Positive predictive value of ELISpot in BAL and pleural fluid from patients with suspected pulmonary tuberculosis

Background: The aim of this study was to evaluate the positive predictive value (PPV) of ELISpot in bronchoalveolar lavage (BAL) and pleural fluid for the diagnosis of active tuberculosis (TB) in real-life clinical practice, together with the added value of a cut-off >1.0 for the ratio between the extra-sanguineous and systemic interferon-gamma responses in positive samples. Methods: A retrospective, single-centre study was performed. Patients with positive ELISpot in BAL and pleural fluid were included. Results: The PPV for TB in patients with positive ELISpot in BAL (n = 40) was 64.9%, which increased to 82.6% for the ESAT-6 panel and 71.4% for the CFP-10 panel after the introduction of a cut-off >1.0 for the ratio between the BAL and blood interferon-gamma responses. In patients with positive ELISpot in pleural fluid (n = 16), the PPV for TB was 85.7%, which increased to 91.7% for the ESAT-6 panel and 92.3% for the CFP-10 panel after the introduction of a cut-off >1.0 for the ratio between the pleural fluid and blood interferon-gamma responses. Conclusions: This report describes the PPV of ELISpot in BAL and pleural fluid for the diagnosis of active TB in real-life clinical practice. The results indicate the possibility of an increase of the PPV using a cut-off >1.0 for the ratio between the extra-sanguineous and systemic interferon-gamma responses. Further studies are needed to underline this ratio-approach and to evaluate the full diagnostic accuracy of ELISpot in extra-sanguineous fluids like BAL and pleural fluid

Serum Biomarker Profile Including CCL1, CXCL10, VEGF, and Adenosine Deaminase Activity Distinguishes Active From Remotely Acquired Latent Tuberculosis

INTRODUCTION: There is an urgent medical need to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI) and prevent undertreatment and overtreatment. The aim of this study was to identify biomarker profiles that may support the differentiation between ATB and LTBI and to validate these signatures. MATERIALS AND METHODS: The discovery cohort included adult individuals classified in four groups: ATB (n = 20), LTBI without prophylaxis (untreated LTBI; n = 20), LTBI after completion of prophylaxis (treated LTBI; n = 20), and healthy controls (HC; n = 20). Their sera were analyzed for 40 cytokines/chemokines and activity of adenosine deaminase (ADA) isozymes. A prediction model was designed to differentiate ATB from untreated LTBI using sparse partial least squares (sPLS) and logistic regression analyses. Serum samples of two independent cohorts (national and international) were used for validation. RESULTS: sPLS regression analyses identified C-C motif chemokine ligand 1 (CCL1), C-reactive protein (CRP), C-X-C motif chemokine ligand 10 (CXCL10), and vascular endothelial growth factor (VEGF) as the most discriminating biomarkers. These markers and ADA(2) activity were significantly increased in ATB compared to untreated LTBI (p ≤ 0.007). Combining CCL1, CXCL10, VEGF, and ADA2 activity yielded a sensitivity and specificity of 95% and 90%, respectively, in differentiating ATB from untreated LTBI. These findings were confirmed in the validation cohort including remotely acquired untreated LTBI participants. CONCLUSION: The biomarker signature of CCL1, CXCL10, VEGF, and ADA2 activity provides a promising tool for differentiating patients with ATB from non-treated LTBI individuals