Tired of the confusion around pleural effusions: Adenosine deaminase detection sets the record straight!

Abstract

Pleural effusion, characterized by the accumulation of fluid in the pleural space, poses significant challenges in clinical practice, especially in determining whether it belongs to the inflammatory exudates or non-inflammatory transudates. Adenosine deaminase (ADA), an enzyme primarily produced by immune cells, particularly lymphocytes, increase in response to inflammatory conditions, including tuberculosis and malignancies. Elevated ADA levels in pleural have been shown to correlate with inflammatory exudates, making it a valuable biomarker for differentiating between inflammatory and non-inflammatory effusions. Moreover, numerous studies have demonstrated the treatment function of ADA in inflammation- related pleural effusion syndrome. Recently, research has established the values for the implication of ADA in diagnosing and managing pleural disease. Based on these findings, ADA becomes a reliable, non-invasive marker for early diagnosis and the appropriate treatment for pleural inflammation, ultimately improving patient outcomes.

Key Words: Pleural effusion; Pleural inflammation; Diagnosis; Biomarker; Adenosine deaminase

Core Tip: Pleural effusion, characterized by the accumulation of fluid in the pleural space, poses significant challenges in clinical practice, particularly in distinguishing inflammatory exudates from non-inflammatory transudates. Adenosine deaminase (ADA), an enzyme primary produced by immune cells, especially lymphocytes, increase in response to inflammatory conditions, including infections such as tuberculosis and malignancies. Elevated ADA levels in pleural have been shown to correlate with inflammatory exudates, making it a valuable biomarker for differentiating between inflammatory and non-inflammatory effusions. Moreover, numerous studies have demonstrated the utility of ADA in inflammation- related pleural effusion syndrome. Recent research has established reference values for the implication of ADA in diagnosing and managing pleural disease. Based on these findings, ADA becomes a reliable, non-invasive marker for early diagnosis and the appropriate treatment of pleural inflammation, ultimately improving patient outcomes.

INTRODUCTION

The etiology and diagnosis of pleural effusion syndrome remain significant challenges in clinical practice, particularly in distinguishing inflammatory exudates from non-inflammatory transudates[1,2]. Traditional diagnostic methods rely on elevated pleural fluid protein and lactate dehydrogenase (LDH) levels. However, the limited sensitivity and specificity restrict their clinical implication[3,4]. In recent years, adenosine deaminase (ADA), an enzyme closely related to immune responses, has gained increasingly attention for its diagnostic potential in pleural fluid[5,6]. Recently, Maranhão et al[7] conducted a study in Brazil and globally to evaluate the ADA as a biomarker for diagnosing the inflammatory pleural effusion. The study enrolled 157 confirmed pleural effusion patients, including 124 with exudates and 33 with transudates. Patients included in this study were required to undergo thoracentesis or thoracoscopy. The diagnosis of pleural effusion was established based on the criteria defined by Maranhão and Silva Junior, with adjustments made to the total protein and total LDH levels in the pleural fluid. Exclusion criteria comprises absolute contraindications or inability to undergo thoracentesis or thoracoscopy, hemolysis in the pleural fluid, chronic renal failure, jaundice, unknown causes of pleural effusion syndrome, and the use of immunosuppressive drugs[8,9]. Receiver operating characteristic curve analysis was performed to determine the optimal cutoff value for P-ADA.

The study strictly follows STARD and STROBE guidelines to ensure methodological rigor and transparency in data reporting. Sample size calculation was based on an expected AUC > 0.50. For statistical analysis, non-parametric tests (e.g., Mann-Whitney U test) and multiple comparison corrections (Dunn’s test) were employed, considering the non-normal distribution of the data and strengthening the scientific validity of the analysis (Table 1).

Table 1 Basic study information.

Item	Content
Study type	Retrospective cohort study
Objective	To evaluate the diagnostic performance of P-ADA as a biomarker for inflammatory pleural diseases
Sample size	157 patients (exudates: 124 cases; transudates: 33 cases)
Key methods	ROC curve analysis to determine optimal P-ADA cutoff; diagnostic parameters evaluated using Youden’s index
Main conclusion	P-ADA ≥ 9.00 U/L demonstrates high diagnostic performance for inflammatory pleural effusions (AUC = 0.81, sensitivity = 77.69%)

AUC: Area under the curve; P-ADA: Pleural adenosine deaminase; ROC: Receiver operating characteristic.

