Relationship of <I>HLA-DRB1</I> gene polymorphism with susceptibility to pulmonary tuberculosis: updated meta-analysis
Bibliographic record
Abstract
BACKGROUND: Studies indicate that human leukocyte antigen (HLA) gene polymorphisms are implicated in the risk of pulmonary tuberculosis (PTB). However, research findings are contradictory. OBJECTIVE: To examine the association between HLA-DRB1 alleles and PTB risk using a meta-analysis on case-control studies. METHODS: We searched for relevant studies in the PubMed and EMBASE databases. We used fixed-effects or random-effects models and reported combined odds ratios (ORs) and 95% confidence intervals (CI). The Newcastle-Ottawa Scale (NOS) was used to estimate the quality of each case-control study. RESULTS: A total of 21 individual case-control studies were identified, including studies of 14 family alleles and 28 specific alleles. Compared with controls, DRB1*15 and DRB1*08:03 were found to have significantly higher frequencies in PTB patients; however, DRB1*03, DRB1*11, DRB1*11:03 and DRB1*12:02 had significantly lower frequencies in the total population. The association between other HLA-DRB1 family alleles and specific alleles and predisposition to PTB was not statistically significant. Among Asian populations, DRB1*03 and DRB1*07:01 were associated with a reduced incidence of PTB, while DRB1*15 and DRB1*08:03 were associated with an increased incidence of PTB. CONCLUSION: We conclude that HLA-DRB1 may be a valuable marker to predict the risk for PTB, especially in Asian populations.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.041 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| 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".