Diagnostic role of inflammatory and anti-inflammatory cytokines and effector molecules of cytotoxic T lymphocytes in tuberculous pleural effusion

The tuberculous pleural effusion

Pleural tuberculosis (TB) is a common entity with similar epidemiological characteristics to pulmonary TB. It represents a spectrum of disease that can variably self-resolve or progress to TB empyema with severe sequelae such as chronic fibrothorax or empyema necessitans. Coexistence of and progression to pulmonary TB is high. Diagnosis is challenging, as pleural TB is paucibacillary in most cases, but every effort should be made to obtain microbiological diagnosis, especially where drug resistance is suspected. Much attention has been focussed on adjunctive investigations to support diagnosis, but clinicians must be aware that apparent diagnostic accuracy is affected both by the underlying TB prevalence in the population, and by the diagnostic standard against which the specified investigation is being evaluated. Pharmacological treatment of pleural TB is similar to that of pulmonary TB, but penetration of the pleural space may be suboptimal in complicated effusions. Evidence for routine drainage is limited, but evacuation of the pleural space is indicated in complicated disease.

Educational aims

To demonstrate that pleural TB incorporates a wide spectrum of disease, ranging from self-resolving lymphocytic effusions to severe TB empyema with serious sequelae.To emphasise the high coexistence of pulmonary TB with pleural TB, and the importance of obtaining sputum for culture (induced if necessary) in all cases.To explore the significant diagnostic challenges posed by pleural TB, and consequently the frequent lack of information about drug sensitivity prior to initiating treatment.To highlight the influence of underlying TB prevalence in the population on the diagnostic accuracy of adjunctive investigations for the diagnosis of pleural TB.To discuss concerns around penetration of anti-TB medications into the pleural space and how this can influence decisions around treatment duration in practice.

Tuberculous pleural effusion prediction using ant colony optimizer with grade-based search assisted support vector machine

Introduction

Although tuberculous pleural effusion (TBPE) is simply an inflammatory response of the pleura caused by tuberculosis infection, it can lead to pleural adhesions and cause sequelae of pleural thickening, which may severely affect the mobility of the chest cavity.

Methods

In this study, we propose bGACO-SVM, a model with good diagnostic power, for the adjunctive diagnosis of TBPE. The model is based on an enhanced continuous ant colony optimization (ACOR) with grade-based search technique (GACO) and support vector machine (SVM) for wrapped feature selection. In GACO, grade-based search greatly improves the convergence performance of the algorithm and the ability to avoid getting trapped in local optimization, which improves the classification capability of bGACO-SVM.

Results

To test the performance of GACO, this work conducts comparative experiments between GACO and nine basic algorithms and nine state-of-the-art variants as well. Although the proposed GACO does not offer much advantage in terms of time complexity, the experimental results strongly demonstrate the core advantages of GACO. The accuracy of bGACO-predictive SVM was evaluated using existing datasets from the UCI and TBPE datasets.

Discussion

In the TBPE dataset trial, 147 TBPE patients were evaluated using the created bGACO-SVM model, showing that the bGACO-SVM method is an effective technique for accurately predicting TBPE.

A meta-analysis of Th1 and Th2 cytokine profiles differentiating tuberculous from malignant pleural effusion

To clarify the predominance of Th1 or Th2 immune responses in malignant and tuberculous pleural effusion (MPE and TPE, respectively), we performed a meta-analysis of previously published results of the levels of Th1/Th2 cytokines associated with these two types of pleural effusion to evaluate the use of Th1/Th2 cytokine profiles in distinguishing TPE from MPE. We searched the PubMed and EMBASE databases for studies indexed from 2000 to March 2021. We included studies that (a) diagnosed TPE and MPE based on culture or pleural tissue biopsy and that (b) compared levels of Th1/Th2 cytokines between TPE and MPE. Pooled data based on a random-effects model or fixed-effects model and standardized mean differences (SMDs) across studies were used to compare TPE and MPE. We also performed Egger’s test to assess publication bias. Of 917 identified studies, a total of 42 studies were selected for the meta-analysis. Compared with MPE subjects, TPE subjects had a significantly higher level of TNF-α [2.22, (1.60–2.84)], an elevated level of IFN-γ [3.30, (2.57–4.40)] in pleural effusion, a situation where the Th1 immune response dominated. Conversely, the levels of interleukin-4 (IL-4) and IL-10 (Th2 cytokines) were higher in the MPE subjects than in the TPE subjects, showing statistically nonsignificant tiny effects [−0.15, (−0.94 to 0.63) and −0.04, (−0.21 to 0.12), respectively]. We confirmed that TPE, a situation in which the Th1 cytokines are predominant. The slight preponderance of Th2 cytokines in MPE, which is not convincing enough to prove.

