Performance of Purified Antigens for Serodiagnosis of Pulmonary Tuberculosis: a Meta-Analysis
Bibliographic record
Abstract
Serological antibody detection tests for tuberculosis may offer the potential to improve diagnosis. Recent meta-analyses have shown that commercially available tests have variable accuracies and a limited clinical role. We reviewed the immunodiagnostic potential of antigens evaluated in research laboratories (in-house) for the serodiagnosis of pulmonary tuberculosis and conducted a meta-analysis to evaluate the performance of comparable antigens. Selection criteria included the participation of at least 25 pulmonary tuberculosis patients and the use of purified antigens. Studies evaluating 38 kDa, MPT51, malate synthase, culture filtrate protein 10, TbF6, antigen 85B, alpha-crystallin, 2,3-diacyltrehalose, 2,3,6-triacyltrehalose, 2,3,6,6'-tetraacyltrehalose 2'-sulfate, cord factor, and TbF6 plus DPEP (multiple antigen) were included in the meta-analysis. The results demonstrated that (i) in sputum smear-positive patients, sensitivities significantly >or=50% were provided for recombinant malate synthase (73%; 95% confidence interval [CI], 58 to 85) and TbF6 plus DPEP (75%; 95% CI, 50 to 91); (ii) protein antigens achieved high specificities; (iii) among the lipid antigens, cord factor had the best overall performance (sensitivity, 69% [95% CI, 28 to 94]; specificity, 91% [95% CI, 78 to 97]); (iv) compared with the sensitivities achieved with single antigens (median sensitivity, 53%; range, 2% to 100%), multiple antigens yielded higher sensitivities (median sensitivity, 76%; range, 16% to 96%); (v) in human immunodeficiency virus (HIV)-infected patients who are sputum smear positive, antibodies to several single and multiple antigens were detected; and (vi) data on seroreactivity to antigens in sputum smear-negative or pediatric patients were insufficient. Potential candidate antigens for an antibody detection test for pulmonary tuberculosis in HIV-infected and -uninfected patients have been identified, although no antigen achieves sufficient sensitivity to replace sputum smear microscopy. Combinations of select antigens provide higher sensitivities than single antigens. The use of a case-control design with healthy controls for the majority of studies was a limitation of the review. Efforts are needed to improve the methodological quality of tuberculosis diagnostic studies.
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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 | 0.024 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.047 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".