Association between breast cancer susceptibility gene associated RING domain-1 single-nucleotide polymorphisms and neuroblastoma: a Meta-analysis
Bibliographic record
Abstract
Objective To assess and synthesize the current evidence on association of rs6435862 and rs3768716 single-nucleotide polymorphisms (SNPs) of breast cancer susceptibility gene associated RING domain-1 (BARD1) gene and neuroblastoma (NB) susceptibility. Methods Five electronic databases including PubMed, Embase, Web of Science, CNKI and Wanfang were searched for potentially relevant studies on the association of BARD1 SNPs and NB from precious to May 10, 2018. Main information of included studies was extracted after literature selection. Newcastle-Ottawa Scale (NOS) was employed for quality assessment. RevMan5.3 software was used to analyze the association of rs6435862 and rs3768716 SNPs and NB susceptibility under allelic model, homozygous model, heterozygous model, dominant model, as well as recessive model. Results Five case-control studies with 9 independent cohorts comprising 3597 NB patients and 10827 healthy controls were yielded for Meta-analysis. For NOS, each included study obtained no less than 6 stars and was labeled of high quality. The findings indicated that rs6435862 and rs3768716 polymorphisms had significant association with NB susceptibility under five genetic models (P<0.05). Conclusion Rs6435862 and rs3768716 SNPs of BARD1 gene are significantly associated with NB; G-allele and GG-genotype carriers appear to have an increased risk of NB susceptibility. Key words: Breast cancer susceptibility gene associated RING domain-1 gene; Single-nucleotide polymorphism; Neuroblastoma; Meta-analysis
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.037 |
| Bibliometrics | 0.006 | 0.008 |
| 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) | 0.004 | 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".