IMPORTANT DISCOVERIES

The study found that the P-ADA value was significantly different between inflammatory and non-inflammatory pleural effusions[10,11], with an optimal cutoff of ≥ 9.00 U/L. This method exhibited a sensitivity of 77.69%, a specificity of 68.75%, a positive predictive value (PPV) of 90.38%, and an AUC of 0.8107 (Table 2). Despite the moderate specificity, the high sensitivity and superior PPV underscore its clinical significance in diagnosing inflammatory pleural effusion[12]. Furthermore, the study demonstrated that the elevation of P-ADA levels may reflect the diverse causes of inflammatory pleural effusion, such as tuberculous pleuritis, cancerous pleuritis. Patients with tuberculous pleural effusion showed a median P-ADA increase of 42.0 U/L, while an extremely high P-ADA level of 401.2 U/L was observed in lymphoma patients, suggesting that markedly elevated P-ADA levels may indicate malignancy. Additionally, the P-ADA level was significantly lower in transudates compared to exudates (6.85 U/L vs 18.4 U/L, P < 0.0001), confirming the role of ADA in differentiating between inflammatory and non-inflammatory responses (Table 3). Regard to mechanism, the authors described the pathological basis of ADA from an immunological perspective, emphasizing the key role of the ADA-2 isoenzyme in monocyte-macrophage activation[13,14]. This mechanistic insight provides theoretical support for P-ADA as a biomarker[15].

Table 2 Diagnostic performance parameters (Receiver operating characteristic curve analysis).

Parameter	Result, %	95%CI
Optimal cutoff (U/L)	≥ 9.00	-
Sensitivity	77.69	69.22-84.75
Specificity	68.75	49.99-83.88
Positive predictive value	90.38	83.03-95.29
Negative predictive value	44.90	30.67-59.77
AUC value	81.07	0.7174-0.8754
Diagnostic accuracy	75.82	68.24-82.37

AUC: Area under the curve.

Table 3 Distribution of pleural effusion etiologies.

Etiology category	n (%)	Notes
Transudates (Non-inflammatory)	33 (21)	Congestive heart failure (26 cases), cirrhosis (3 cases), etc.
Exudates (Inflammatory)	124 (79)	Tuberculous effusion (44 cases), adenocarcinoma (37 cases), etc.
Other notable etiologies	-	Empyema (8 cases), lymphoma (7 cases), etc.

ADVANTAGES AND EXISTED PROBLEMS

The study validated the role and value of detecting ADA levels in diagnosing inflammatory pleural effusion, emphasizing its clinical application, detection methodology, and regional representativeness[16]. First, the proposed cutoff value (≥ 9.00 U/L) is much lower than the traditional threshold for tuberculous pleural effusion (≥ 30 U/L), thereby broadening the clinical applicability of P-ADA, especially for early-stage inflammatory screening. Second, the cutoff value was determined using the Youden index, and the model's discriminatory power was evaluated using the Hosmer-Lemeshow test, ensuring the robustness of the results[17]. In terms of regional representativeness, since the study was initially conducted in Brazil, it provides region-specific data for pleural effusion diagnosis in areas with a high burden of tuberculosis, highlighting its public health significance[18,19].

Despite the advantages, the study has several limitations. For instance, the retrospective study design may bring a selection bias (e.g., including cases with complete data only) and an inability to control for confounding factors (e.g., comorbid infections or medication history. Also, the research was conducted at a single center, the population characteristics, such as age and etiology distribution may affect the generalizability of the results. Likewise, 79% of transudates were attributed to congestive heart failure, with fewer cases of other causes (e.g., cirrhosis), potentially underestimating P-ADA’s performance in non-cardiogenic pleural effusions. Additionally, although the authors emphasized that the cutoff value was based on statistical optimization, significant differences in P-ADA levels across different etiologies (e.g., tuberculosis vs. lymphoma) suggest that a single threshold may not be universally applicable across all clinical scenarios[20,21].

To address these issues, the following strategies can be implemented for targeted improvement[22,23]. A stratified diagnostic approach, which combines P-ADA levels with etiological features to establish stratified diagnostic thresholds, is recommended. For example, a threshold of ≥ 9 U/L can be used for initial screening of inflammatory pleural effusion, while levels ≥ 150 U/L should prompt investigation into lymphoma or complex infection. Additionally, rather than relying on single biomarker, combining multiple parameters can enhance diagnostic accuracy[24,25]. This could be achieved by integrating P-ADA value with cytokines (such as interleukin-6), microbiological tests, or imaging techniques[26]. Lastly, given the limitations of a single-center retrospective study, conducing multi-center prospective clinical studies is crucial to determine detection cutoff values and promote the widespread use of P-ADA level testing in regions with limited healthcare resources[27,28].

CONCLUSION

To summarize, this study systematically demonstrated the P-ADA exhibits high sensitivity in diagnosing of inflammatory pleural effusion and shows positive predication value[28,29], offering a practical tool for clinicians[30]. Despite the inherent limitations of a retrospective design, the methodological rigor and biological plausibility of the data provide high confidence in the findings[31]. Future research should focus on refining the cutoff value strategy and exploring its potential applications in personalized medicine, ultimately achieving precise diagnosis and early intervention of pleural effusion etiology[32].

ACKNOWLEDGEMENTS

We would like to thank Xi-Chen Wang (MSD China, Shanghai, China) for providing academic information consulting support.