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Treatment and lifestyle profiles of healthy aging survivors: A report from the Childhood Cancer Survivor Study.

2025· article· en· W4410805449 on OpenAlexaff
Timothy J. D. Ohlsen, Kenny Ye, Cindy Im, Rusha Bhandari, Yan Chen, Stephanie B. Dixon, Kirsten K. Ness, Lucie M. Turcotte, Yutaka Yasui, Jennifer M. Yeh, Gregory T. Armstrong, Paul C. Nathan, Claire Snyder, Kevin C. Oeffinger, Eric J. Chow

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineChildhood cancerCancerCancer survivorGerontologyCancer survivorshipSurvivorship curvePediatricsInternal medicine

Abstract

fetched live from OpenAlex

10058 Background: Survivors of childhood cancer are at elevated risk for adverse health outcomes, but many maintain excellent health throughout adulthood. We sought to characterize the trajectories of, and examine factors associated with, healthy aging across the lifespan. Methods: We longitudinally surveyed ≥5 y cancer survivors (18-64 y) and sibling controls enrolled in the Childhood Cancer Survivor Study. “Healthy aging” was defined by 1) having a cumulative number of severe or life-threatening (i.e., grade 3+) chronic health conditions (CHCs) less than or equal to the mean of same age, same sex sibling controls; and 2) having no functional impairment or activity limitations. We then examined prevalences of healthy aging and its 2 component domains across survivor age groups ( < 30, 30-39, 40-49, ≥50 y). Multivariable logistic regression models adjusted for demographic, treatment, and lifestyle factors at cohort entry estimated risk factors for healthy aging among survivors. Results: We analyzed 17,263 survivors (median age 39 y, IQR 32-46) and 3,378 siblings. Among all sibling age/sex groups, mean grade 3+ CHC counts were < 1. Of survivors, 53.4% (95% CI 52.7-54.2) had no Grade 3+ CHC, and 71.4% (95% CI 70.7-72.1) reported no functional impairment. Overall, 45.0% (95% CI 44.2-45.7) of survivors met criteria for healthy aging, but this prevalence decreased with age (Table). In multivariable analysis, treatment factors associated with lower odds of healthy aging included anthracycline dose (≥250 mg/m 2 vs none: OR 0.60, 95% CI 0.52-0.69), alkylator dose (≥8 g/m 2 vs none: OR 0.76, 95% CI 0.67-0.86), and stem cell transplant (OR 0.60, 95% CI 0.41-0.89). High doses of radiation to any site were also associated with less healthy aging (e.g., ≥30 Gy to brain vs none: OR 0.22, 95% CI 0.19-0.26). Baseline physical activity > 180 min/week was associated with healthy aging (vs < 180 min: OR 1.23, 95% CI 1.11-1.37). Underweight, overweight, and obese baseline BMIs had lower odds of healthy aging compared with normal BMI (ORs 0.54 to 0.82, each p < 0.05). Survivors treated in more recent decades were more likely to experience healthy aging (1990s vs 1970s: OR 1.26, 95% CI 1.06-1.50) even after adjusting for attained age. Conclusions: Among childhood cancer survivors, the prevalence of healthy aging declines with age but has improved in more recent treatment eras. Higher levels of exercise and normal BMI at baseline were associated with subsequent healthy aging, suggesting that the trajectory of aging could be improved through targeted interventions. Prevalence (%) of outcomes across survivor age groups (95% CI). <30 y 30-39 y 40-49 y ≥50 y CHC count ≤ sibling mean for age/sex 67.4 (65.8, 69.0) 59.3 (58.1, 60.5) 47.5 (46.2-48.9) 34.4 (32.6-36.2) No functional impairment 76.0 (74.6, 77.5) 73.9 (72.8, 74.9) 69.4 (68.2-70.7) 64.1 (62.3-65.9) Healthy aging 58.0 (56.3, 59.7) 50.8 (49.5, 52.0) 39.2 (37.8-40.5) 27.2 (25.5-28.9)

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)0.001
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
Metaresearch0.0010.001
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 science0.0000.000
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 head0.106
GPT teacher head0.497
Teacher spread0.392 · 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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