Dietary patterns and risk of bladder cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Several studies have investigated the relationship between dietary patterns and the risk of bladder cancer (BC) in different regions including Europe, the United States, and Asia, with no conclusive evidence. A meta-analysis was undertaken to integrate the most recent information on the relationship between a data-driven Western diet (WD), the Mediterranean diet (MD), and dietary-inflammatory-index (DII) and the risk of BC. Method We looked for published research into the relationship between dietary patterns and the incidence of BC in the PubMed/Medline, Cochrane Library, Web of Science, and Scopus databases up until February 2021. Using a multivariate random-effects model, we compared the highest and lowest categories of WD, MD and DII patterns and provided the relative risk (RR) or odds ratios (OR) and 95 percent confidence intervals (CIs) for the relevant relationships. Results The analysis comprised 12 papers that were found to be suitable after scanning the databases. Both case–control (OR 0.73, 95% CI: 0.52, 0.94; I2 = 49.9%, n = 2) and cohort studies (RR 0.93, 95% CI: 0.88, 0.97; I2 = 63%, n = 4) found a substantial inverse association between MD and BC. In addition, although cohort studies (RR 1.53, 95% CI 1.37, 1.70; I2 = 0%, n = 2) showed a direct association between WD and BC, case–control studies (OR 1.33, 95% CI 0.81, 1.88; I2 = 68.5%, n = 2) did not. In cohort studies, we found no significant association between DII and BC (RR 1.02, 95% CI 0.93, 1.12; I2 = 38.5%, n = 2). In case–control studies, however, a strong direct association between DII and BC was discovered (RR 2.04, 95% CI 1.23, 2.85; I2 = 0%, n = 2). Conclusion The current meta-analysis showed that MD and WD have protective and detrimental effects on BC risk, respectively. No significant association between DII and the risk of BC was observed. More research is still needed to confirm the findings. Additional study is warranted to better understand the etiological mechanisms underlying how different dietary patterns affect BC. Trial registration Protocol registration number:CRD42020155353. Database for protocol registration: The international prospective register of systematic reviews database (PROSPERO). Data of registration: August 2020.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.033 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".