Methylenetetrahydrofolate reductase C677T and A1298C polymorphisms and gastric cancer susceptibility
Bibliographic record
Abstract
AIM: To identify the association between methylenetetrahydrofolate reductase (MTHFR) polymorphisms and gastric cancer (GC) susceptibility. METHODS: Systematic searches were performed on the electronic databases PubMed, ISI, Web of knowledge, CNKI and Wanfang, as well as manual searching of the references of the identified articles. A total of 26 papers were included in this meta-analysis. Overall and subgroup analyses were performed. Odds ratio (OR) and 95%CI were used to evaluate the associations between MTHFR polymorphisms and GC risk. The I (2) statistics were used to evaluate between-study heterogeneity. Sensitivity analysis was also performed. RESULTS: Increased risk was found for the MTHFR C677T polymorphism under four genetic models (TT + CT vs CC: OR = 1.23, P = 0.002; T vs C: OR = 1.15, P = 0.001; TT vs CC: OR = 1.37, P = 0.0005; TT vs CT + CC: OR = 1.17, P = 0.0008). Subgroup analysis by ethnicity suggested that C677T polymorphism conferred a risk of GC in eastern but not in western populations. Stratification by tumor site showed an association between the C677T polymorphism and gastric cardia cancer and non-cardia GC in the worldwide population and in eastern populations. Regardless of comparisons with controls or diffuse-type GC, a positive association was found for the C677T polymorphism and an increased risk of intestinal-type GC in the whole population and in western populations. With regard to the A1298C polymorphism, we found that genotype CC was significantly decreased and conferred protection against GC in eastern populations (CC vs AA: OR = 0.44, P = 0.03; CC vs AC + AA: OR = 0.46, P = 0.04). CONCLUSION: MTHFR C677T polymorphism is a risk factor for GC, and the A1298C polymorphism may be a protective factor against GC in eastern populations.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".