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Record W4385494067 · doi:10.1016/j.jtct.2023.07.024

Financial Hardship in Childhood Cancer Survivors Treated with Hematopoietic Cell Transplantation: A Report from the Childhood Cancer Survivor Study

2023· article· en· W4385494067 on OpenAlexaff
David Buchbinder, Neel S. Bhatt, Huiqi Wang, Yutaka Yasui, Saro H. Armenian, Smita Bhatia, Eric J. Chow, I‐Chan Huang, Anne Kirchoff, Wendy M. Leisenring, Elyse R. Park, K. Robin Yabroff, Gregory T. Armstrong, Paul C. Nathan, Nandita Khera

Bibliographic record

VenueTransplantation and Cellular Therapy · 2023
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Cancer Institute
KeywordsFinanceChildhood cancerLogistic regressionMedicineConfidence intervalPopulationSiblingDemographyCancerPsychologyGerontologyInternal medicineDevelopmental psychologyEnvironmental healthEconomics

Abstract

fetched live from OpenAlex

Long-term survivors of childhood cancer are at risk for financial hardship. However, it is not known if HCT leads to an incremental change in financial hardship for survivors who received it versus those who did not. We examined financial outcomes among adult survivors of childhood cancer who had undergone HCT. Using a cross-sectional survey in the Childhood Cancer Survivor Study population between 2017 and 2019, self-reported financial hardship was compared between survivors who received HCT, survivors treated without HCT ("non-HCT"), and siblings and categorized into 3 domains: material hardship/financial sacrifices, behavioral, and psychological hardship. The standardized score of each domain of financial hardship was calculated by adding the item responses and dividing by the standard deviation among siblings. Multivariable linear and logistic regression were used to evaluate associations between sociodemographic characteristics, cancer diagnosis, post-treatment complications, and financial hardship among survivors. The mean adjusted score for each hardship domain was not significantly different between HCT survivors (n = 133) and non-HCT survivors (n = 2711); mean differences were .18 (95% confidence interval [CI], -.05 to .41) for material hardship/financial sacrifices, .07 (95% CI, -.18 to .32) for behavioral hardship, and .19 (95% CI, -.04 to .42) for psychological hardship. Within specific items, a higher proportion of survivors treated with HCT reported greater financial hardship compared to non-HCT survivors. HCT survivors also had significantly higher mean domain scores compared to sibling controls (n = 1027) in all domains. Household income and chronic health conditions, but not HCT, were associated with financial hardship among all survivors. Adult survivors of childhood cancer treated with HCT do not report greater overall financial hardship compared to non-HCT survivors but do report greater overall financial hardship compared to sibling controls. Surveillance and intervention may be necessary for all survivors regardless of HCT status.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.282
Teacher spread0.259 · 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 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

Citations4
Published2023
Admission routes1
Has abstractno

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