Association Between Metformin Use and Risk of Prostate Cancer and Its Grade
Bibliographic record
Abstract
BACKGROUND: Metformin is commonly prescribed to treat type 2 diabetes. Recent evidence suggests that it may possess antitumoral properties. The aim of this study was to test the association between metformin use and risk of prostate cancer and its grade among men with diabetes. METHODS: Data were obtained from population-based health-care administrative databases in Ontario, Canada. This retrospective cohort study used a nested case-control approach to examine the relationship between metformin exposure and the risk of prostate cancer within a cohort of incident diabetic men aged 66 years or older. We conducted four case-control analyses, defining case subjects as 1) any prostate cancer, 2) high-grade, 3) low-grade, and 4) biopsy-diagnosed. In each analysis, case subjects were matched to five control subjects on age and cohort entry date. Metformin exposure was determined based on prescriptions before cancer diagnosis, and adjusted odds ratios (aOR) were estimated using conditional logistic regression. All statistical tests were two-sided. RESULTS: Within our cohort of 119 315 men with diabetes, there were 5306 case subjects with prostate cancer and 26 530 matched control subjects. Within the cancer case subjects, 1104 had high- grade cancer, 1719 had low-grade cancer, and 3524 had biopsy-diagnosed cancer. There was no association between metformin use and risk of any prostate cancer (aOR = 1.03, 95% confidence interval [CI] = 0.96 to 1.1), high-grade cancer (aOR = 1.13, 95% CI = 0.96 to 1.32), low-grade cancer (aOR = 0.94, 95% CI = 0.82 to 1.06), or biopsy-diagnosed cancer (aOR = 0.98, 95% CI = 0.84 to 1.02). CONCLUSIONS: This large study did not find an association between metformin use and risk of prostate cancer among older men with diabetes, regardless of cancer grade or method of diagnosis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".