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Record W2159916422 · doi:10.1002/pbc.21418

Nutrition and cancer in children

2007· article· en· W2159916422 on OpenAlexaffabout
Ronald D. Barr, Stephanie A. Atkinson, Paul B. Pencharz, Guillermo Ruiz Argüelles

Bibliographic record

VenuePediatric Blood & Cancer · 2007
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of TorontoMcMaster UniversityMcMaster Children's Hospital
Fundersnot available
KeywordsMedicineContext (archaeology)CancerUnderweightMalnutritionPsychological interventionOverweightPediatricsGerontologyInternal medicineObesityPsychiatry

Abstract

fetched live from OpenAlex

Underweight and overweight conditions are global problems; even occurring conjointly in households as the “nutrition paradox” 1, 2. Aberrant nutrition is especially relevant to the growing child, and particularly so when cancer develops in early life. There are well-defined nutritional contributions to the pathogenesis of malignant diseases, the tolerance of anti-neoplastic therapy, and the duration and quality of survival after completion of treatment for cancer in childhood and adolescence. The confluence of childhood, cancer, and nutrition has been designated a “dynamic triangle” 3. This assumes considerable importance in “countries with limited resources” in which malnutrition is prevalent and the great majority of children reside 4. The first international workshop to address this interactive triad was held in Puebla, Mexico almost a decade ago under the auspices of the International Union Against Cancer. It was entitled “Nutritional morbidity in children with cancer: mechanisms, measures, and management” 5. Since then there has been increasing recognition of the central role of nutrition in the context of children with cancer, exemplified by the establishment of a scientific committee on the topic within the Children's Oncology Group 6. Further elucidation on causality and prevention, such as the linkage between maternal ingestion of DNA topoisomerase II inhibitors during pregnancy and MLL+ acute myeloid leukemia in infants 7, and the reduction in the incidence of acute lymphoblastic leukemia in the first year of life associated with a high maternal intake of folate antenally 8. The development of algorithms for nutritional assessment and supplementation 9. Studies of specific interventions to reduce treatment-related morbidity, such as oral mucositis 10, and improve health-related quality of life. Nevertheless the “holy grail”—of increasing the duration of survival by improving nutritional status—remains elusive. However, in long-term survivors the need to diminish obesity, with its risk of attendant co-morbidities (some of which may be life-limiting), is an obvious priority. The overall objective of the second international workshop (held under the auspices of the International Network for Cancer Treatment and Research) is to examine the current “state of play” with the development of “positions” on selected topics to inform the rapidly expanding research agenda, with the ultimate aim of further reducing the burden of morbidity and mortality associated with nutritional aberrations in children with cancer worldwide. This event would not have been possible without the generous support of the Office of International Affairs in the National Cancer Institute, National Institutes of Health; an award from the National Cancer Institute of Canada; the Capitulo Puebla de la Fundacion Mexicana para la Salud; and the Fondo FUNSALUD-AMEH. Local hospitality was provided by the Universidad de las Americas Puebla. The Public Health Agency of Canada funded the publication of this report.

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)0.001
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 score0.036
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.309
Teacher spread0.296 · 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

Citations18
Published2007
Admission routes2
Has abstractyes

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