Data from Lifetime Physical Activity and the Risk of Non-Hodgkin Lymphoma
Bibliographic record
Abstract
Abstract Research regarding the association between physical activity and the risk of non-Hodgkin lymphoma (NHL) is limited and inconsistent, and few studies have investigated whether the intensity and timing of physical activity influence the association. A case–control study of NHL was conducted in British Columbia, Canada, in 2000 to 2004. Data were collected on various NHL risk factors, including moderate-intensity and vigorous-intensity physical activity performed over the lifetime. Logistic regression was used to estimate the association between physical activity and the risk of NHL. This analysis included 818 controls and 749 cases. Lifetime vigorous-intensity physical activity was inversely associated with NHL risk. Participants in the second, third, and fourth quartiles of lifetime vigorous-intensity physical activity had an approximately 25% to 30% lower risk of NHL than those in the lowest quartile [adjusted odds ratios, 0.69 (95% confidence interval [CI], 0.52–0.93); 0.68 (95% CI, 0.50–0.92); and 0.75 (95% CI, 0.55–1.01), respectively]. No consistent associations were observed for total or moderate-intensity physical activity. There were no apparent age periods in which physical activity appeared to confer a greater risk reduction. In this study, we found that lifetime vigorous-intensity physical activity was associated with a significantly reduced risk of NHL. Given this finding, more research on physical activity intensity and timing in relation to NHL risk is warranted. Cancer Epidemiol Biomarkers Prev; 24(5); 873–7. ©2015 AACR.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".