S1390 Is Metformin Associated With Decreased Mortality of Gastric Cancer? A Meta-Analysis
Bibliographic record
Abstract
Introduction: Gastric cancer remains one of the most common cancers worldwide. Metformin, whose antineoplastic effect on several types of malignancy, including gastric cancer, was shown to inhibit the proliferation of cancer cells in vitro and in vivo, and induce apoptosis. However, the results of clinical studies were inconsistent regarding its effect on gastric cancer mortality. Methods: A comprehensive literature search on PubMed was conducted to identify all relevant studies published prior to October 2020. The quality assessment was performed by the Newcastle-Ottawa Scale (NOS). The pooled relative risk (RR) and 95% confidence intervals (CI) were calculated to estimate the association between metformin and gastric cancer mortality. A random-effect model was used. Subgroup analysis was performed based on geographical location, and post-gastrectomy. Sensitivity analysis and publication bias detection were also performed. All statistical analyses were performed using RevMan software (version 5.3.1; Cochrane library) and STATA 15.1 statistical software (Stata Corp., College Station, TX), and all P values were two-tailed, the test level was 0.05. Results: Five articles with moderate to high quality, involving 2,092 participants, were included. Metformin was not associated with reduced gastric cancer mortality (RR 0.77, 95% CI: 0.59, 1.02, P = 0.07, I2 = 80%). No reduced gastric cancer mortality was found in Asia (RR 0.76, 95% CI: 0.55, 1.05, P = 0.10, I2 = 85%) or in Europe (RR 0.86, 95% CI: 0.56, 1.32, P = 0.49). Two studies investigating post-gastrectomy patients did not find reduced mortality among metformin users either (RR 0.71, 95%CI: 0.45, 1.11, P = 0.13, I2 = 84%). Sensitivity analysis found that after excluding the study conducted by Baglia et al, metformin was associated with decreased gastric cancer mortality. Egger's test (t = -0.21, P = 0.845), and Begg's test (z = 0.24, P = 0.806) found no publication bias of analysis. Conclusion: Metformin is not associated with decreased gastric cancer mortality. However, only five studies were included, and sensitivity analysis did not confirm robust stability. More original studies are needed.Figure 1.: Forrest plot of overall result.Table 1.: Results of quality assessment
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.057 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".