<em>GSTM1 </em>polymorphism is related to risks of nasopharyngeal cancer and laryngeal cancer: a meta-analysis
Bibliographic record
Abstract
Background: Accumulating data have reported that GSTM1 polymorphism may be related to nasopharyngeal cancer (NPC) and laryngeal cancer (LC). This meta-analysis was performed to investigate the relationship between GSTM1 polymorphism and risks of NPC and LC. Methods: Pubmed, Embase, and China National Knowledge Infrastructure (CNKI) databases were searched for potential articles. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the relationship of GSTM1 polymorphism with the risks of NPC and LC. I 2 >50% or P <0.05 indicates significant heterogeneity. When heterogeneity existed, the random-effects model was used to pool data, otherwise, the fixed-effects model was adopted. Publication bias was detected by Begg’s funnel plot and Egger’s regression. Quality of each study was evaluated by Newcastle-Ottawa Scale. Results: Thirty-two eligible articles were included. Pooled outcome suggested the significant relationship of GSTM1 null genotype with increased risk of LC (OR =1.28, 95% CI =1.05–1.54). Compared with hospital-based (HB) population, GSTM1 null genotype was also related to increased risk of LC (OR =1.38, 95% CI =1.06–1.80). Positive relationship of GSTM1 null genotype with enhanced risk of NPC was observed (OR =1.43, 95% CI =1.26–1.63). A similar trend was also observed in the subgroup analysis by source of control (population-based [PB]: OR =1.39, 95% CI =1.18–1.63; HB: OR =1.52, 95% CI =1.22–1.89). Conclusion: GSTM1 null genotype is related to increased risk of NPC and LC. Keywords: GSTM1 , polymorphism, NPC, LC
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.044 |
| 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) | 0.003 | 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".