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Association of neurocognitive impairment and financial hardship in adult survivors of childhood cancer: A report from the Childhood Cancer Survivor Study (CCSS).

2025· article· en· W4410805437 on OpenAlexaff
Daniel J. Zheng, Shalini Bhatia, Sedigheh Mirzaei, Yutaka Yasui, Sogol Mostoufi‐Moab, Kira Bona, Kelly Getz, Richard Aplenc, K. Robin Yabroff, I‐Chan Huang, Pim Brouwers, Tara M. Brinkman, Kim Edelstein, Elyse Richelle Park, Anne C. Kirchhoff, Gregory T. Armstrong, Claire Snyder, Kevin R. Krull, Paul C. Nathan

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHospital for Sick ChildrenPrincess Margaret Cancer CentreUniversity Health Network
FundersAmerican Lebanese Syrian Associated Charities
KeywordsChildhood cancerNeurocognitiveMedicineCancerCancer survivorGerontologyAssociation (psychology)PsychiatryClinical psychologyInternal medicinePsychologyCognitionPsychotherapist

Abstract

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10055 Background: Adult survivors of childhood cancer are at high risk for financial hardship due to the cumulative lifetime costs of cancer-directed therapy and chronic health conditions. Whether neurocognitive impairment increases the risk for financial hardship is unknown. Methods: Childhood cancer survivors (≥ 5-year survivors, diagnosed < 21 years of age between 1970-1999) enrolled in CCSS completed a validated self-report Neurocognitive Questionnaire (NCQ) in 2014 and a subsequent financial hardship survey (age ≥ 26 at survey completion) 3 years later. The NCQ measured neurocognitive impairment in four domains: (1) memory ; (2) task efficiency; (3) organization; (4) emotional regulation. NCQ was the exposure and operationalized as the number of impaired domains (0-4); in each domain, impairment was defined as a Z-score >90 th percentile. Financial hardship outcomes were measured in behavioral (e.g., delaying care due to cost), material (e.g., high out-of-pocket costs), and psychological (e.g., worry about financial situation) domains, as well as two discrete outcomes of debt collection and bankruptcy. Multivariable linear and logistic regressions were used to analyze associations adjusting for age, sex, and race/ethnicity. Results: 3023 survivors completed the NCQ (mean age 38.8, SD=8.6 years) and a subsequent financial hardship survey (mean age 41.5, SD=8.7 years). 13.9%, 8.1%, 6.0%, and 2.6% of survivors had neurocognitive impairments in 1-4 domains, respectively. Individuals with NCQ impairment had significantly higher mean standardized scores across all three financial hardship domains than those without NCQ impairments (Table). Each ordinal increase in the number of impaired NCQ domains was associated with a higher mean standardized score for both behavioral and material financial hardship. Individuals with impairments in all four NCQ domains were more likely to be sent to debt collection (54% vs. 25%, OR=3.82, 95% CI: 2.27-6.43) and file for bankruptcy protection (21% vs. 8%, OR=2.81, 95% CI: 1.53-5.17) compared to those without impairments. Conclusions: Cancer survivors with neurocognitive impairment are particularly vulnerable to financial hardship. This survivor population should be specifically assessed for these outcomes and offered support to prevent and mitigate financial challenges. Standardized mean differences (SMD) of each financial hardship domain by number of NCQ impairments compared to no NCQ impairments. Number of NCQ domains impaired Behavioral Domain SMD (95% CI) Material DomainSMD (95% CI) Psychological DomainSMD (95% CI) 1 0.21 (0.11-0.31) 0.20 (0.10-0.29) 0.41 (0.31-0.50) 2 0.39 (0.27-0.51) 0.32 (0.20-0.44) 0.38 (0.25-0.50) 3 0.48 (0.34-0.63) 0.35 (0.20-0.49) 0.44 (0.30-0.58) 4 0.72 (0.51-0.93) 0.72 (0.52-0.94) 0.74 (0.53-0.94)

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 score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.047
GPT teacher head0.433
Teacher spread0.386 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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