Comparative accuracy of pleural fluid unstimulated interferon-gamma and adenosine deaminase for diagnosing pleural tuberculosis: A systematic review and meta-analysis

Objective

We compared diagnostic accuracy of pleural fluid adenosine deaminase (ADA) and interferon-gamma (IFN-γ) in diagnosing tuberculous pleural effusion (TPE) through systematic review and comparative meta-analysis.

Methods

We queried PubMed and Embase databases to identify studies providing paired data for sensitivity and specificity of both pleural fluid ADA and IFN-γ for diagnosing TPE. We used hierarchical summary receiver operating characteristic (HSROC) plots and HSROC meta-regression to model individual and comparative diagnostic performance of the two tests.

Results

We retrieved 376 citations and included 45 datasets from 44 publications (4974 patients) in our review. Summary estimates for sensitivity and specificity for ADA were 0.88 (95% CI 0.85–0.91) and 0.91 (95% CI 0.89–0.92), while for IFN-γ they were 0.91 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97), respectively. HSROC plots showed consistently greater diagnostic accuracy for IFN-γ over ADA across the entire range of observations. HSROC meta-regression using test-type as covariate yielded a relative diagnostic odds ratio of 2.22 (95% CI 1.68–2.94) in favour of IFN-γ, along with better summary sensitivity and specificity figures. No prespecified subgroup variable significantly influenced the summary diagnostic accuracy estimates.

Conclusion

Pleural fluid IFN-γ estimation has better diagnostic accuracy than ADA estimation for diagnosis of TPE.

A rapid calprotectin test for the diagnosis of pleural effusion

In previous studies, measuring the levels of calprotectin in patients with pleural effusion (PE) was an exceptionally accurate way to predict malignancy. Here, we evaluated a rapid method for the measurement of calprotectin levels as a useful parameter in the diagnosis of malignant pleural effusion (MPE) in order to minimise invasive diagnostic tests. Calprotectin levels were measured with Quantum Blue^® sCAL (QB^®sCAL) and compared with the gold standard reference ELISA method. Calprotectin levels in patients with benign pleural effusion (BPE) were significantly higher (p < 0.0001) than for MPE patients. We measured the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and positive and negative likelihood ratios (LRs) for a cut-off value of ≤ 14,150 ng/mL; the diagnostic accuracy was 64%. The odds ratio for PE calprotectin levels was 10.938 (95% CI [4.133 − 28.947]). The diagnostic performance of calprotectin concentration was better for predicting MPE compared to other individual parameters. Comparison of two assays showed a slope of 1.084, an intercept of 329.7, and a Pearson correlation coefficient of 0.798. The Bland–Altman test showed a positive bias for the QB^®sCAL method compared to ELISA fCAL^®. Clinical concordance between both these methods was 88.5% with a Cohen kappa index of 0.76 (95% CI [0.68 − 0.84]). We concluded that QB^®sCAL is a fast, reliable, and non-invasive diagnostic tool for diagnosing MPE and represents an alternative to ELISA that could be implemented in medical emergencies.

Pleural fluid tumor necrosis factor for diagnosis of pleural tuberculosis: A systematic review and meta-analysis

OBJECTIVE

Tumor necrosis factor (TNF) is an important local host response mediator in tuberculous pleural effusion (TPE) and is proposed as a potential biomarker for diagnosing TPE. We assessed the performance of pleural fluid TNF in the diagnosis of TPE, and evaluated its ability to distinguish TPE from parapneumonic or malignant effusions.

