Blood RNA biomarkers and C-reactive protein for triage of adult patients with tuberculosis lymphadenitis and pericarditis in South Africa: a single-centre, prospective, observational, diagnostic accuracy study
Notice bibliographique
Résumé
BACKGROUND: Data on the diagnostic accuracy of blood RNA biomarker signatures for extrapulmonary tuberculosis are scarce. We aimed to address this question among people investigated for tuberculosis lymphadenitis and tuberculosis pericarditis. METHODS: This prospective, observational, diagnostic accuracy study was done at a tertiary hospital in Cape Town, South Africa. We enrolled consecutive symptomatic adults (aged 18 years or older) with presumptive tuberculosis lymphadenitis (Jan 25, 2017, to Oct 9, 2019) or tuberculosis pericarditis (Nov 24, 2016, to Oct 28, 2019). We used microbiological testing of samples from the site of disease as the reference standard. We evaluated the diagnostic accuracy of seven previously reported blood RNA signatures by area under the receiver operating characteristic curve (AUROC) and sensitivity and specificity at prespecified thresholds using two SDs above the mean of a healthy reference control group, benchmarked against blood C-reactive protein and WHO target product profile for a tuberculosis triage test. Decision curve analysis was used to evaluate clinical utility of the best-performing blood RNA signature and C-reactive protein. FINDINGS: The pooled cohort included 440 individuals, 374 of whom (275 with lymphadenitis and 99 with pericarditis) had at least one microbiological test from the site of disease, blood C-reactive protein, and RNA measurements available and were included in the analysis. 181 (48%) participants were female and 193 (52%) were male. The diagnostic accuracy of blood RNA signatures was similar across patients with lymphadenitis and pericarditis. In pooled analysis of both cohorts, all RNA signatures had similar discrimination, with AUROC point estimates ranging from 0·77 (95% CI 0·72-0·82) to 0·82 (0·77-0·86), and greater than that of C-reactive protein (0·61 [0·56-0·67]). The best-performing signature (Roe3) did not meet the WHO target product profile benchmark for a triage test. At the prespecified threshold, Roe3 had 78% (95% CI 72-83) sensitivity and 69% (62-75) specificity; C-reactive protein at a threshold of 10 mg/L had 83% (77-87) sensitivity and 35% (29-43) specificity. In this setting, decision curve analysis showed that Roe3 offered greater net benefit than other approaches for services aiming to reduce the number needed to investigate with confirmatory testing to fewer than four to identify each individual with tuberculosis. INTERPRETATION: Our results suggest RNA biomarkers show better accuracy and clinical utility than C-reactive protein to trigger confirmatory tuberculosis testing in patients with tuberculosis lymphadenitis and tuberculosis pericarditis, but still fall short of the WHO target product profile for tuberculosis triage tests. 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, Wellcome Trust, National Institute for Health and Care Research, and Royal College of Physicians.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».