Association Between Diabetes and Risk of Prostate Cancer: A Systematic Review and Meta-Analysis of Observational Studies
Bibliographic record
Abstract
PURPOSE: Metabolic diseases such as diabetes mellitus may play a role in the development and progression of prostate cancer (PC); however, this association remains to be explored in the context of specific PC stages. The objective of this study was to systematically review the evidence for an association between diabetes and overall, early, or advanced PC risk. MATERIALS AND METHODS: A systematic review with meta-analysis was performed (MEDLINE, EMBASE, and CINAHL) from inception until September 2023. Cohort and case-control studies that assessed PC risk in adult males (≥18 years) associated with type 2 diabetes mellitus or diabetes (if there was no distinction between diabetes type) were included. The Newcastle-Ottawa Scale (NOS) was used to assess study bias; those with NOS<7 were excluded. Evidence certainty was assessed with the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) method. RESULTS: Thirty-four studies (n=26 cohorts and n=8 case-controls) were included. Of these, 32 assessed diabetes and all PC stages combined, 12 included early PC stages, and 15 included advanced PC stages. Our meta-analysis showed diabetes had a protective effect against early PC development (n=11, risk ratio [RR]=0.71; 95% confidence interval [CI]=0.61-0.83, I²=84%) but no association was found for combined (n=21, RR=0.95; 95% CI=0.79-1.13, I²=99%) or advanced PC stages (n=15, RR=0.96; 95% CI=0.77-1.18, I²=98%) at diagnosis. According to GRADE, the evidence certainty was very low. CONCLUSIONS: Diabetes may be protective against early PC stages, yet evidence linking diabetes to risk across all stages, and advanced PC specifically, is less conclusive. High heterogeneity may partially explain discrepancy in findings and was mostly associated with study design, method used for PC diagnosis, and risk measures. Our results may aid risk stratification of males with diabetes and inform new approaches for PC screening in this group, especially considering the reduced sensitivity of prostate-specific antigen values for those with diabetes.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.030 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".