Association between CASP3 polymorphisms and overall cancer risk: A meta‐analysis of case‐control studies
Bibliographic record
Abstract
Several studies inspected the relationship between caspase-3 (CASP3) polymorphisms and the risk of several human cancers, but the findings remain controversial. We conducted a meta-analysis aiming to inspect the association between CASP3 rs1049216 T>C, rs12108497 C>T, rs4647603 G>A, rs4647602 C>A, rs6948 T>G, rs2705897 A>C, and rs113420705 G>A polymorphisms and cancer risk. Eligible studies were recognized by searching the Web of Science, PubMed, Scopus, and Google Scholar databases. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to quantitatively evaluate the association between each polymorphism of CASP3 and cancer risk. The rs4647603 variant significantly increased the risk of cancer in an overdominant (OR, 1.44; 95% CI, 1.03-2.01; P = 0.03; AG vs AA+GG) inheritance model. Regarding the rs4647602 variant, the findings revealed that this variant was associated with protection against cancer in homozygous codominant (OR, 0.67; 95% CI, 0.56-0.80; P < 0.00001; AA vs CC), dominant (OR, 0.84; 95% CI, 0.73-0.96; P = 0.009; AC+AA vs CC), recessive (OR, 0.70; 95% CI, 0.61-0.79; P < 0.00001; AA vs AC+CC), and allele (OR, 0.81; 95% CI, 0.75-0.88; P = 0.00001; A vs C) models. The findings suggested that the rs2705897 variant significantly decreased the risk of cancer in heterozygous codominant (OR, 0.80; 95% CI, 0.67-0.94; P = 0.009; AC vs AA), dominant (OR, 0.81; 95% CI, 0.69-0.95; P = 0.009; AC+CC vs AA), overdominant (OR, 0.80; 95% CI, 0.68-0.95; P = 0.01; AC vs CC+AA), and allele (OR, 0.85; 95% CI, 0.74-0.97; P = 0.02; C vs A) models. The results did not support an association between CASP3 rs1049216 and rs6948 polymorphisms and cancer risk. In summary, the findings of this meta-analysis support an association between CASP3 polymorphisms and cancer risk. Larger and well-designed studies are desired to evaluate these associations in detail.
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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 | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.033 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".