Meta Analysis the Effect of Physical Activity on Survival Life in Breast Cancer Patients
Bibliographic record
Abstract
Background: Physical activity has a positive role in breast cancer risk. Physical activity intensity is often expressed as metabolic equivalents (METs) and the analytic guidelines for international physical activity questionnaires define low activity as 4 METs and high activity as 8 METs. This study aims to estimate the effect of physical activity on the survival of breast cancer survivors based on a number of previous similar studies.Subjects and Method: This study is a systematic review and meta-analysis study. The articles used in this study were obtained from several databases including PubMed, Science Direct, Google Scholar, and Springer Link. The articles used in this study were those published from 2000-2020. The population in the study were breast cancer survivors with an intervention in the form of high physical activity. Comparison, namely low physical activity, and an outcome in the form of survival. Keywords for searching articles are as follows: "physical activity" AND "breast cancer survivors" AND "lifesustainability" OR "survival" AND "breast cancer" AND "adjusted hazard ratio" AND "cohort". The articles included in this study are full text articles with a cohort study design. Articles were collected using PRISMA flow diagrams. Articles were analyzed using the Review Manager 5.3 application.Results: There were 8 articles originating from Denmark, Norway, Canada, Germany and the United States. The results of the meta-analysis showed that physical activity was statistically significant in increasing the survival of breast cancer survivors (HR= 0.74 95% CI= 0.63 to 0.87; p= 0.0003) and I² = 0%.Conclusion: High physical activity increases the survival of breast cancer survivors.Keywords: High physical activity, survival, breast cancer survivorsCorrespondence: Enge Surabina Ketaren. Masters Progam in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta 57126, Central Java. Email: ketarenenge3@gmail.com. Mobile: 087838583646.Indonesian Journal of Medicine (2021), 06(01): 32-41https://doi.org/10.26911/theijmed.2021.06.01.04.
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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 | 0.018 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.070 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".