Fruit and Vegetable Consumption and the Risk of Prostate Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Emerging researches has evaluated whether fruit and vegetable consumption reduce the risk of prostate cancer. However, the conclusions of published articles remained confusing. Thus, we conducted an updated systematic review and meta-analysis to confirm the relationship of fruit and vegetable consumption and the risk of prostate cancer. METHOD: We searched PubMed, EMBASE, Web of Science and Chinese National Knowledge Infrastructure (CNKI) up to September 1, 2020. We finally included 17 cohort studies related to fruit or vegetable intake after rigid quality assessment and checking references of the retrieved articles and relevant reviews. Newcastle-Ottawa scale was adopted to assess the quality of studies and random effect model with RR and 95% CI were used to assess the risk. RESULTS: No significant relationship was found between fruit consumption (RR = 1.00, 95% CI = 0.94-1.05) and vegetable consumption (RR = 0.98, 95% CI = 0.94-1.02) and the risk of prostate cancer. No significant heterogeneity or publication bias was identified. CONCLUSION: Our updated meta-analysis demonstrated that fruit and vegetable consumption can barely reduce the risk of prostate cancer with several limitations. Further clinical and basic researches are eagerly awaited to confirm our results and clarify the potential biological mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".