Association between recorded physical activity and cancer progression or mortality in individuals diagnosed with cancer in South Africa
Bibliographic record
Abstract
OBJECTIVES: This study aimed to determine the association between progression and mortality in individuals with stage 1 cancer and their recorded physical activity before the diagnosis of the cancer. METHODS: We included 28 248 members with stage 1 cancers enrolled in an oncology programme in South Africa. Physical activity was recorded using fitness devices, logged gym sessions and participation in organised fitness events. Levels of physical activity over the 12 months before cancer diagnosis were categorised as no physical activity, low physical activity (an average of <60 min/week) and moderate to high physical activity (≥60 min/week). Measured outcomes were time to progression, time to death and all cause mortality. RESULTS: Physically active members showed lower rates of cancer progression and lower rates of death from all causes. The HR for progression to higher stages or death was 0.84 (95% CI 0.79 to 0.89), comparing low activity with no physical activity, and 0.73 (95% CI 0.70 to 0.77), comparing medium to high physical activity with no physical activity. The HR for all cause mortality was 0.67 (95% CI 0.61 to 0.74), comparing low physical activity with no activity, and 0.53 (95% CI 0.50 to 0.58), comparing medium to high physical activity with no physical activity. CONCLUSIONS: Individuals engaging in any level of recorded physical activity showed a reduced risk of cancer progression or mortality than those not physically active. There was a further reduction among individuals with moderate to high levels of physical activity compared with those with lower levels.
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 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 | 0.001 | 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".