Assessing the Diagnostic Performance of New Commercial Interferon-γ Release Assays for<i>Mycobacterium tuberculosis</i>Infection: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: We compared 6 new interferon-γ release assays (IGRAs; hereafter index tests: QFT-Plus, QFT-Plus CLIA, QIAreach, Wantai TB-IGRA, Standard E TB-Feron, and T-SPOT.TB/T-Cell Select) with World Health Organization (WHO)-endorsed tests for tuberculosis infection (hereafter reference tests). METHODS: Data sources (1 January 2007-18 August 2021) were Medline, Embase, Web of Science, Cochrane Database of Systematic Reviews, and manufacturers' data. Cross-sectional and cohort studies comparing the diagnostic performance of index and reference tests were selected. The primary outcomes of interest were the pooled differences in sensitivity and specificity between index and reference tests. The certainty of evidence (CoE) was summarized using the GRADE approach. RESULTS: Eighty-seven studies were included (44 evaluated the QFT-Plus, 4 QFT-Plus CLIA, 3 QIAreach, 26 TB-IGRA, 10 TB-Feron [1 assessing the QFT-Plus], and 1 T-SPOT.TB/T-Cell Select). Compared to the QFT-GIT, QFT Plus's sensitivity was 0.1 percentage points lower (95% confidence interval [CI], -2.8 to 2.6; CoE: moderate), and its specificity 0.9 percentage points lower (95% CI, -1.0 to -.9; CoE: moderate). Compared to QFT-GIT, TB-IGRA's sensitivity was 3.0 percentage points higher (95% CI, -.2 to 6.2; CoE: very low), and its specificity 2.6 percentage points lower (95% CI, -4.2 to -1.0; CoE: low). Agreement between the QFT-Plus CLIA and QIAreach with QFT-Plus was excellent (pooled κ statistics of 0.86 [95% CI, .78 to .94; CoE: low]; and 0.96 [95% CI, .92 to 1.00; CoE: low], respectively). The pooled κ statistic comparing the TB-Feron and the QFT-Plus or QFT-GIT was 0.85 (95% CI, .79 to .92; CoE: low). CONCLUSIONS: The QFT-Plus and the TB-IGRA have very similar sensitivity and specificity as WHO-approved IGRAs.
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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 | 0.004 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.009 |
| 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 | 0.001 |
| 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".