METHODS

We queried the PubMed and Embase databases for studies indexed till August 2020. We included studies that (a) provided data on sensitivity and specificity of pleural fluid TNF for the diagnosis of TPE, or (b) compared pleural fluid TNF levels between TPE and malignant or parapneumonic effusions. We used a hierarchical summary receiver operating characteristic plot to model summary sensitivity and specificity. A random effects model was used to pool standardized mean differences (SMD) across studies comparing TPE and other effusions. We explored heterogeneity using subgroup analysis. We also performed meta-regression to identify factors significantly influencing results.

RESULTS

We retrieved 1090 citations, and included 38 publications, in our review. The summary estimates for sensitivity, specificity, and diagnostic odds ratio were 0.79 (95% CI 0.72-0.84), 0.82 (95% CI 0.76-0.87), and 16.84 (95% CI 9.47-29.95) respectively. Pleural fluid TNF levels were significantly higher in TPE than in malignant effusions (summary SMD 1.50, 95% CI 1.13-1.87), but not parapneumonic effusions (summary SMD 0.61, 95% CI -0.14 to 1.35). None of the prespecified subgroup variables significantly influenced summary estimates.

CONCLUSION

Pleural fluid TNF has poor diagnostic accuracy for diagnosing TPE and imperfectly discriminates TPE from parapneumonic pleural effusions.

The diagnostic utility of pleural markers for tuberculosis pleural effusion

Tuberculosis pleural effusion (TPE) is common in clinical practice, and its diagnosis remains a challenge for clinicians. Ziehl-Neelsen staining, PE Mycobacterium tuberculosis culture, and biopsy are the gold standards for TPE diagnosis; however, they are time-consuming, invasive, observer-dependent, and insensitive. PE markers represent a rapid, low-cost, and non-invasive objective diagnostic tool for TPE. In the past decades, several PE biomarkers have been developed, and their diagnostic accuracy has been evaluated in many studies. Here, we reviewed the literature to summarize the diagnostic accuracy of these biomarkers, especially using the evidence from systematic review and meta-analysis. The current research strongly suggests that adenosine deaminase (ADA), interferon-gamma (IFN-γ), and interleukin 27 (IL-27) have extremely higher diagnostic accuracy for TPE, while the diagnostic accuracy of interferon gamma release assays (IGRAs), tumor necrosis factor-α (TNF-α), and interferon-γ-induced protein 10 kDa (IP-10) is moderate. Although some evidence supports C-X-C motif chemokine ligand 9 (CXCL9), CXCL11, CXCL12, sFas ligand, angiotensin-converting enzyme (ACE), calpain-1, spectrin breakdown products (SBDP), matrix metalloproteinase-1 (MMP-1), soluble CD26 (sCD26), soluble interleukin 2 receptor (sIL-2R) as useful diagnostic markers for TPE, more support is needed to validate their diagnostic accuracy. Finally, nucleic acid amplification tests (NAATs) have extremely high diagnostic specificity, but their sensitivity is low. Taken together, ADA is the preferred marker for TPE because its low cost and suitability for standardization.

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.

Identifying tuberculous pleural effusion using artificial intelligence machine learning algorithms

BACKGROUND

The differential diagnosis of tuberculous pleural effusion (TPE) is challenging. In recent years, artificial intelligence (AI) machine learning algorithms have started being used to an increasing extent in disease diagnosis due to the high level of efficiency, objectivity, and accuracy that they offer.

METHODS

Data samples on 192 patients with TPE, 54 patients with parapneumonic pleural effusion (PPE), and 197 patients with malignant pleural effusion (MPE) were retrospectively collected. Based on 28 different features obtained via statistical analysis, TPE diagnostic models using four machine learning algorithms (MLAs), namely logistic regression, k-nearest neighbors (KNN), support vector machine (SVM) and random forest (RF) were established and their respective diagnostic performances were calculated. The respective diagnostic performances of each of the four algorithmic models were compared with that of pleural fluid adenosine deaminase (pfADA). Based on 12 features with the most significant impacts on the accuracy of the RF model, a new RF model was designed for clinical application. To demonstrate its external validity, a prospective study was conducted and the diagnostic performance of the RF model was calculated.

