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Record W1973820468 · doi:10.1002/ijc.25433

Quality of life during active treatment for pediatric acute lymphoblastic leukemia

2010· article· en· W1973820468 on OpenAlexafffund
Lillian Sung, Rochelle Yanofsky, Robert J. Klaassen, David Dix, Sheila Pritchard, Naomi Winick, Sarah Alexander, Anne F. Klassen

Bibliographic record

VenueInternational Journal of Cancer · 2010
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster UniversityChildren's Hospital of Eastern OntarioUniversity of ManitobaUniversity of TorontoSickKids FoundationUniversity of British ColumbiaHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsMedicinePsychosocialQuality of life (healthcare)Confidence intervalPediatricsLymphoblastic LeukemiaPopulationPhysical therapyInternal medicineLeukemiaPsychiatry

Abstract

fetched live from OpenAlex

The objectives of the study were to describe quality of life (QoL), identify predictors of worse QoL and examine QoL during different phases of active therapy for acute lymphoblastic leukemia (ALL). A multiinstitutional cross-sectional study was performed in children with ALL. We included children at least 2 months from diagnosis who were receiving treatment in first remission. Parents described QoL using the PedsQL 4.0 Generic Core Scales and the PedsQL 3.0 Acute Cancer Module. The 206 children on treatment for ALL had overall [median 62.5, 95% confidence interval (CI) 34.8-94.4], physical (median 62.5, 95% CI 18.8-100.0) and psychosocial (median 65.4, 95% CI 38.3-94.2) summary scores that were one to two standard deviations lower than population norms. In high-risk ALL, girls and older children had worse QoL. In standard-risk ALL, those with lower household incomes and unmarried parents had worse QoL. QoL scores were generally constant across phases of ALL therapy. Children on therapy for ALL have lower QoL compared to healthy children. Age and gender predicted QoL in high-risk ALL, whereas socioeconomics predicted QoL in standard-risk ALL. Future efforts should focus on longitudinal studies that describe QoL over time within individual patients.

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 score0.293
Threshold uncertainty score0.482

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 head0.030
GPT teacher head0.383
Teacher spread0.354 · 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

Citations123
Published2010
Admission routes2
Has abstractyes

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