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Record W4411046343 · doi:10.1001/jamaoncol.2025.1340

Body Mass Index, Physical Activity, and Subsequent Neoplasm Risk Among Childhood Cancer Survivors

2025· article· en· W4411046343 on OpenAlexaboutno aff
Lenat Joffe, Sedigheh Mirzaei, Shalini Bhatia, Himani Darji, Kirsten K. Ness, Aron Onerup, Elena J. Ladas, Cindy Im, Philip J. Lupo, Kevin C. Oeffinger, Danielle Novetsky Friedman, Rebecca M. Howell, Miriam Conces, Michael Arnold, Gregory T. Armstrong, Joseph P. Neglia, Yutaka Yasui, Nina S. Kadan‐Lottick, Lucie M. Turcotte

Bibliographic record

VenueJAMA Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsMedicineBody mass indexCancerCohortCohort studyPediatricsCancer registryInternal medicineYoung adult

Abstract

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Importance: High body mass index (BMI) and low physical activity levels are risk factors for adult-onset cancers. Limited data exist on their relationship with subsequent neoplasms among childhood cancer survivors. Objective: To evaluate associations between time-varying BMI/physical activity and subsequent neoplasm risk among childhood cancer survivors. Design, Setting, and Participants: This retrospective cohort analysis included 5-year childhood cancer survivors diagnosed younger than 21 years of age between 1970 and 1999, enrolled in the Childhood Cancer Survivor Study (CCSS), with follow-up through September 2019 at pediatric tertiary care hospitals in the US and Canada. The data analysis was performed between March 2021 and July 2024. Exposures: Self-reported time-varying BMI and maximum reported physical activity (metabolic equivalent of task h/wk [MET-h/wk]) before any subsequent neoplasm development; first assessed at cohort entry and up to 6 times thereafter. Main Outcomes and Measures: Cumulative incidence by physical activity level and relative rates (RRs) by physical activity and time-varying BMI categories, adjusted for demographic and clinical variables, were estimated for any, subtype (hematologic, solid organ, central nervous system [CNS], skin), and specific (breast, thyroid, colorectal, meningioma) subsequent neoplasms using piecewise exponential models. Results: Of 25 658 enrolled CCSS participants, 22 716 had BMI data before subsequent neoplasm development and met eligibility criteria for this study (46.3% female; median [range] attained age, 33.7 [5.7-67.3 years]). Among 22 716 survivors, 2554 subsequent neoplasms occurred among 2156 individuals (56.7% female; median [range] age at subsequent neoplasm diagnosis, 37.4 [13.7-63.3] years). Survivors reporting lower physical activity had higher 30-year subsequent neoplasm cumulative incidence: 18.6% (95% CI, 17.0-20.3) for 0 MET-h/wk vs 10.9% (95% CI, 9.9-12.1) for 15-21 MET-h/wk. Obese BMI was associated with increased incidence rates of solid organ (RR, 1.22; 95% CI, 1.01-1.46), CNS (RR, 1.47; 95% CI, 1.12-1.95), and skin (RR, 1.30; 95% CI, 1.13-1.50) subsequent neoplasms. Higher physical activity (15-21 MET-h/wk) demonstrated a protective association for any (RR, 0.61; 95% CI, 0.53-0.71), solid organ (RR, 0.65; 95% CI, 0.52-0.83), CNS (RR, 0.50; 95% CI, 0.35-0.70), and skin (RR, 0.72; 95% CI, 0.60-0.86) subsequent neoplasms. BMI and physical activity were specifically associated with subsequent meningiomas and thyroid carcinomas, but not with breast or colorectal cancers, nor hematologic subsequent neoplasms. Conclusions and Relevance: Among childhood cancer survivors in this cohort study, obesity was associated with an increased risk for multiple subsequent neoplasm types, while higher physical activity was associated with reduced subsequent neoplasm risk. Lifestyle interventions should be considered in future subsequent neoplasm prevention research.

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)0.000
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 score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.333
Teacher spread0.319 · 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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Citations5
Published2025
Admission routes1
Has abstractyes

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