RESULTS

The respective sensitivity and specificity of each of the four TPE diagnostic models were as follows: logistic regression - 80.5 and 84.8%; KNN- 78.6 and 86.6%; SVM - 83.2 and 85.9%; and RF - 89.1 and 93.6%. The sensitivity and specificity of pfADA were 85.4 and 84.1%, respectively, at the best cut-off value of 17.5 U/L. RF was the superior method among the four MLAs, and was also superior to pfADA. The newly designed RF model (based on 12 out of 28 features) exhibited an acceptable performance rate for the diagnosis of TPE with a sensitivity and specificity of 90.6 and 92.3%, respectively. In the prospective study, its sensitivity and specificity were 100.0 and 90.0%, respectively.

CONCLUSIONS

Establishing a model for the diagnosis of TPE using RF resulted in a more effective, economical, and faster diagnostic method. This method could enable clinicians to diagnose and treat TPE more effectively.

Tuberculous pleural effusion

Tuberculous effusion is a common disease entity with a spectrum of presentations from a largely benign effusion, which resolves completely, to a complicated effusion with loculations, pleural thickening and even frank empyema, all of which may have a lasting effect on lung function. The pathogenesis is a combination of true pleural infection and an effusive hypersensitivity reaction, compartmentalized within the pleural space. Diagnostic thoracentesis with thorough pleural fluid analysis including biomarkers such as adenosine deaminase and gamma interferon achieves high accuracy in the correct clinical context. Definitive diagnosis may require invasive procedures to demonstrate histological evidence of caseating granulomas or microbiological evidence of the organism on smear or culture. Drug resistance is an emerging problem that requires vigilance and extra effort to acquire a complete drug sensitivity profile for each tuberculous effusion treated. Nucleic acid amplification tests such as Xpert MTB/RIF can be invaluable in this instance; however, the yield is low in pleural fluid. Treatment consists of standard anti-tuberculous therapy or a guideline-based individualized regimen in the case of drug resistance. There is low-quality evidence that suggests possible benefit from corticosteroids; however, they are not currently recommended due to concomitant increased risk of adverse effects. Small studies report some short- and long-term benefit from interventions such as therapeutic thoracentesis, intrapleural fibrinolytics and surgery but many questions remain to be answered.

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.

Clinical significance of Glasgow Prognostic Score in patients with tuberculous pleurisy

Background

The Glasgow Prognostic Score (GPS) reflects the host systemic inflammatory response and is a validated, independent prognostic factor for various malignancies. We investigated the clinical significance of the GPS in patients with tuberculosis (TB) pleurisy, focusing on treatment outcomes including paradoxical response (PR).

Methods

This was a retrospective study performed between January 2010 and December 2015 in two referral and university hospitals in South Korea, with intermediate incidences of TB. In all, 462 patients with TB pleurisy were registered in the study. The patients were classified into three groups based on GPS score, as follows: (I) GPS of 2, elevated CRP level (>1.0 mg/dL) and hypoalbuminemia (<3.5 g/dL); (II) GPS of 1, elevated CRP level or hypoalbuminemia; and (III) GPS of 0, neither elevated CRP level nor hypoalbuminemia.

Results

A total of 367 patients with TB pleurisy were finally included. PR occurred in 102 (27.8%) patients after a mean of 75 days following initiation of anti-TB treatment. The proportion of PR occurrence was significantly lower in the GPS 2 group (P=0.007). Successful treatment outcomes including cure and completion were also significantly lower in the GPS 2 group (P=0.001), while all-cause mortality and TB-specific mortality were higher in the GPS 2 group (P=0.001 and <0.001, respectively). Old age over than 65 years old was an independent predicting factor for high mortality and lower PR occurrence. However, the TB relapse rate was not different among the three GPS groups.

Conclusions

Higher GPS value and elderly age were identified as prognostic factors for poor outcomes in TB pleurisy and as predicting factors for lower PR occurrence. More prospective studies are needed to clarify the utility of GPS in patients with TB pleurisy.

