Metformin and breast cancer risk: A meta-analysis and critical literature review.
Bibliographic record
Abstract
25 Background: Observational studies have suggested that metformin, commonly used for diabetes treatment that increases insulin sensitivity and improves glycemic control, decreases the incidence of several common cancers. However, findings regarding metformin and breast cancer incidence have been mixed. To explore this issue, a systematic literature review and meta-analysis were performed with a focus on potential biases. Methods: We conducted a comprehensive literature search for all pertinent studies addressing metformin use and breast cancer risk by searching Pub Med, Cochrane Library, Scopus (which includes Embase, ISI Web of Science) using the Mesh terms: "metformin" or "biguanides" or "diabetes mellitus, type 2/therapy" and "cancer" or "neoplasms". When multiple hazard ratios (HR) or odds ratio (OR) were reported, the most adjusted estimate was used in the base-case analysis. We pooled the adjusted HR using and performed sensitivity analyses on duration of metformin use (> or < 3 years use), study quality (assessed using the GRADE system), and initial observation year of the cohort (before vs after 1997). Results: From a total of 421 citations, 13 full-text articles were considered, and 7 independent studies were included. All were observational (4 cohort and 3 case control). Our combined OR for metformin association with invasive breast cancer of all 7 studies was 0.83 (95% CI, 0.71-0.97). Funnel plot analyses did not suggest publication bias. Stronger associations were found when analyses were limited to studies estimating the impact of longer metformin duration (OR = 0.75. 95% CI, 0.62-0.91) or among studies that began observing their cohort before 1997 (OR=0.68. 95% CI, 0.55-0.84). Stratification according to study quality did not affect the combined OR but higher quality studies had smaller CI and achieved statistical significance. Interpretation is limited by the observational nature of reports and different comparison groups. Conclusions: Our analyses support a protective effect of metformin on invasive breast cancer incidence among postmenopausal women with diabetes. Clinical trials are needed to determine whether metformin reduces breast cancer risk.
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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 | 0.029 | 0.066 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.032 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".