Association of CTLA-4 gene polymorphisms and alopecia areata: a systematic review and meta-analysis
Bibliographic record
Abstract
To provide evidence of the association between CLTA-4 gene polymorphisms and alopecia areata (AA). PubMed, EMBASE, Web of Science, Cochrane, Wanfang, and CNKI databases were searched until 30 April 2021. The selection was completed according to the inclusion and exclusion criteria. The study quality assessment was based on Newcastle-Ottawa Scale. The assessment of the association was measured by ORs and 95%CIs. Nine studies, containing 2858 AA cases and 5444 disease-free control subjects were included. For rs231775 polymorphism, no significant association with AA was found, which was A vs. a, OR = 1.02 [0.81, 1.30], p = 0.85; AA vs. aa, OR = 1.26 [0.81, 1.97], p = 0.31; Aa vs. aa, OR = 1.04 [0.54, 2.01], p = 0.91; AA + Aa vs. aa, OR = 1.04 [0.71, 1.53], p = 0.82; AA vs. Aa + aa, OR = 1.31 [0.97, 1.78], p = 0.08. For rs3087243 polymorphism, also no significant association was found, which was A vs. a, OR = 0.93 [0.78, 1.11]; p = 0.40, AA vs. aa, OR = 0.68 [0.44, 1.06]; p = 0.09; Aa vs. aa, OR = 0.87 [0.45, 1.68], p = 0.68; AA + Aa vs. aa, OR = 0.93 [0.68, 1.28], p = 0.66; AA vs. Aa + aa, OR = 0.78 [0.34, 1.81], p = 0.57. For rs231726 polymorphism, a significant correlation was found, which was A vs. a, OR = 0.76 [0.70, 0.82], p < 0.05. A significant correlation between CTLA-4 rs231726 polymorphism and AA susceptibility was found, but no significant association of CTLA-4 gene rs231775 and rs3087243 polymorphisms and AA susceptibility was found.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.027 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".