A combination of the QuantiFERON-TB Gold In-Tube assay and the detection of adenosine deaminase improves the diagnosis of tuberculous pleural effusion

Nomogram to determine predictive risk for active tuberculosis based on the QuantiFERON-TB Gold In-Tube test

Interferon-γ release assay (IGRA) is a widely used blood test for detecting TB infection. However, a positive result of IGRA cannot differentiate active tuberculosis (ATB) infection from inactive tuberculosis (IATB). In this study, we established a nomogram model for predictive risk of ATB, differentiated from IATB, based on the concentration of interferon-γ (IFN-γ) of QuantiFERON-TB Gold In-Tube Test (QFT-GIT) and clinical characteristics. Participants with a positive QFT-GIT result were recruited and divided into a training and validation cohort according to hospitalisation date. The nomogram model for the differential diagnosis of ATB from IATB was established according to gender, age, pleural effusion (PE), and the concentration of IFN-γ in the Nil, TB antigen, and mitogen tube of QFT-GIT in the training cohort by logistic regression and validated in the validation cohort, and then combined with adenosine deaminase (ADA) to evaluated the performance value in ATB cases with PE. The area under receiver operating characteristic curve (AUC) of the diagnostic nomogram model, which we called the NSMC-ATB model for ATB diagnosis was 0.819 (95% CI 0.797-0.841), with sensitivity 73.16% and specificity 75.95% in training cohort, and AUC was 0.785 (95% CI 0.744-0.827), with sensitivity 67.44% and specificity 75.14% in validation cohort. A combination of the NSMC-ATB model and ADA performed better than the NSMC-ATB model and ADA alone in predicting ATB cases with PE, as AUC was 0.903 (95% CI 0.856-0.950) with sensitivity 78.63% and specificity 87.50%. We established an effective diagnostic nomogram model, called the NSMC-ATB model to differentiate ATB from IATB. Meanwhile, the combination of the NSMC-ATB model and ADA improved the performance value of ATB with PE.

T-SPOT with CT image analysis based on deep learning for early differential diagnosis of nontuberculous mycobacteria pulmonary disease and pulmonary tuberculosis

OBJECTIVES

This study aimed to establish a diagnostic algorithm combining T-SPOT with computed tomography image analysis based on deep learning (DL) for early differential diagnosis of nontuberculous mycobacteria pulmonary disease (NTM-PD) and pulmonary tuberculosis (PTB).

METHODS

A total of 1049 cases were enrolled, including 467 NTM-PD and 582 PTB cases. A total of 320 cases (160 NTM-PD and 160 PTB) were randomized as the testing set and were analyzed using T-SPOT combined with the DL model. The testing cases were first divided into T-SPOT-positive and -negative groups, and the DL model was then used to separate the cases into four subgroups further.

RESULTS

The precision was found to be 91.7% for the subgroup of T-SPOT-negative and DL classified as NTM-PD, and 89.8% for T-SPOT-positive and DL classified as PTB, which covered 66.9% of the total cases, compared with the accuracy rate of 80.3% of T-SPOT alone. In the other two remaining groups, where the T-SPOT prediction was inconsistent with the DL model, the accuracy was 73.0% and 52.2%, separately.

CONCLUSION

Our study shows that the new diagnostic system combining T-SPOT with DL based computed tomography image analysis can greatly improve the classification precision of NTM-PD and PTB when the two methods of prediction are consistent.

Development and validation of a prediction model for tuberculous pleural effusion: a large cohort study and external validation

Background

Distinguishing tuberculous pleural effusion (TPE) from non-tuberculosis (TB) benign pleural effusion (BPE) remains to be a challenge in clinical practice. The aim of the present study was to develop and validate a novel nomogram for diagnosing TPE.

Methods

In this retrospective analysis, a total of 909 consecutive patients with TPE and non-TB BPE from Ningbo First Hospital were divided into the training set and the internal validation set at a ratio of 7:3, respectively. The clinical and laboratory features were collected and analyzed by logistic regression analysis. A diagnostic model incorporating selected variables was developed and was externally validated in a cohort of 110 patients from another hospital.

Results

Six variables including age, effusion lymphocyte, effusion adenosine deaminase (ADA), effusion lactatedehy drogenase (LDH), effusion LDH/effusion ADA, and serum white blood cell (WBC) were identified as valuable parameters used for developing a nomogram. The nomogram showed a good diagnostic performance in the training set. A novel scoring system was then established based on the nomogram to distinguish TPE from non-TB BPE. The scoring system showed good diagnostic performance in the training set [area under the curve (AUC) (95% confidence interval (CI)), 0.937 (0.917–0.957); sensitivity, 89.0%, and specificity, 89.5%], the internal validation set [AUC (95%CI), 0.934 (0.902–0.966); sensitivity, 88.7%, and specificity, 90.3%], and the external validation set [(AUC (95%CI), 0.941 (0.891–0.991); sensitivity, 93.6%, and specificity, 87.5%)], respectively.

