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Record W95347501 · doi:10.1093/pch/11.2.103

Adolescents and young adults with cancer: An orphaned population

2006· article· en· W95347501 on OpenAlexaff
Conrad V. Fernandez, Ronald D. Barr

Bibliographic record

VenuePaediatrics & Child Health · 2006
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster UniversityIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsMedicineSurvivorship curveReferralYoung adultClinical trialPopulationCancerFamily medicinePediatricsGerontologyInternal medicine

Abstract

fetched live from OpenAlex

Adolescents and young adults (AYAs [15 to 29 years of age]) with cancer have a distinct cancer epidemiology, evolving hormonal milieu, maturing development, transitions in autonomy, increasing demands in education, entry into the workplace and family responsibilities. The prevalence of epithelial cancers in AYA patients represents a major shift from the embryonal cancers that predominate in early childhood. Thus, one would expect a specialized expertise to be required in caring for these patients, who typically fall between paediatric and oncology spheres of practice. Complex issues contribute to the lower survival rates noted for AYAs compared with those of younger patients, even with the same cancer. Cooperative group clinical trial participation has been crucial in advancing the excellent outcomes accomplished in paediatric oncology, yet participation by adolescents in clinical trials (either adult or paediatric) is typically low. There is increasing evidence that both appropriate location of care and access to specialists in paediatric or adult oncology contribute to favourable outcomes. Issues specific to AYA patients should be studied rigorously so that evidence-based approaches may be used to reduce waiting times, ensure prompt referral to appropriate centres, increase accrual to clinical trials, foster compliance, provide comprehensive supportive care and promote programs designed to enhance survivorship.

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 score0.034
Threshold uncertainty score0.990

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 head0.012
GPT teacher head0.291
Teacher spread0.280 · 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

Citations44
Published2006
Admission routes1
Has abstractyes

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