Developing a new intelligent system for the diagnosis of tuberculous pleural effusion

BACKGROUND AND OBJECTIVE

In countries with high prevalence of tuberculosis (TB), clinicians often diagnose tuberculous pleural effusion (TPE) by using diagnostic tests, which have not only poor sensitivity, but poor availability as well. The aim of our study is to develop a new artificial intelligence based diagnostic model that is accurate, fast, non-invasive and cost effective to diagnose TPE. It is expected that a tool derived based on the model be installed on simple computer devices (such as smart phones and tablets) and be used by clinicians widely.

METHODS

For this study, data of 140 patients whose clinical signs, routine blood test results, blood biochemistry markers, pleural fluid cell type and count, and pleural fluid biochemical tests' results were prospectively collected into a database. An Artificial intelligence based diagnostic model, which employs moth flame optimization based support vector machine with feature selection (FS-MFO-SVM), is constructed to predict the diagnosis of TPE.

RESULTS

The optimal model results in an average of 95% accuracy (ACC), 0.9564 the area under the receiver operating characteristic curve (AUC), 93.35% sensitivity, and 97.57% specificity for FS-MFO-SVM.

CONCLUSIONS

The proposed artificial intelligence based diagnostic model is found to be highly reliable for diagnosing TPE based on simple clinical signs, blood samples and pleural effusion samples. Therefore, the proposed model can be widely used in clinical practice and further evaluated for use as a substitute of invasive pleural biopsies.

Identification of differential expressed PE exosomal miRNA in lung adenocarcinoma, tuberculosis, and other benign lesions

Pleural effusion (PE) is a common clinical complication of many pulmonary and systemic diseases, including lung cancer and tuberculosis. Nevertheless, there is no clinical effective biomarker to identify the cause of PE. We attempted to investigate differential expressed exosomal miRNAs in PEs of lung adenocarcinoma (APE), tuberculous (TPE), and other benign lesions (NPE) by using deep sequencing and quantitative polymerase chain reaction (qRT-PCR). As a result, 171 differentiated miRNAs were observed in 3 groups of PEs, and 11 significantly differentiated exosomal miRNAs were validated by qRT-PCR. We identified 9 miRNAs, including miR-205-5p, miR-483-5p, miR-375, miR-200c-3p, miR-429, miR-200b-3p, miR-200a-3p, miR-203a-3p, and miR-141-3p which were preferentially represented in exosomes derived from APE when compared with TPE or NPE, while 3 miRNAs, including miR-148a-3p, miR-451a, and miR-150-5p, were differentially expressed between TPE and NPE. These different miRNAs profiles may hold promise as biomarkers for differential diagnosis of PEs with more validation based on larger cohorts.

Pleural fluid tests to diagnose tuberculous pleuritis

PURPOSE OF REVIEW

This article summarizes current data regarding the accuracy of pleural fluid tests assisting the diagnosis of tuberculous pleuritis (TBP).

RECENT FINDINGS

No pleural fluid test reliably rules-in TBP in settings with low TBP prevalence. Interferon-γ) alone or in combination with adenosine deaminase (ADA) is more reliable than ADA for this purpose in nonlow prevalences. ADA can reliably rule-out TBP in prevalences of less than 40% although in higher prevalences the product of interleukin-27 and ADA is the most accurate rule-out test.

SUMMARY

The definite diagnosis of TBP requires the isolation of Mycobacterium tuberculosis from pleural fluid or biopsies. Because of the low sensitivity of pleural fluid cultures and the invasiveness of pleural biopsy techniques, the concept of a pleural fluid test that accurately establishes or excludes TBP diagnosis has been proposed. Numerous pleural fluid tests have been evaluated for this purpose with ADA being the most widely accepted one. During the last years, it has been demonstrated that the ability of ADA to rule-in or rule-out TBP is affected by the prevalence of TBP in the setting where the test is used. The complementary use of interferon-γ or interleukin-27 increases the ability of ADA to rule-in or rule-out the disease, respectively.

Diagnostic value of interferon-γ-induced protein of 10kDa for tuberculous pleurisy: A meta-analysis

BACKGROUND

The accurate diagnosis of tuberculous pleurisy is still a clinical challenge. Many studies reported that interferon-γ-induced protein of 10kDa (IP-10) plays a role in diagnosing tuberculous pleurisy, but with considerable variance of results. This meta-analysis aimed to evaluate the overall diagnostic accuracy of IP-10 for tuberculous pleurisy.

