제 2형 당뇨병 환자의 유방암 발생 위험 및 사망률에 대한 메트포민의 영향 : 체계적 문헌고찰 및 메타분석
Bibliographic record
Abstract
Background: The protective effect of metformin against breast cancer is inconclusive. Objective: To evaluate the effect of metformin on breast cancer risk and mortality in patients with type 2 diabetes. Method: A comprehensive literature search was performed for pertinent articles published prior to June 30, 2014, using PubMed and EMBASE. Study heterogeneity was estimated with I2 statistic. The data from the included studies were pooled and weighted by random-effects model. The quality of each included study was assessed on the basis of the 9-star Newcastle-Ottawa Scale and publication bias was evaluated by visual inspection of a funnel plot. Results: Ten studies were included in the meta-analysis of the association of metformin and breast cancer risk. By synthesizing the data from the studies, the pooled odds ratio (OR) was 0.72 (95% CI: 0.59, 0.87) (p = 0.0005). Three cohort studies were included for meta-analysis of the association between metformin and breast cancer- related mortality. Metformin was associated with a significant decrease in mortality (Risk ratio: 0.68; 95% CI: 0.51, 0.90, p = 0.007). Conclusion: The present metaanalysis suggests that metformin appears to be associated with a lower risk of breast cancer incidence and mortality in patients with type 2 diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".