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Biomarkers to identify Mycobacterium tuberculosis infection among borderline QuantiFERON results

BACKGROUND: Screening for tuberculosis (TB) infection often includes QuantiFERON-TB Gold Plus (QFT) testing. Previous studies showed that two-thirds of patients with negative QFT results just below the cut-off, so-called borderline test results, nevertheless had other evidence of TB infection. This...

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Detalles Bibliográficos
Autores principales: Uzorka, Jonathan W., Bakker, Jaap A., van Meijgaarden, Krista E., Leyten, Eliane M.S., Delfos, Nathalie M., Hetem, David J., Kerremans, Jos, Zwarts, Mieke, Cozijn, Sandra, Ottenhoff, Tom H.M., Joosten, Simone A., Arend, Sandra M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: European Respiratory Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363845/
https://www.ncbi.nlm.nih.gov/pubmed/35058249
http://dx.doi.org/10.1183/13993003.02665-2021
Descripción
Sumario:BACKGROUND: Screening for tuberculosis (TB) infection often includes QuantiFERON-TB Gold Plus (QFT) testing. Previous studies showed that two-thirds of patients with negative QFT results just below the cut-off, so-called borderline test results, nevertheless had other evidence of TB infection. This study aimed to identify a biomarker profile by which borderline QFT results due to TB infection can be distinguished from random test variation. METHODS: QFT supernatants of patients with a borderline (≥0.15 and <0.35 IU·mL(−1)), low-negative (<0.15 IU·mL(−1)) or positive (≥0.35 IU·mL(−1)) QFT result were collected in three hospitals. Bead-based multiplex assays were used to analyse 48 different cytokines, chemokines and growth factors. A prediction model was derived using LASSO regression and applied further to discriminate QFT-positive Mycobacterium tuberculosis-infected patients from borderline QFT patients and QFT-negative patients RESULTS: QFT samples of 195 patients were collected and analysed. Global testing revealed that the levels of 10 kDa interferon (IFN)-γ-induced protein (IP-10/CXCL10), monokine induced by IFN-γ (MIG/CXCL9) and interleukin-1 receptor antagonist in the antigen-stimulated tubes were each significantly higher in patients with a positive QFT result compared with low-negative QFT individuals (p<0.001). A prediction model based on IP-10 and MIG proved highly accurate in discriminating patients with a positive QFT (TB infection) from uninfected individuals with a low-negative QFT (sensitivity 1.00 (95% CI 0.79–1.00) and specificity 0.95 (95% CI 0.74–1.00)). This same model predicted TB infection in 68% of 87 patients with a borderline QFT result. CONCLUSIONS: This study was able to classify borderline QFT results as likely infection-related or random. These findings support additional laboratory testing for either IP-10 or MIG following a borderline QFT result for individuals at increased risk of reactivation TB.