Conclusions

The study developed and validated a novel scoring system based on a nomogram originated from six clinical parameters. The novel scoring system showed a good diagnostic performance in distinguishing TPE from non-TB BPE and can be conveniently used in clinical settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02051-4.

A retrospective study on the combined biomarkers and ratios in serum and pleural fluid to distinguish the multiple types of pleural effusion

Purpose

Pleural effusion (PE) is a common clinical manifestation, and millions of people suffer from pleural disease. Herein, this retrospective study was performed to evaluate the biomarkers and ratios in serum and pleural fluid (PF) for the differential diagnosis of the multiple types of PE and search for a new diagnostic strategy for PE.

Methods

In-patients, who developed tuberculous PE (TPE), malignant PE (MPE), complicated parapneumonic effusion (CPPE), uncomplicated PPE (UPPE), or PE caused by connective tissue diseases (CTDs) and underwent thoracentesis at Peking University People’s Hospital from November 2016 to April 2019, were included in this study. Eleven biomarkers and their ratios in serum and PF were investigated and compared between pairs of the different PE groups, and a decision-tree was developed.

Results

Totally 112 PE cases, including 25 MPE, 33 TPE, 19 CPPE, 27 UPPE, and 8 PE caused by CTDs, were reviewed. Biomarkers and ratios showed good diagnostic performance with high area under the curve values, sensitivities, and specificities for the differential diagnosis of the multiple types of PE. According to the decision-tree analysis, the combination of adenosine deaminase (ADA), serum albumin, serum lactate dehydrogenase, total protein, PF-LDH/ADA, and PF-LDH/TP provided the best predictive capacity with an overall accuracy of 84.8%; the sensitivity and specificity for TPE diagnosis were 100% and 98.7%, respectively.

Conclusion

The biomarkers and ratios showed good diagnostic performance, and a decision-tree with an overall accuracy of 84.8% was developed to differentiate the five types of PE in clinical settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01459-w.

IgA and IgG antibody detection of mycobacterial antigens in pleural fluid and serum from pleural tuberculous patients

Background

A previous study demonstrated pleural fluid (PF) IgA immunodominance for the fused MT10.3:MPT64 protein in pleural tuberculosis (PLTB) cases. However, no clue on the role of IgA and IgG against this and other antigens in PF and serum concerning improved diagnosis is available. Thus, the aim of the present study was to validate PF IgA-MT10.3:MPT64 and evaluate PF and serum IgA and IgG reactivity against this protein, its peptides (F2) and single MPT64, MT10.3 and the PPE59 mycobacterial specific antigens. IgA and IgG ELISA were measured against the antigen in PLTB (n = 29) and other non-TB pleurisy (n = 39) patient samples.

Results

The immunodominance of PF IgA-MT10.3:MPT64 was confirmed in PLTB (86.2%) followed by PPE59 (62%), while serum IgA-F2 exhibited 51.7% sensitivity. PF and serum IgG-MT10.3:MPT64 led to 65.5 and 51.7% sensitivity, respectively. However, MT10.3 and MPT64 displayed overall lower sensitivity (≤34.5) for both antibodies. All results at 95% fixed specificity. Combinatory results indicated 93.1% sensitivity for PF IgA-MT10.3:MPT64/−PPE59 and IgA/IgG-MT10.3:MPT64 at 92.3% specificity, followed by IgA-MT10.3:MPT64/−MPT64 or /−F2 (89.6%) without jeopardizing specificity (94.9%). The combinatory results of the PF adenosine deaminase test (ADA) and IgA-MT10.3:MPT64/−F2 demonstrated the highest sensitivity (96.6%), with a specificity of 92.3%.

Conclusions

The PF IgA-MT10:MPT64 immune dominance was validated in PLTB, and its combinatory results with PPE59 or MPT64 or F2 antigens as well as with IgG, are reported herein for the first time, improving their potential to assist diagnosis. Combining PF-ADA and IgA-MT10.3:MPT64/−F2 results achieved better accuracy. Moreover, serum IgG, although less accurate, displays potential beyond microbiological tests.

