The Association between Leisure Time Physical Activity and Pancreatic Cancer Risk in Adults: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
We conducted a meta-analysis of the association between leisure time physical activity (LTPA) and risk of pancreatic cancer to update previous analyses in light of newly published studies, to examine subgroups of interest and potential sources of heterogeneity. We searched the PubMed and MEDLINE databases for studies until February 2015. Study information was collected using a standardized form to abstract relevant data on study design, number of cases, participant and study characteristics, assessment of LTPA, risk estimates, and adjustments for confounding by two independent abstractors. We used random-effects models to pool estimates from included studies of lowest versus highest comparison of LTPA. The search identified 26 studies eligible for inclusion into the meta-analysis. The combined summary risk estimate was [relative risk (RR), 0.89; 95% confidence interval (CI), 0.82-0.96]. There was evidence of heterogeneity across studies (I(2) = 22.1%, Pheterogeneity = 0.130). Some of the heterogeneity could be explained by study design, with stronger protective effects observed among case-control studies (RR, 0.69; 95% CI, 0.59-0.81) compared with cohort studies (RR, 0.96; 95% CI, 0.91-1.02). Across study designs, age of population was a source of heterogeneity, with stronger effects observed among younger (<50 years) populations. The present meta-analysis supports a protective association between LTPA and pancreatic cancer with an 11% risk reduction observed. LTPA appears to have the strongest effect among young populations. Additional investigations are needed to provide insights regarding the impact of LTPA in healthy adult populations, to reduce the risk of pancreatic cancer and encourage increases in LTPA.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.050 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".