Lifan Zhang1,2,3, Shijun Wan1, Ziyue Zhou4, Yueqiu Zhang1, Xiaoqing Liu5,6,7. 1. Division of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China. 2. Clinical Epidemiology Unit, International Epidemiology Network, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, 100730, China. 3. Centre for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 4. Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China. 5. Division of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China. liuxqpumch@126.com. 6. Clinical Epidemiology Unit, International Epidemiology Network, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, 100730, China. liuxqpumch@126.com. 7. Centre for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. liuxqpumch@126.com.
Abstract
BACKGROUND: The differential diagnosis of active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging in clinical practice. We aimed to evaluate the diagnostic accuracy of the IFN-γ/TNF-α FluoroSpot assay for differentiating ATB from LTBI. METHODS: We conducted a pilot study of case-control design, using the FluoroSpot assay to simultaneously detect IFN-γ and TNF-α secretion at the single-cell level. The frequencies of antigen-specific single TNF-α-, total TNF-α-, single IFN-γ-, total IFN-γ- and dual IFN-γ/TNF-α-secreting T cells were detected. The optimal cutoffs value of frequencies for differentiating ATB from LTBI were determined according to receiver operating characteristic curve analysis. The sensitivity, specificity, predictive values (PV) and likelihood ratios (LR) of the FluoroSpot assay were calculated. RESULTS: Thirty patients diagnosed microbiologically with ATB, 36 healthcare workers with LTBI and 36 healthy controls were enrolled. After stimulated by ESAT-6 or CFP-10 peptides, the median frequencies of single TNF-α-, total TNF-α-, single IFN-γ-, total IFN-γ- and dual IFN-γ/TNF-α-secreting T cells in ATB patients were all significantly higher than those in LTBI and HC groups (P < 0.01). The frequencies of total IFN-γ-secreting T cells detected by FluoroSpot assay correlated significantly with those of T-SPOT.TB (r = 0.910 for ESAT-6, P < 0.001, r = 0.845 for CFP-10, P < 0.001). After stimulated by ESAT-6 peptides, with total TNF-α-secreting T cells frequencies at a cut off value of 21 iSFCs/250,000 PBMCs, the sensitivity, specificity, PLR, NLR, PPV, NPV of IFN-γ/TNF-α FluoroSpot assay in differentiating ATB from LTBI were 96.7% (95%CI, 82.8-99.9%), 94.3% (95%CI, 80.8-99.3%), 16.92 (95%CI, 4.40-65.08), 0.04 (95%CI, 0.01-0.24), 93.6% (95%CI,78.6-99.2%) and 97.1% (95%CI, 84.7-99.9%), respectively. With the frequencies of total TNF-α- and total IFN-γ-secreting T cells stimulated by ESAT-6 peptides combined, the specificity was increased to 97.1%, and the positive likelihood ratio to 31.5. The combination with CFP-10 might not improve the diagnostic accuracy of the ESAT-6 for differentiating ATB from LTBI. CONCLUSIONS: IFN-γ/TNF-α FluoroSpot assay might have potential to help differentiate ATB from LTBI, but the findings need to be further verified by cross-sectional or prospective cohort studies.
BACKGROUND: The differential diagnosis of active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging in clinical practice. We aimed to evaluate the diagnostic accuracy of the IFN-γ/TNF-α FluoroSpot assay for differentiating ATB from LTBI. METHODS: We conducted a pilot study of case-control design, using the FluoroSpot assay to simultaneously detect IFN-γ and TNF-α secretion at the single-cell level. The frequencies of antigen-specific single TNF-α-, total TNF-α-, single IFN-γ-, total IFN-γ- and dual IFN-γ/TNF-α-secreting T cells were detected. The optimal cutoffs value of frequencies for differentiating ATB from LTBI were determined according to receiver operating characteristic curve analysis. The sensitivity, specificity, predictive values (PV) and likelihood ratios (LR) of the FluoroSpot assay were calculated. RESULTS: Thirty patients diagnosed microbiologically with ATB, 36 healthcare workers with LTBI and 36 healthy controls were enrolled. After stimulated by ESAT-6 or CFP-10 peptides, the median frequencies of single TNF-α-, total TNF-α-, single IFN-γ-, total IFN-γ- and dual IFN-γ/TNF-α-secreting T cells in ATB patients were all significantly higher than those in LTBI and HC groups (P < 0.01). The frequencies of total IFN-γ-secreting T cells detected by FluoroSpot assay correlated significantly with those of T-SPOT.TB (r = 0.910 for ESAT-6, P < 0.001, r = 0.845 for CFP-10, P < 0.001). After stimulated by ESAT-6 peptides, with total TNF-α-secreting T cells frequencies at a cut off value of 21 iSFCs/250,000 PBMCs, the sensitivity, specificity, PLR, NLR, PPV, NPV of IFN-γ/TNF-α FluoroSpot assay in differentiating ATB from LTBI were 96.7% (95%CI, 82.8-99.9%), 94.3% (95%CI, 80.8-99.3%), 16.92 (95%CI, 4.40-65.08), 0.04 (95%CI, 0.01-0.24), 93.6% (95%CI,78.6-99.2%) and 97.1% (95%CI, 84.7-99.9%), respectively. With the frequencies of total TNF-α- and total IFN-γ-secreting T cells stimulated by ESAT-6 peptides combined, the specificity was increased to 97.1%, and the positive likelihood ratio to 31.5. The combination with CFP-10 might not improve the diagnostic accuracy of the ESAT-6 for differentiating ATB from LTBI. CONCLUSIONS: IFN-γ/TNF-α FluoroSpot assay might have potential to help differentiate ATB from LTBI, but the findings need to be further verified by cross-sectional or prospective cohort studies.
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