Soy Foods Intake in Adolescence and the Risk of Breast Cancer:A Systematic Review
Bibliographic record
Abstract
Objective To assess the influence of soy foods intake in Adolescence on the female adult's breast cancer.Methods Literatures about the influence of soy foods intake in Adolescence on the female adult's breast cancer were retrieved in The Cochrane Library,MEDLINE,EMbase,CNKI,VIP,WanFang Data and CBM from the date of their establishment to August 2011,meanwhile,the references of included papers were also retrieved.The data were extracted according to the inclusion and exclusion criteria by two reviewers independently,the quality of the included studies was assessed according to the Cochrane Newcastle-Ottawa scale and GRAEDprofiler 3.2.2,and meta-analysis was conducted by using Stata 11.0.Results A total of 6 studies involving 6609 patients and 79538 controls were included.The results of meta-analyses showed that compared with the non-intake or low intake of soy foods in Adolescence,high soy foods intake in Adolescence was associated with lower risk of breast cancer(OR=0.816,95%CI 0.670 to 0.993);In the subgroup analysis,soy foods intake in Adolescence was more effective to prevent premenopausal(OR=0.661,95%CI 0.550 to 0.796) rather than post-menopausal(OR=0.782,95%CI 0.486 to 1.259) breast cancer;and the effects of soy foods intake in Adolescence were not significantly different between the eastern(OR=0.793,95%CI 0.569 to 1.105) and western(OR=0.837,95%CI 0.743 to 0.943) women.Conclusion Soy foods intake in Adolescence may be associated with a small reduction in the risk of adults' breast cancer,especially for the premenopausal women,though there is no difference between the eastern and western women.However,restricted by quantity and quality of the studies,this conclusion should be confirmed by more studies.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".