Abstract PD03-03: Metformin and Cancer Risk in Diabetic Patients: A Systematic Review and Meta-Analysis, with Special Emphasis to Breast Cancer
Bibliographic record
Abstract
Abstract Background: Metformin (M), an insulin-lowering agent, has been associated with decreased cancer risk in epidemiological studies in diabetic patients in comparison with other antidiabetic treatments. Methods: We performed a comprehensive literature search and meta-analysis of epidemiological studies to assess the effect of M on cancer incidence and mortality in diabetic patients, using Pubmed, ISI-Web of Science (Science Citation Index Expanded), Embase, and the Cochrane library until June 2010, with no language or time restrictions. A manual search was also done for references cited in the selected articles, reviews or books. Published independent reports with sufficient information to allow adequate risk estimation of cancer risk/mortality and a corresponding measure of uncertainty after M use compared with other diabetic treatments were reviewed. Association between M and cancer incidence/mortality was computed as a summary relative risk (SRR) with 95% confidence intervals. Random effects models were applied to take into account heterogeneity. Sensitivity analyses were carried out to verify stability of the estimates. Publication bias was investigated using funnel plots and the Macaskill regression test. Results: Eleven studies were selected for relevance in terms of intervention, population studied, independence and reporting of cancer incidence or mortality data, reporting 4042 cancer events and 529 cancer deaths. A significant 31% reduction (overall SRR=0.69, 95%CI, 0.61-0.79) was found in subjects taking M compared with other antidiabetic drugs. The protective effect was significant for pancreatic and hepatocellular cancer, and non-significant trends were noted for colon, and prostate and breast cancer (BC). A non significant protective effect of M on BC incidence was found (SRR=0.75, 95% CI, 0.44-1.29; p for heterogeneity = 0.09, I2=59%). Conclusion: Among diabetics, M use is associated with a significant inverse association with any cancer incidence and a promising trend on BC incidence as compared with other diabetic treatments, including insulin. Further prospective studies of M as a cancer preventive agent are warranted. For breast cancer, Libby et al (Diabetes Care 2009;32:1620-25) found a non-significant trend for a protective effect on M users vs. not users (HR=0.6, 0.32-1.10), whereas Currie et al (Diabetologia 2009;52:1766- 77) noted a weak trend when M was a concomitant treatment among glargine users vs. all other insulin regimens (HR=0.88, 0.48-1.63), or when metformin was given as a monotherapy vs. insulin-based regimens (HR=0.93, 0.69-1.27). No effect was found when M monotherapy was compared with sulphonylureas (HR=1.02, 0.71-1.45). Bodmer et al (Diabetes Care 2010;33:1304-8) found a significant protective effect (OR=0.44, 0.24-0.82) only with a long term use of M, defined as equal to approximately 5+ years. The SRR for M and BC risk is plotted in figure. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr PD03-03.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".