METHODS

PubMed, EMBASE, and other databases were searched for studies examining accuracy of pleural IP-10 for diagnosing tuberculous pleurisy. Related data were extracted and sensitivity/specificity, positive/negative likelihood ratio (PLR/NLR), and diagnostic odds ratio (DOR) were pooled. Summary receiver operating characteristic curve and area under the curve (AUC) were performed and calculated to summarize the overall test performance.

RESULTS

Fourteen studies involving 1382 subjects met inclusion criteria, including 715 cases of tuberculous pleurisy and 667 controls. Summary estimates of the diagnostic performance of the IP-10 for tuberculous pleurisy were listed as follows: sensitivity, 0.84 (95%CI 0.81 to 0.87); specificity, 0.90 (95% CI 0.88 to 0.92); PLR, 7.96 (95% CI 5.59 to 11.32); NLR, 0.19 (95% CI 0.15 to 0.24); DOR, 49.82 (95% CI 28.08 to 88.38); and AUC 0.94. No publication bias was detected.

CONCLUSION

Pleural IP-10 is a useful diagnostic marker for tuberculous pleurisy. Nevertheless, its result should be interpreted together with the results of conventional test and clinical information of patients.

Cytokines as Biomarkers and Their Respective Clinical Cutoff Levels

Cytokines, including interleukins, interferons, tumor necrosis factors, and chemokines, have a variety of pro- and anti-inflammatory effects in the body through a number of biochemical pathways and interactions. Stimuli, actions, interactions, and downstream effects of cytokines have been investigated in more depth in recent years, and clinical research has also been conducted to implicate cytokines in causal patterns in certain diseases. However, particular cutoffs of cytokines as biomarkers for disease processes have not been well studied, and this warrants future work to potentially improve diagnoses for diseases with inflammatory markers. A limited number of studies in this area are reviewed, considering diseases correlated with abnormal cytokine profiles, as well as specific cutoffs at which cytokines have been deemed clinically useful for diagnosing those diseases through Receiver Operator Characteristics modeling. In light of studies such as those discussed in this review, cytokine testing has the potential to support diagnosis due to its lack of invasiveness and low cost, compared to other common types of testing for infections and inflammatory diseases.

Extracellular vesicles from malignant effusions induce tumor cell migration: inhibitory effect of LMWH tinzaparin

Elevated levels of extracellular vesicles (EVs) have been correlated with inflammatory diseases as well as progressive and metastatic cancer. By presenting tissue factor (TF) on their membrane surface, cellular microparticles (MPs) activate both the coagulation system and cell-signaling pathways such as the PAR/ERK pathway. We have shown before that malignant effusions are a rich source of tumor cell-derived EVs. Here, we used EVs from malignant effusions from three different patients after serial low-speed centrifugation steps as recommended by the ISTH (lsEV). Significant migration of human pancreatic carcinoma cells could be induced by lsEVs and was effectively inhibited by pre-incubation with tinzaparin, a low-molecular-weight heparin. Tinzaparin induced tissue factor pathway inhibitor (TFPI) release from tumor cells, and recombinant TFPI inhibited EV-induced tumor cell migration. EVs also induced ERK phosphorylation, whereas inhibitors of PAR2 and ERK suppressed EV-induced tumor cell migration. LsEVs have been characterized by high-resolution flow cytometry and, after elimination of smaller vesicles including exosomes, by further high-speed centrifugation (hsEV). The remaining population consisting primarily of MPs is indeed the main migration-inducing population with tenase activity. Compared to other LMWHs, tinzaparin is suggested to have high potency to induce TFPI release from epithelial cells. The migration-inhibitory effect of TFPI and the interruption of tumor cell migration by inhibitors of PAR2 and ERK suggest that lsEVs induce tumor cell migration by activating the PAR2 signaling pathway. Tinzaparin might inhibit this process at least partly by inducing the release of TFPI from tumor cells, which blocks PAR-activating TF complexes. The clinical relevance of the results is discussed.

