<i>SRD5A2 V89L</i> polymorphism and prostate cancer risk: A meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Increasing studies investigating the association between steroid 5-alpha reductase type II gene polymorphism at codon 89 (SRD5A2 V89L) and susceptibility to prostate cancer (PCa) confer inconsistent results. To precisely estimate the relationship with more statistical power, a meta-analysis was performed. METHODS: A comprehensive search was conducted to identify all case-control studies investigating such an association. Odds ratio (OR) and its 95% confidence interval (CI) were used to evaluate the size effect. RESULTS: Twenty-five eligible reports were identified including 8,615 cases/9,089 controls in 33 comparisons. In overall analysis, no significant associations were found in all genetic models. Subgroup analyses by ethnicity revealed that small excess PCa risks were observed in dominant model (OR, 1.11; 95% CI, 1.03-1.19 for (LL + VL) vs. VV; P < 0.01; P(heterogeneity) = 0.49) and L allele frequency comparison (OR, 1.09; 1.03-1.15 for L allele frequency; P < 0.01; P(heterogeneity) = 0.07) in Europeans. Meanwhile, SRD5A2 V89L polymorphism was significantly associated with an increased PCa risk in men aged < or =65 under the co-dominant (OR, 1.70; 95% CI, 1.09-2.66 for LL vs. VV; P = 0.02; P(heterogeneity) = 0.31) and recessive (OR, 1.75; 95% CI, 1.14-2.68 for LL vs. (VV + VL); P = 0.01; P(heterogeneity) = 0.12) models. However, no significant associations were found in Asians and Africans. CONCLUSIONS: Our study suggests SRD5A2 V89L polymorphism could play a low-penetrant role in PCa risk among Europeans and individuals younger than 65 years. Additional well-designed studies are warranted to validate these findings.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.048 |
| Bibliometrics | 0.004 | 0.006 |
| 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".