LSP1 Gene rs3817198 Polymorphism and Breast Cancer Risk: A Systematic Review and Meta-analysis Study
Bibliographic record
Abstract
In this meta-analysis, we tried to clear the relationship between breast cancer risk and LSP1 gene rs3817198T>C polymorphism. This meta-analysis was conducted according to PRISMA protocol. We searched PubMed/Medline, Web of sciences and EMBASE. All literature investigating the association of LSP1 gene rs3817198T>C and breast cancer risk were considered to include in the meta-analysis. We pooled ORs using both fixed and random-effect models. Egger’s test and funnel plot were used to evaluate Publication bias and small study effect. After evaluation and screening of citations, 14 publications were eligible for final analysis after applying of inclusion and exclusion criteria. Overall, 30,204 cases and 35,282 controls included in this meta-analysis. There was the significant association between LSP1 gene rs3817198T>C polymorphism and breast cancer only in homozygote genetic model (OR=1.14 [1.05-1.24]) and no association was found in heterozygotes (OR=1.03 [0.98-1.07]). The association was significant for popula ion-based studies and European & American & African population in both homozygote and heterozygote genetic model. There was no evidence of bias of literature and no small study effect. In conclusion, it seems that LSP1 gene rs3817198 polymorphism play its role in breast cancer incidence and other SNPs and environment are such triggers. Nevertheless, we recommend genome-wide association studies to evaluate the effect of SNPs in combination, not as single SNPs.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.041 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".