Folate Intake,<i>MTHFR</i>Polymorphisms, and the Risk of Colorectal Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background. The objective was to determine whether relationships exist between the methylene-tetrahydrofolate reductase (MTHFR) polymorphisms and risk of colorectal cancer (CRC) and examine whether the risk is modified by level of folate intake. Methods. MEDLINE, Embase, and SCOPUS were searched to May 2012 using the terms "folic acid," "folate," "colorectal cancer," "methylenetetrahydrofolate reductase," "MTHFR." Observational studies were included which (1) assessed the risk of CRC for each polymorphism and/or (2) had defined levels of folate intake for each polymorphism and assessed the risk of CRC. Results. From 910 references, 67 studies met our criteria; hand searching yielded 10 studies. The summary risk estimate comparing the 677CT versus CC genotype was 1.02 (95% CI 0.95-1.10) and for 677TT versus CC was 0.88 (95% CI 0.80-0.96) both with heterogeneity. The summary risk estimates for A1298C polymorphisms suggested no reduced risk. The summary risk estimate for high versus low total folate for the 677CC genotype was 0.70 (95% CI 0.56-0.89) and the 677TT genotype 0.63 (95% CI 0.41-0.97). Conclusion. These results suggest that the 677TT genotype is associated with a reduced risk of developing CRC, under conditions of high total folate intake, and this associated risk remains reduced for both MTHFR 677 CC and TT genotypes.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.023 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".