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Record W2003708878 · doi:10.1002/cncr.22546

Osteopenia and cancer in children and adolescents

2007· review· en· W2003708878 on OpenAlexaff
Alessandra Sala, Ronald D. Barr

Bibliographic record

VenueCancer · 2007
Typereview
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineOsteopeniaOsteoporosisPeak bone massCancerBone mineralPediatricsInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

The attainment of a satisfactory peak bone mass, which is accomplished largely by the end of adolescence, is the best protection against excessive bone mineral loss in late adulthood. Factors that influence this process include age, race, sex, body size, pubertal status, diet, physical activity, and other lifestyle elements. Cancer and its treatment in children and teenagers adversely impact bone mineralization. In particular, chemotherapy (especially glucocorticosteroids and methotrexate) and cranial irradiation (apparently by reducing growth hormone secretion and by causing hypogonadotropic hypogonadism) interfere with normal bone turnover. Resorption often exceeds formation, resulting in net bone mineral loss and providing a rational basis for the use of antiresorptive drugs. Such osteopenia may be symptomatic, with pain and abnormal gait, and increases the risk of fractures several fold. The disorder is compounded by reduced physical activity, so programs to reduce this deficit are of measurable benefit. All of those engaged in the care of children and adolescents with cancer have an opportunity to improve the bone health of these young people and to limit their risk of developing osteoporosis and fragility fractures in adult life.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.868
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.044
GPT teacher head0.410
Teacher spread0.366 · 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 designOther design
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

Citations70
Published2007
Admission routes1
Has abstractyes

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