ASSOCIATION BETWEEN APE1 ASP148GLU AND COLORECTAL CANCER RISK: A META-ANALYSIS
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer (CRC) is recognized as one of the most common cancer globally. The association between CRC and apurinic endonuclease 1 (APE1) Asp148Glu polymorphism remains unclear; thus, this meta-analysis aimed to explore whether APE1 Asp148Glu polymorphism is related to CRC risk. METHODS: Embase, PubMed, Cochrane library, CNKI and Wanfang databases were subject to a systematic search until April, 17, 2020 to evaluate the effect of APE1 Asp148Glu polymorphism on CRC risk. The associated strength was used to evaluate with odds ratios (ORs) with 95% confidence intervals (CIs) between Asp148Glu polymorphism and CRC risk. Subgroup analyses were also performed. RESULTS: In total, 11 articles including 8,136 subjects (3,836 cases and 4,300 controls) were included. Five genetic models were analyzed, including the additive model (G vs. T), the heterozygote comparison (TG vs. TT), the homozygote comparison (GG vs. TT), the dominant model (TG+GG vs. TT), and the recessive model (GG vs. TG+TT). In these models, T refers to thymine and G refers to guanine. The APE1 Asp148Glu polymorphism in heterozygote comparison [OR (95%CI) = 1.36 (1.05, 1.75), P=0.019] and dominant model [OR (95%CI) =1.31 (1.07, 1.61), P=0.010] significantly increased CRC risk. No significant association was seen for the additive model [OR (95%CI) = 1.14 (1.00, 1.31), P=0.057], recessive model [OR (95%CI) = 0.97 (0.71, 1.31), P=0.826] or in homozygote comparison [OR (95%CI) = 1.15 (0.88, 1.52), P=0.309]. Moreover, CRC risk indicated a remarkable association with APE1 Asp148Glu polymorphism in the PCR-RFLP additive model, homozygote comparison and recessive model (PG) may be a potential risk factor for CRC.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.046 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".