Quantitative Assessment of the Effects of<i>IL-1ß</i>-511 C&gt;T Variant on Breast Cancer Risk: An Updated Meta-Analysis of 3331 Cases and 3609 Controls
Bibliographic record
Abstract
OBJECTIVE: Growing evidence suggests that IL-1β -511C>T, as a functional variant, affects the risk of developing breast cancer (BC); however, the results have not been conclusive. This meta-analysis was conducted to estimate the link between this variant and BC risk. METHODS: We retrieved available publications on IL-1β -511C>T polymorphism by conducting a comprehensive literature search on the Web of Science, MEDLINE, PubMed, Scopus, and Google scholar databases (last search on February 25, 2020). RESULTS: The overall analysis indicates that IL-1β -511C>T polymorphism conferred an increased risk of BC under a recessive TT vs CT+CC model by 1.14-fold and showed protection against BC under an overdominant CT vs TT+CC genetic contrast model (odds ratio = 0.84). Stratified analysis based on ethnicity revealed the protective effect of this single-nucleotide polymorphism against BC risk in Caucasian patients. CONCLUSION: Our data results provide a proof of concept for the association of IL-1β -511C>T with BC risk. Larger, well-designed population-based studies are needed to confirm these findings.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.021 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".