Association between single nucleotide polymorphisms of IL-6 and susceptibility to skin cancer: a meta-analysis and systematic review
Bibliographic record
Abstract
Background: As one of the most common body malignant cancers, skin cancers contain a group of highly heterogeneous tumors with different malignant potential, prognosis and treatment methods.Despite the progress in the treatment of skin cancers worldwide, the overall prognosis is still poor.Recent studies indicated single nucleotide polymorphisms (SNPs) of interleukin-6 (IL-6), including 174G/C and 597G/A, might be associated with susceptibility to skin cancer.This meta-analysis aims to clarify the relationship between IL-6 gene polymorphisms and skin cancers.Methods: Eligible studies were identified from searching PubMed, Embase, Web of Science and Cochrane.Pooled odds ratio (OR) and corresponding 95% confidence interval (CI) were obtained for the relationships between IL-6 174G/C and 597G/A polymorphisms and skin cancer using random-effects models.For the included studies, the Newcastle-Ottawa scale (NOS) score was calculated to assess study quality.Heterogeneity tests, sensitivity analysis, and publication bias assessments were also performed.Trim-and-fill method was used when publication bias existed aiming to adjusting OR.All data were analyzed in R (version 4.0.2).Results: This meta-analysis included 1,705 cases and 1,987 controls for 174G/C polymorphism (10 publications), and 968 cases and 998 controls for 597G/A polymorphism (3 publications).No elevated risk of skin cancer was found in all comparisons for 174G/C polymorphism: CC vs. GC + GG, OR =1.03 (95% CI: 0.81-1.31);GC + CC vs. GG, OR =1.16 (95% CI: 0.96-1.39);CC vs. GG, OR =1.14 (95% CI: 0.86-1.53);GC vs. GG, OR =1.16 (95% CI: 0.99-1.37);C vs. G, OR =1.07 (95% CI: 0.92-1.24).Then we performed subgroup analysis based on publication year, the cancer type, sample size, NOS score.Significant differences were observed in the subgroup of publication year before 2010 (GC + CC vs. GG, OR =1.255, P=0.012; GC vs. GG, OR =1.277, P=0.01), while there is no statistical significance in the subgroup of publication year after 2010 (P>0.05 for all comparisons).After publication bias adjustment, the results further suggested that 174G/C polymorphism is not associated with the risk of skin cancer.No elevated risk of skin cancer was found in the comparisons for 597G/A polymorphism.Discussion: Current evidence showed that IL-6 gene polymorphisms might not be associated with the susceptibility to skin cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| 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) | 0.004 | 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".