Commercial Serological Antibody Detection Tests for the Diagnosis of Pulmonary Tuberculosis: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The global tuberculosis epidemic results in nearly 2 million deaths and 9 million new cases of the disease a year. The vast majority of tuberculosis patients live in developing countries, where the diagnosis of tuberculosis relies on the identification of acid-fast bacilli on unprocessed sputum smears using conventional light microscopy. Microscopy has high specificity in tuberculosis-endemic countries, but modest sensitivity which varies among laboratories (range 20% to 80%). Moreover, the sensitivity is poor for paucibacillary disease (e.g., pediatric and HIV-associated tuberculosis). Thus, the development of rapid and accurate new diagnostic tools is imperative. Immune-based tests are potentially suitable for use in low-income countries as some test formats can be performed at the point of care without laboratory equipment. Currently, dozens of distinct commercial antibody detection tests are sold in developing countries. The question is "do they work?" METHODS AND FINDINGS: We conducted a systematic review to assess the accuracy of commercial antibody detection tests for the diagnosis of pulmonary tuberculosis. Studies from all countries using culture and/or microscopy smear for confirmation of pulmonary tuberculosis were eligible. Studies with fewer than 50 participants (25 patients and 25 control participants) were excluded. In a comprehensive search, we identified 68 studies. The results demonstrate that (1) overall, commercial tests vary widely in performance; (2) sensitivity is higher in smear-positive than smear-negative samples; (3) in studies of smear-positive patients, Anda-TB IgG by enzyme-linked immunosorbent assay shows limited sensitivity (range 63% to 85%) and inconsistent specificity (range 73% to 100%); (4) specificity is higher in healthy volunteers than in patients in whom tuberculosis disease is initially suspected and subsequently ruled out; and (5) there are insufficient data to determine the accuracy of most commercial tests in smear microscopy-negative patients, as well as their performance in children or persons with HIV infection. CONCLUSIONS: None of the commercial tests evaluated perform well enough to replace sputum smear microscopy. Thus, these tests have little or no role in the diagnosis of pulmonary tuberculosis. Lack of methodological rigor in these studies was identified as a concern. It will be important to review the basic science literature evaluating serological tests for the diagnosis of pulmonary tuberculosis to determine whether useful antigens have been described but their potential has not been fully exploited. Activities leading to the discovery of new antigens with immunodiagnostic potential need to be intensified.
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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 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".