Association of Exercise With Mortality in Adult Survivors of Childhood Cancer
Bibliographic record
Abstract
Importance: Adult survivors of childhood cancer are at excess risk for mortality compared with the general population. Whether exercise attenuates this risk is not known. Objective: To examine the association between vigorous exercise and change in exercise with mortality in adult survivors of childhood cancer. Design, Setting, and Participants: Multicenter cohort analysis among 15 450 adult cancer survivors diagnosed before age 21 years from pediatric tertiary hospitals in the United States and Canada between 1970 and 1999 enrolled in the Childhood Cancer Survivor Study, with follow-up through December 31, 2013. Exposures: Self-reported vigorous exercise in metabolic equivalent task (MET) hours per week. The association between vigorous exercise and change in vigorous exercise and cause-specific mortality was assessed using multivariable piecewise exponential regression analysis to estimate rate ratios. Main Outcomes and Measures: The primary outcome was all-cause mortality. Secondary end points were cause-specific mortality (recurrence/progression of primary malignant neoplasm and health-related mortality). Outcomes were assessed via the National Death Index. Results: The 15 450 survivors had a median age at interview of 25.9 years (interquartile range [IQR], 9.5 years) and were 52.8% male. During a median follow-up of 9.6 years (IQR, 15.5 years), 1063 deaths (811 health-related, 120 recurrence/progression of primary cancer, 132 external/unknown causes) were documented. At 15 years, the cumulative incidence of all-cause mortality was 11.7% (95% CI, 10.6%-12.8%) for those who exercised 0 MET-h/wk, 8.6% (95% CI, 7.4%-9.7%) for 3 to 6 MET-h/wk, 7.4% (95% CI, 6.2%-8.6%) for 9 to 12 MET-h/wk, and 8.0% (95% CI, 6.5%-9.5%) for 15 to 21 MET-h/wk (P < .001). There was a significant inverse association across quartiles of exercise and all-cause mortality after adjusting for chronic health conditions and treatment exposures (P = .02 for trend). Among a subset of 5689 survivors, increased exercise (mean [SD], 7.9 [4.4] MET-h/wk) over an 8-year period was associated with a 40% reduction in all-cause mortality rate compared with maintenance of low exercise (rate ratio, 0.60; 95% CI, 0.44-0.82; P = .001). Conclusions and Relevance: Vigorous exercise in early adulthood and increased exercise over 8 years was associated with lower risk of mortality in adult survivors of childhood 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".