those aged 15 to 24 years, 50% in those aged 20 to 29 years, and 80% in those aged 25 to 34 years. CONCLUSIONS: Prostate cancer in older adolescent and young adult men has increased in most countries. There is some evidence that this may be caused in part by underdiagnosis, prostate-specific antigen screening, and overdiagnosis. It also may be caused by trends in obesity, physical inactivity, HPV infection, substance exposure, environmental carcinogens, and/or referral patterns. How the biology of these cancers differs from that in older men and how the etiologies vary from country to country remain to be determined.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.040
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.303
Teacher spread0.288 · 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".

Quick stats

Citations130
Published2019
Admission routes1
Has abstractyes

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