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Record W4405943194 · doi:10.3390/curroncol32010022

Pain and Frailty in Childhood Cancer Survivors: A Narrative Review

2024· review· en· W4405943194 on OpenAlexvenueno aff
Chiara Papini, Jaspreet Sodhi, Cassie M. Argenbright, Kirsten K. Ness, Tara M. Brinkman

Bibliographic record

VenueCurrent Oncology · 2024
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of HealthAmerican Lebanese Syrian Associated Charities
KeywordsMedicineChildhood cancerCancerPsychological interventionPopulationGerontologyNarrative reviewPsychiatryInternal medicineIntensive care medicineEnvironmental health

Abstract

fetched live from OpenAlex

A significant proportion of childhood cancer survivors experience persistent health problems related to cancer or cancer treatment exposures, including accelerated or early onset of aging. Survivors are more likely than non-cancer peers to present a frail phenotype suggestive of reduced physiologic reserve and have symptoms that interfere with function in daily life, including pain. Studies in the general population, mostly among older adults, suggest that pain is a significant contributor to development and progression of frail health. This association has not been explored among childhood cancer survivors. In this narrative review, we highlight this gap by summarizing the epidemiologic evidence on pain and frailty, including their prevalence, common risk factors, and correlates in childhood cancer survivors. We further discuss associations between pain and frailty in non-cancer populations, likely biological mechanisms in survivors, and potential interventions targeting both domains.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.196
GPT teacher head0.509
Teacher spread0.313 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

Explore more

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