02 Prevalence of obesity and its impact on outcome in children diagnosed with cancer in Canada: A population-based study
Bibliographic record
Abstract
Abstract Background Childhood obesity can result in adverse health outcomes. Objectives Objectives were to describe the prevalence of obesity and determine the association between obesity at cancer diagnosis and event-free survival (EFS) and overall survival (OS) in children diagnosed with cancer in Canada. Design/Methods We conducted a retrospective cohort study using the Cancer in Young People in Canada database, a population-based surveillance program collecting data from all paediatric cancer patients. This study included all children with newly diagnosed cancer aged 2 to 18 years across Canada from 2001 to 2020. Obesity was defined as age and sex-adjusted body mass index ≥ 95th percentile. EFS was defined as the time from diagnosis to first event (relapse, progression, secondary malignancies, or death). Univariate and multivariable Cox proportional hazards models compared EFS and OS between patients with and without obesity. Results A total of 11,291 patients were included (37.1% leukemias, 14.5% lymphomas, 21.8% central nervous system (CNS) tumors, 26.6% non-CNS solid tumors). At diagnosis, 10.5% were obese and the prevalence of obesity was significantly higher at 1 year (15.7%, p<0.001) and 2 years (20.1%, p<0.001) after diagnosis. The prevalence of obesity was higher in the leukemia and lymphoma cohort compared to other cancer categories (11.4% vs. 9.5%, p=0.001). In multivariable models controlling for age at diagnosis, sex, ethnicity, neighborhood income quintile, treatment era and cancer categories, obesity at diagnosis remained significantly associated with inferior EFS [adjusted HR (aHR) 1.16, 95% CI 1.02–1.32] and OS [aHR 1.29, 95% CI 1.11–1.49]. In children with acute lymphoblastic leukemia (ALL) (n=3458, 82.5% of all leukemias), after adjusting for high-risk features such as age, white blood cell count and CNS status, obesity at diagnosis remained significantly associated with inferior EFS [aHR 1.55, 95% CI 1.17–2.04] and OS [aHR 1.75, 95% CI 1.23–2.49]. In patients with CNS tumors, obesity at diagnosis was also independently associated with inferior EFS [aHR 1.38, 95% CI 1.09–1.76] and OS [aHR 1.47, 95% CI 1.13–1.91]. Conclusion In this population-based study of children with cancer, the prevalence of obesity was 11% at diagnosis and continued to increase in the following 2 years. Obesity at cancer diagnosis was independently associated with inferior survival across the entire cohort, especially in children with ALL and CNS tumors. Prevention of childhood obesity should be emphasized as it can lead to several adverse health outcomes in children with cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".