ArticleThe Lancet. Respiratory medicine2026
PET-CT benchmarked detection and 5-year progression of asymptomatic tuberculosis: a longitudinal, prospective cohort study.
Article in The Lancet. Respiratory medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Airway immune signatures of protection and disease progression in recent human tuberculosis household contacts.Nature immunology · 2026Article
- Inflammatory biomarkers of asymptomatic and symptomatic tuberculosis.Nature communications · 2026Article
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38 authors.
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Abstract
backgroundTo understand how lung pathology relates to symptoms, microbiology, and progression risk in tuberculosis and to advance diagnostic development, we determined the frequency at screening of tuberculosis-consistent lesions in asymptomatic individuals within 5 years of tuberculosis diagnosis using highly sensitive imaging ([
methodsWe enrolled a prospective longitudinal cohort in Khayelitsha, Cape Town, South Africa, of asymptomatic, HIV-uninfected contacts aged 18-65 years of patients with rifampicin-resistant tuberculosis, a tuberculosis high-risk group not eligible for chemoprophylaxis. Participants underwent baseline PET-CT, chest x-ray, phlebotomy, and intensive sputum collection, and were classified into four PET-CT lung categories: consistent with tuberculosis, inactive tuberculosis, other lesions, and normal. Chest x-ray was processed by three types of CAD software (CAD4TB [version 7.0], qXR [version 3.0.0], and Lunit [version 3.1.4.111]). Follow-up included symptom-agnostic tuberculosis screening (23-38 months) and provincial register review (≤74 months), and a subgroup had repeat PET-CT (5-15 months). Tuberculosis was defined as bacteriologically confirmed or clinically diagnosed. The primary outcome measures were hazard ratio (HR) for tuberculosis diagnosis and treatment by baseline PET-CT lung abnormality category with normal as the reference group, and diagnostic performance of chest x-ray CAD software using area under the receiver operator characteristic curve (AUC).
findings250 asymptomatic adults were enrolled between March 3, 2015, and Oct 11, 2017, irrespective of tuberculosis history or previous infection, and followed up for 1107 person-years (median 4·7 years [IQR 4·0-5·1]). 18 (7%) participants were treated for tuberculosis (16 [89%] of 18 bacteriologically confirmed). Six of 18 participants were diagnosed at baseline (four requiring induced sputum culture) and 12 of 18 after a median of 32 months (IQR 12-35). By baseline PET-CT category, tuberculosis was diagnosed and treated in 12 (41%) of 29 participants with scans consistent with tuberculosis, two (7%) of 30 with scans consistent with inactive tuberculosis, two (2%) of 83 with scans showing other lesions, and two (2%) of 108 with scans showing normal lungs. Participants with baseline PET-CT scans consistent with tuberculosis had the highest risk of 5-year tuberculosis diagnosis (HR 28·54 [95% CI 6·37-127·81] compared with those with scans showing normal lungs, p<0·0001), with no significant risk for scans consistent with inactive tuberculosis (3·55 [0·50-25·21], p=0·21) or other lung lesions (1·30 [0·18-9·23], p=0·79). 11 (69%) of the 16 participants with bacteriologically confirmed tuberculosis were asymptomatic at bacteriological confirmation, and ten (91%) of 11 had baseline PET-CT scans consistent with tuberculosis. Using baseline PET-CT classification as reference, the AUC for chest x-ray CAD software ranged from 0·86 (95% CI 0·72-0·99) to 0·89 (0·75-1·00) for bacteriologically confirmed tuberculosis.
interpretationMost adult asymptomatic contacts diagnosed with tuberculosis over 5 years had baseline radiographically evident disease, not radiographically negative incipient tuberculosis. Although PET-CT is not feasible for routine screening, it provides a highly sensitive reference benchmark for diagnostic development, with chest x-ray CAD performing comparatively well.
fundingSouth Africa Medical Research Council, US National Institutes of Health, Gates Foundation, Wellcome, UK Research and Innovation Medical Research Council, and Walter and Eliza Hall Institute of Medical Research.
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