Novel biomarker analysis of pleural effusion enhances differentiation of tuberculous from malignant pleural effusion

Lymphocytic pleurisy is commonly observed in tuberculosis and cancer. Noninvasive biomarkers are needed to distinguish tuberculous pleural effusion (TPE) from malignant pleural effusion (MPE) because current clinical diagnostic procedures are often invasive. We identified immune response biomarkers that can discriminate between TPE and MPE. Fourteen pleural effusion biomarkers were compared in 22 MPE patients and five TPE patients. Of the innate immunity biomarkers, the median levels of interleukin (IL)-1β and interferon-induced protein-10 (IP-10) were higher in TPE patients than in MPE patients (P<0.05 and P<0.01, respectively). Of the adaptive immunity biomarkers, the median levels of IL-13 and interferon-γ (IFN-γ) were higher in TPE patients than in MPE patients (P<0.05). In addition, the levels of basic fibroblast growth factor were higher in MPE patients than in TPE patients (P<0.05). Receiver operator characteristic analysis of these biomarkers was performed, resulting in the highest area under the curve (AUC) for IP-10 (AUC =0.95, 95% confidence interval, P<0.01), followed by IL-13 (AUC =0.86, 95% confidence interval, P<0.05). Our study shows that five biomarkers (IL-1β, IP-10, IFN-γ, IL-13, and basic fibroblast growth factor) have a potential diagnostic role in differentiating TPE from MPE, particularly in lung cancer-related MPE.

Potential diagnostic value of serum/pleural fluid IL-31 levels for tuberculous pleural effusion

The aim of this study was to explore the diagnostic value of IL-31 levels in the pleural fluid and plasma to differentially diagnose tuberculous and malignant pleural effusion. We enrolled 91 cases, including tuberculous pleural effusion (TPE, n = 50), malignant pleural effusion (MPE, n = 41), other cases including pneumonia with pleural fluid, pulmonary tuberculosis and healthy people as controls. Whole blood was stimulated with the M. tuberculosis-specific antigens and plasma was collected. The multiplex bead-based cytokine immunoassay was employed to measure the levels of various cytokines. IL-31 was found to be the most prominent cytokine (P < 0.0001), and with an optimal cut-off value of 67.5 pg/mL, the sensitivity and specificity for the diagnosis of TPE were 86% and 100%, respectively. Furthermore, the tuberculosis-specific IL-31 levels in the plasma of TPE patients were higher than that of MPE patients (P = 0.0002). At an optimal cut-off value of 23.9 pg/mL, the sensitivity and specificity for the diagnosis of TPE were 92.9% and 85.7%, respectively. Ultimately, the combination of pleural fluid with the plasma tuberculosis-specific IL-31 levels improved the sensitivity and specificity to 94.0% and 95.1%, respectively. Thus, we identified a novel biomarker for the diagnosis of TPE for clinical application.

Tuberculous pleural effusions: advances and controversies

On a global scale, tuberculosis (TB) remains one of the most frequent causes of pleural effusions. Our understanding of the pathogenesis of the disease has evolved and what was once thought to be an effusion as a result of a pure delayed hypersensitivity reaction is now believed to be the consequence of direct infection of the pleural space with a cascade of events including an immunological response. Pulmonary involvement is more common than previously believed and induced sputum, which is grossly underutilised, can be diagnostic in approximately 50%. The gold standard for the diagnosis of tuberculous pleuritis remains the detection of Mycobacterium tuberculosis in pleural fluid, or pleural biopsy specimens, either by microscopy and/or culture, or the histological demonstration of caseating granulomas in the pleura along with acid fast bacilli (AFB). In high burden settings, however, the diagnosis is frequently inferred in patients who present with a lymphocytic predominant exudate and a high adenosine deaminase (ADA) level, which is a valuable adjunct in the diagnostic evaluation. ADA is generally readily accessible, and together with lymphocyte predominance justifies treatment initiation in patients with a high pre-test probability. Still, false-negative and false-positive results remain an issue. When adding closed pleural biopsy to ADA and lymphocyte count, diagnostic accuracy approaches that of thoracoscopy. The role of other biomarkers is less well described. Early pleural drainage may have a role in selected cases, but more research is required to validate its use and to define the subpopulation that may benefit from such interventions.