Diagnostic value of polymerase chain reaction/acid-fast bacilli in conjunction with computed tomography-guided pleural biopsy in tuberculous pleurisy: A diagnostic accuracy study

Patients with tuberculous pleurisy often remain undiagnosed even after blind thoracentesis and closed pleural biopsy (PB). In this study, we assessed the value of computed tomography (CT)-guided core needle biopsy of pleural lesion and evaluated the diagnostic accuracy of polymerase chain reaction (PCR)/staining for acid-fast bacilli (AFB) in suspicious tuberculous pleurisy undiagnosed in blind thoracentesis.Patients with exudative pleural effusion (PE) without specific etiology after blind thoracentesis and closed PB were enrolled in this study. PB specimens were obtained through CT-guided core needle biopsy of pleural lesion, then underwent PCR, AFB, histopathological examination, and some routine tests. Diagnostic values were evaluated through sensitivity, specificity, negative predictive value, positive predictive value, and accuracy.A total of 261 participants (TB group: 241, non-TB group: 20) were recruited. In this cohort, the sensitivity, specificity, and accuracy were 56.0%, 95.0%, and 59.0%, respectively for PCR, whereas 57.3%, 95.0%, and 60.2%, respectively for AFB. Their parallel test achieved an improved sensitivity (76.8%) and accuracy (77.8%), with a slight decrease in specificity (90.0%). In histopathological examination, granuloma was the most common finding in TB group (88.4%, 213/241), but also observed in non-TB group (10.0%, 2/20). In addition, pleural lymphocyte percentage in TB group was significantly higher than that of non-TB group (92% vs 61%, respectively; P = .003). However, no significant differences were found for other biomarkers.CT-guided core needle PB is essential for patients with exudative PE but undiagnosed after blind thoracentesis. Combining with PCR and AFB, it strongly improves the diagnosis of tuberculous pleurisy.

Diagnostic accuracy of interleukin-22 and adenosine deaminase for tuberculous pleural effusions

OBJECTIVE

Reliable markers for accurately diagnosing tuberculous pleural effusions (TPE) are needed. This study sought to investigate the diagnostic potential of pleural interleukin-22 (IL-22) and compare it with the performance of adenosine deaminase (ADA).

METHOD

This prospective study involved 49 patients with TPE and 60 patients with pleural effusion of other causes. Pleural levels of IL-22 and ADA were determined, respectively, using ELISA or an enzymatic method. A receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated to summarize the diagnostic accuracy of single markers or marker combinations.

RESULTS

Levels of IL-22 in pleural effusion were significantly higher in TPE patients than in other patients (322.36 ± 406.65 vs. 83.13 ± 22.15 pg/ml, P < 0.05). With a cut-off value of 97.82 pg/ml, the diagnostic sensitivity of IL-22 for TPE was 71.42%, specificity was 81.67%, and the area under the curve (AUC) was 0.83. ADA levels were also increased in TPE, and its AUC for diagnosing TPE was 0.90. The combination of IL-22 and ADA enhanced diagnostic accuracy, offering sensitivity of 83.67%, specificity of 91.67%, and an AUC of 0.93.

CONCLUSION

IL-22 may be useful for diagnosing TPE, and combining it with ADA may further enhance diagnostic accuracy. Our results justify more rigorous studies with larger samples to confirm the diagnostic potential of IL-22 for TPE.

Application of Venn's diagram in the diagnosis of pleural tuberculosis using IFN-γ, IP-10 and adenosine deaminase

BACKGROUND

Pleural tuberculosis (PlTB) is the most common extrapulmonary manifestation of this infectious disease which still presents high mortality rates worldwide. Conventional diagnostic tests for PlTB register multiple limitations, including the lack of sensitivity of microbiological methods on pleural specimens and the need of invasive procedures such as pleural biopsy performance. In this scenario, the search for biological markers on pleural fluid (PF) has been the target of several studies as a strategy to overcome the limitations of PlTB diagnosis. This study aims to evaluate the use either isolated or in combination with adenosine deaminase (ADA), interferon-gamma (IFN-γ), interferon-gamma inducible protein of 10-kD (IP-10) levels on PF in order to guide an accurate anti-TB treatment in microbiologically non-confirmed cases.

