Postdiagnosis sedentary behavior and health outcomes in cancer survivors: A systematic review and meta‐analysis
Bibliographic record
Abstract
Background High levels of sedentary behavior may negatively affect health outcomes in cancer survivors. A systematic review and meta‐analysis was performed to clarify whether postdiagnosis sedentary behavior is related to survival, patient‐reported outcomes, and anthropometric outcomes in cancer survivors. Methods The Ovid MEDLINE, EMBASE, CINAHL (The Cumulative Index to Nursing and Allied Health Literature), and SPORTDiscus databases were searched from study inception to June 2019. Studies of adults who had been diagnosed with cancer that examined the association between sedentary behavior and mortality, patient‐reported outcomes (eg, fatigue, depression), or anthropometric outcomes (eg, body mass index, waist circumference) were eligible for inclusion. Meta‐analyses were performed to estimate hazard ratios for the highest compared with the lowest levels of sedentary behavior for all‐cause and colorectal cancer‐specific mortality outcomes. The ROBINS‐E (Risk of Bias in Nonrandomized Studies‐of Exposures tool) and the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) system were used to assess the risk of bias and the strength of evidence, respectively. Results Thirty‐three eligible publications from a total of 3569 identified articles were included in the review. A higher level of postdiagnosis sedentary behavior was associated with an increased risk of all‐cause mortality (hazard ratio, 1.22; 95% CI, 1.06‐1.41; heterogeneity [I2 statistic], 33.8%) as well as colorectal cancer‐specific mortality (hazard ratio, 1.53; 95% CI, 1.14‐2.06; I2, 0%). No clear or consistent associations between sedentary behavior and patient‐reported or anthropometric outcomes were identified. The risk of bias in individual studies ranged from moderate to serious, and the strength of evidence ranged from very low to low. Conclusions Although avoiding high levels of sedentary behavior after a cancer diagnosis may improve survival, further research is required to help clarify whether the association is causal.
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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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.036 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".