Association between ERα gene Pvu II polymorphism and breast cancer susceptibility
Bibliographic record
Abstract
BACKGROUND: Estrogen has played an important role in the development of breast cancer. ER-α PvuII gene polymorphism is in close association with the occurrence risk of breast cancer, but no consensus has been achieved currently. METHODS: PubMed, Embase, China National Knowledge Infrastructure (CNKI) database, Wanfang database, and VIP database were retrieved to collect the case-control studies on association between ERα gene Pvu II polymorphism and breast cancer risk published before September 1, 2017. Newcastle-Ottawa Scale (NOS) was used to assess the quality of the literatures, Stata 14.0 software was applied for meta-analysis, and the pooled odds ratio (OR) and 95% confidence interval (95% CI) were calculated. The subgroup analysis was performed to assess the confounding factors, followed by assessment of publication bias and sensitivity analysis. RESULTS: A total of 26 studies were enrolled in the analysis based on inclusion criteria, which included 15,360 patients and 26,423 controls. The results demonstrated that ERα gene Pvu II polymorphism was in significant association with the decrease of breast cancer risk in 3 genetic models (C vs T, OR = 0.962, 95% CI = 0.933-0.992, P = .012; CC vs TT, OR = 0.911, 95% CI = 0.856-0.969, P = .003; CC vs TT/CT, OR = 0.923, 95% CI = 0.874-0.975, P = .004). Subgroup analysis was conducted on the basis of ethnicity and source of controls, whose results illustrated that ERα gene Pvu II polymorphism was in significant association with the decrease of breast cancer risk in Asians rather than in Caucasians (CC vs TT, OR = 0.862, 95% CI = 0.750-0.922, P = .038; CC vs TT/CT, OR = 0.851, 95% CI = 0.755-0.959, P = .008). In population-based subgroup rather than in hospital-based subgroup, ERα gene Pvu II polymorphism was in significant association with the decrease of breast cancer risk in the allele model, homozygous model, dominant model, and recessive model (C vs T, OR = 0.943, 95% CI = 0.911-0.977, P = .001; CC vs TT, OR = 0.878, 95% CI = 0.817-0.944, P = .000; CC/CT vs TT, OR = 0.936, 95% CI = 0.881-0.994, P = .031; CC vs TT/CT, OR = 0.902, 95% CI = 0.847-0.960, P = .001). CONCLUSION: ERα gene Pvu II polymorphism exerts an important function in the progression of breast cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".