Blood RNA biomarkers for tuberculosis screening in people living with HIV before antiretroviral therapy initiation: a diagnostic accuracy study
Bibliographic record
Abstract
BACKGROUND: Undiagnosed tuberculosis remains a major threat for people living with HIV. Multiple blood transcriptomic biomarkers have shown promise for tuberculosis diagnosis. We sought to evaluate their diagnostic accuracy and clinical utility for systematic pre-antiretroviral therapy (ART) tuberculosis screening. METHODS: We enrolled consecutive adults (age ≥18 years) referred to start ART at a community health centre in Cape Town, South Africa, irrespective of symptoms. Sputa were obtained (using induction if required) for two liquid cultures. Whole-blood RNA samples underwent transcriptional profiling using a custom Nanostring gene panel. We measured the diagnostic accuracy of seven candidate RNA signatures (one single gene biomarker [BATF2] and six multigene biomarkers) for the reference standard of Mycobacterium tuberculosis culture status, using area under the receiver-operating characteristic curve (AUROC) analysis, and sensitivity and specificity at prespecified thresholds (two standard scores above the mean of healthy controls; Z2). Clinical utility was assessed by calculating net benefit in decision curve analysis. We compared performance with C-reactive protein (CRP; threshold ≥5 mg/L), WHO four-symptom screen (W4SS), and the WHO target product profile for tuberculosis triage tests. FINDINGS: (IQR 184-486). Of 676 participants with available sputum culture results, 89 (13%) had culture-confirmed tuberculosis. The seven RNA signatures were moderately to highly correlated (Spearman rank coefficients 0·42-0·93) and discriminated tuberculosis culture positivity with similar AUROCs (0·73-0·80), but none statistically better than CRP (AUROC 0·78, 95% CI 0·72-0·83). Diagnostic accuracy was similar across CD4 count strata, but lower among participants with negative W4SS (AUROCs 0·56-0·65) compared with positive (AUROCs 0·75-0·84). The RNA biomarker with the highest AUROC point estimate was a four-gene signature (Suliman4; AUROC 0·80, 95% CI 0·75-0·86), with sensitivity 83% (95% CI 74-90) and specificity 59% (55-63) at the Z2 threshold. In decision curve analysis, Suliman4 and CRP had similar clinical utility to guide confirmatory tuberculosis testing, but both had higher net benefit than W4SS. In exploratory analyses, an approach combining CRP (≥5 mg/L) and Suliman4 (≥Z2) had sensitivity of 80% (70-87), specificity of 70% (66-74), and higher net benefit than either biomarker alone. INTERPRETATION: RNA biomarkers showed better clinical utility to guide confirmatory tuberculosis testing for people living with HIV before ART initiation than symptom-based screening, but their performance did not exceed that of CRP and fell short of WHO recommended targets. Interferon-independent approaches might be required to improve accuracy of host-response biomarkers to support tuberculosis screening before ART initiation. FUNDING: South African Medical Research Council, European and Developing Countries Clinical Trials Partnership 2, National Institutes of Health National Institute of Allergy and Infectious Diseases, The Wellcome Trust, National Institute for Health and Care Research, Royal College of Physicians London.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".