Association Between <i>TNF-α</i> -308G/A Polymorphism and Risk of Immune Thrombocytopenia: A Meta-Analysis
Bibliographic record
Abstract
Objective: Previous studies have investigated the association between tumor necrosis factor-alpha (TNF-α) -308G/A polymorphism and risk of immune thrombocytopenia (ITP), but the reported results have been inconsistent. Thus, a systematic meta-analysis was performed to resolve this discrepancy. Methods: Electronic databases and the cited references of the obtained published articles were manually searched. Quality assessment of each study was conducted using the Newcastle–Ottawa Scale (NOS). All case–control studies were used to assess the strength of the association. Statistical analysis was performed using Stata version 12.0. Results: Eight high-quality studies, including 947 patients and 1911 controls, were selected for the final meta-analysis. There was no significant association between TNF-α -308G/A polymorphism and ITP in overall and Asian populations. However, a significant positive association was observed between them in the dominant genetic model (AA+AG versus GG) in the Caucasian population (OR = 1.35, 95% confidence interval [CI]: 1.07–1.71, PH = 0.173). Conclusions: Our finding suggested that TNF-α -308G/A might be involved in development of ITP in the Caucasian population, but not in the Asian population. Among Caucasians the A allele (AA+AG) was associated with ITP. However, larger-scale studies are required to confirm our findings.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".