Association of interleukin-6 gene polymorphisms with the risk of hepatocellular carcinoma
Bibliographic record
Abstract
BACKGROUND: This study was aimed to evaluate the association between interleukin-6 (IL-6) gene polymorphisms and the risk of hepatocellular carcinoma (HCC) in a meta-analysis. METHODS: A literature search was performed for case-control studies published during May, 1993 to May, 2020 focusing on IL-6 gene polymorphisms (-174G > C, -572G > C, and -597G > A) and HCC susceptibility by using PubMed, Cochrane Database, EMBASE, Web of science, and China National Knowledge Infrastructure. From 128 full-text articles, 11 were included in this meta-analysis. I index was used to assess heterogeneity and Newcastle-Ottawa Scale was utilized for quality assessment. RESULTS: For IL-6 -174G > C polymorphism, in codominant (GG vs CC: odds ratios [OR] = 2.78, 95% confidence intervals [CI] = 1.25-6.19, P = .01, I = 16%) and recessive (GG+GC vs CC: OR = 2.76, 95% CI = 1.29-5.90, P = .009, I = 3%) models, IL-6 -174G>C polymorphism was significantly associated with the risk of HCC. In dominant (GG vs CC+GC: OR = 1.80, 95% CI = 0.92-3.54, P = .09, I = 86%) and allele (G vs C: OR = 1.49, 95% CI = 0.95-2.32, P = .08, I = 68%) models, IL-6 -174G>C polymorphism had no impact on the risk of HCC. However, in non-Italian Caucasian population, IL-6 -174G>C polymorphism was significantly related to the occurrence of HCC in both dominant (GG vs CC+GC: OR = 3.26, 95% CI = 2.29-4.65, P < .00001, I = 0%) and allele (G vs C: OR = 2.48, 95% CI = 1.48-4.15, P = .0006) models. Such correlations also could be observed when healthy individuals were selected as controls. For IL-6 -572G>C and -597G>A polymorphisms, no significant association was observed in all models, regardless of the source of control and population subgroups. No publication bias could be calculated when Begg and Egger tests were employed. CONCLUSION: This meta-analysis indicated that IL-6 -174G>C polymorphism was significantly related with the risk for HCC, especially in non-Italian Caucasian population. No significant association was observed for the correlation between IL-6 -572G>C and -597G>A polymorphisms and HCC susceptibility.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".