METHODS AND FINDINGS

Eighty patients presenting pleural effusion under investigation were enrolled in a cross-sectional study conducted at Pedro Ernesto University Hospital, Rio de Janeiro, RJ, Brazil. Peripheral blood (PB) and PF samples collected from all patients were applied to the commercial IFN-γ release assay, QuantiFERON-TB Gold In-Tube, and samples were analyzed for IFN-γ and IP-10 by immunoassays. ADA activity was determined on PF by the colorimetric method. Based on microbiological and histological criteria, patients were categorized as follow: confirmed PlTB (n = 16), non-confirmed PlTB (n = 17) and non-PlTB (n = 47). The Mycobacterium tuberculosis antigen-specific production of IFN-γ and IP-10 on PB or PF did not show significant differences. However, the basal levels of these biomarkers, as well as the ADA activity on PF, were significantly increased in confirmed PlTB in comparison to non-PlTB group. Receiver operating characteristics curves were performed and the best cut-off points of these three biomarkers were estimated. Their either isolated or combined performances (sensitivity [Se], specificity [Sp], positive predictive value [PPV], negative predictive value [NPV] and accuracy [Acc]) were determined and applied to Venn's diagrams among the groups. Based on the confirmed PlTB cases, IFN-γ showed the best performance of them at a cut-off point of 2.33 IU/mL (Se = 93.8% and Sp = 97.9%) followed by ADA at a cut-off of 25.80 IU/L (Se = 100% and Sp = 84.8%) and IP-10 (Cut-point = 4,361.90 pg/mL, Se = 75% and Sp = 82.6%). IFN-γ plus ADA (cut-point: 25.80 IU/L) represent the most accurate biomarker combination (98.4%), showing Se = 93.7%, Sp = 100%, PPV = 100% and NPV = 97.9%. When this analysis was applied in non-confirmed PlTB, 15/17 (88.2%) presented at least two positive biomarkers in combination.

CONCLUSION

IFN-γ, IP-10, and ADA in PlTB effusions are significantly higher than in non-PlTB cases. IFN-γ is an excellent rule-in and rule-out test compared to IP-10 and ADA. The combination of IFN-γ and ADA, in a reviewed cut-off point, showed to be particularly useful to clinicians as their positive results combined prompts immediate treatment for TB while both negative results suggest further investigation.

Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB

BACKGROUND

The early and accurate diagnosis of tuberculosis (TB) is critical for controlling the global TB epidemic. Although early studies have supported the potential role of cytokine biomarkers in blood for the diagnosis of TB, this method requires further investigation and validation in different populations. A set of biomarkers that can discriminate between active TB (ATB) and latent TB infection (LTBI) remains elusive.

METHODS

In the current study, we organized two retrospective cohorts and one prospective cohort to investigate the immune responses at different clinical stages of TB infection, as determined by candidate cytokine biomarkers detected with a multiplex cytokine platform. Using a pre-established diagnostic algorithm, participants were classified as ATB, LTBI, and TB uninfected controls (CON). Based on our multiplex cytokine assay, a multi-cytokine biosignature was modelled for the optimal recognition of the different TB infection status.

RESULTS

Our analysis identified a six-cytokine biosignature of TB-antigen stimulated IFN-γ, IP-10, and IL-1Ra, and unstimulated IP-10, VEGF, and IL-12 (p70) for a biomarker screening group (n = 88). The diagnostic performance of the biosignature was then validated using a biomarker validation cohort (n = 216) and resulted in a sensitivity of 88.2% and a specificity of 92.1%. In a prospectively recruited clinical validation cohort (n = 194), the six-cytokine biosignature was further evaluated, and displayed a sensitivity of 85.7%, a specificity of 91.3% and an overall accuracy of 88.7%.

CONCLUSIONS

We have identified a six-cytokine biosignature for accurately differentiating ATB patients from subjects with LTBI and CON. This approach holds promise as an early and rapid diagnostic test for ATB.

Comparison of laboratory testing methods for the diagnosis of tuberculous pleurisy in China

To evaluate the diagnostic utilities of different methods for Mycobacterium tuberculosis (M. tuberculosis) detection in pleural fluid that represent potentially cost-effective measures for resource-limited settings in China. We compared diagnostic characteristics of the AmpSure simultaneous amplification and testing method, the BACTEC MGIT 960 system, and acid-fast bacilli staining of specimen smears for detection of M. tuberculosis in pleural fluids of 438 patients with suspected tuberculous pleurisy. Chest radiographs, computed tomography scans and the results of sputum and pleural biopsy testing were used for confirmations of tuberculosis diagnoses. The sensitivity of the AmpSure test (21.2%) was significantly higher than that of smear analysis (3.1%; p < 0.001), but was similar to that of the BACTEC culture method (17.8%; p > 0.05). The specificity of the AmpSure, BACTEC, and smear tests were 100%, 96.4%, and 100%, respectively. The positive and negative predictive values of the AmpSure, BACTEC, and smear tests were 100%/23.1%; 78.6%/19.8%; and 100%/22.4%, respectively. The sensitivity of ADA, IFNγ and histopathological analyses of pleural biopsies were all 100%. The sensitivities of all three methods were suboptimal for the detection of M. tuberculosis in pleural fluid. Future studies of a composite diagnostic index consisting of a combination of these tests are warranted.