Genetic polymorphisms of<i>RAD51</i>and<i>XRCC3</i>and acute myeloid leukemia risk: a meta-analysis
Bibliographic record
Abstract
Studies on gene polymorphisms of RAD51 and X-ray repair cross-complementing group 3 (XRCC3) and acute myeloid leukemia risk (AML) are conflicting and there is no recent meta-analysis. Therefore, the purpose of this study was to evaluate the effect of RAD51 G135C and XRCC3 Thr241Met genotypes on AML susceptibility. We conducted a systematic search of three databases including PubMed and EMBASE for the period up to 20 February 2013 and identified 43 relevant studies. Six eligible studies were eventually selected for RAD51 (1764 cases and 3469 controls) and six studies for XRCC3 (1352 cases and 2582 controls). Pooled odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of AML associated with RAD51 and XRCC3 were appropriately calculated based on fixed- or random-effects models. The quality of studies was evaluated using the Newcastle-Ottawa Scale (NOS). Subgroup analyses were performed among Asian, Caucasian and other populations. The pooled results showed that the leukemia risk was not significantly associated with RAD51: the same results were obtained among any subgroup analysis. No significant association was demonstrated for AML risk with XRCC3 in the total population, but elevated associations were observed in Caucasians for the homozygote and recessive comparison (Met/Met vs. Thr/Thr, OR = 1.67, 95% CI = 1.09-2.57, p = 0.019; recessive model, OR = 1.78, 95% CI = 1.19-2.65, p = 0.005). This meta-analysis provides evidence that the RAD51 and XRCC3 polymorphisms are not associated with an increased risk of AML in the total population.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.041 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".