Cardiorespiratory Fitness as a Predictor of Cancer Mortality Among Men With Pre-Diabetes and Diabetes
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article was to examine the risk of cancer mortality across levels of fitness and to examine the fitness-mortality relation for site-specific cancers in men with pre-diabetes and diabetes. RESEARCH DESIGN AND METHODS: We examined the fitness-mortality relation for all-cause and site-specific cancer mortality among 18,858 men with pre-diabetes and 2,805 men with diabetes (aged 46.3 +/- 9.7 years [mean +/- SD]) from the Aerobics Center Longitudinal Study. We identified 719 cancer deaths during 354,558 person-years of risk. The duration of follow-up was 16.4 +/- 7.8 years (range <1-30.0 years). RESULTS: In men with pre-diabetes, moderate (hazard ratio 0.71 [95% CI 0.57-0.88]) and high fitness (0.76 [0.60-0.96]) were associated with lower risks of cancer mortality compared with the low-fit group in a model adjusted for age, examination year, smoking, alcohol use, fasting glucose concentration, previous cancer, and BMI. Similarly, for individuals with diabetes, moderate (0.53 [0.35-0.82]) and high fitness (0.44 [0.26-0.73]) were associated with lower risks of cancer mortality compared with the low-fit group. Among all men, being fit was associated with a lower risk of mortality from gastrointestinal (0.55 [0.39-0.77]), colorectal (0.53 [0.30-0.96]), liver (0.22 [0.07-0.71]), and lung cancer (0.43 [0.30-0.60]). CONCLUSIONS: In men with pre-diabetes and diabetes, higher levels of cardiorespiratory fitness were associated with lower risk of cancer mortality, particularly as a result of cancers of the gastrointestinal tract, compared with those who had low levels of fitness.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".