Pleural effusions represent a common clinical manifestation of diverse pathological processes, with tuberculosis and malignancy constituting the predominant etiologies in developing countries [1,2]. The differential diagnosis between tuberculous pleural effusions (TPE) and malignant pleural effusions (MPE) remains challenging due to overlapping clinical presentations and conventional diagnostic limitations [3,4]. Neopterin (1',2',3'-D-erythro-trihydroxypropylpterin), a pyrazino-pyrimidine compound belonging to the pteridine class, serves as a sensitive biomarker of cell-mediated immune activation [5]. This unconjugated pteridine is synthesized from guanosine triphosphate (GTP) through the GTP cyclohydrolase I pathway, primarily by activated macrophages and dendritic cells under the influence of interferon-gamma (IFN-γ) [6,7]. Mycobacterium tuberculosis, as an intracellular pathogen with prolonged macrophage survival capacity, induces robust cellular immune responses characterized by T-lymphocyte and macrophage activation [8]. This immunological cascade results in elevated neopterin production, potentially serving as a diagnostic marker for tuberculous inflammation [9,10]. Current diagnostic approaches for pleural effusion evaluation rely heavily on adenosine deaminase (ADA) measurement, with established sensitivity and specificity for tuberculous etiology [11,12]. However, the need for additional biomarkers with enhanced diagnostic accuracy has led to investigation of neopterin as a potential adjunctive tool [13,14]. Given the high tuberculosis burden in India and the diagnostic challenges in resource-limited settings, this study aims to evaluate the diagnostic utility of pleural fluid neopterin levels in differentiating tuberculous from malignant pleural effusions, comparing its performance with the established biomarker ADA.

2.1 Study Design and Setting A cross-sectional observational study was conducted at the Department of Pulmonary Medicine, Government General and Chest Hospital, Erragadda, Hyderabad, Telangana, India, over a 24-month period from December 2015 to November 2017. The study protocol received approval from the Institutional Ethics Committee, and written informed consent was obtained from all participants. 2.2 Study Population Inclusion Criteria: • Patients aged >15 years with moderate to massive pleural effusions • Willingness to provide informed consent Exclusion Criteria: • HIV-positive patients • Pleural effusions of cardiac or renal origin • Patients declining to participate 2.3 Clinical Assessment All participants underwent comprehensive clinical evaluation including detailed history, physical examination, and radiological assessment using chest radiography and ultrasonography. Smoking history, presenting symptoms (fever, cough, dyspnea, chest pain), and demographic data were systematically recorded. 2.4 Laboratory Methods 2.4.1 Pleural Fluid Collection and Processing Pleural fluid samples were obtained via thoracocentesis under sterile conditions. Samples were centrifuged at 3000 rpm for 10 minutes, and supernatants were stored at -40°C until analysis. 2.4.2 Neopterin Measurement Pleural fluid neopterin levels were determined using enzyme-linked immunosorbent assay (ELISA) with the Human Neopterin Kit (IBL Medical, Turkey) based on biotin double-antibody sandwich technology. The assay procedure followed manufacturer protocols with standard dilutions ranging from 40 nmol/L to 1.25 nmol/L. Optical density was measured at 450 nm wavelength within 10 minutes of stop solution addition. 2.4.3 Adenosine Deaminase Assay ADA levels were measured using colorimetric method with spectrophotometric detection. Results were expressed in international units per liter (IU/L). 2.4.4 Additional Biochemical Parameters Serum glucose, protein, urea, creatinine, and pleural fluid cell count with differential were analyzed using standard laboratory techniques. 2.5 Diagnostic Confirmation Definitive diagnosis was established through: • Pleural biopsy with histopathological examination • Bronchoscopy with biopsy where indicated • Cytological examination of pleural fluid • Microbiological studies including acid-fast bacilli staining and culture 2.6 Statistical Analysis Statistical analysis was performed using SPSS software version 22.0. Continuous variables were expressed as mean ± standard deviation and compared using Student's t-test. Categorical variables were analyzed using chi-square test. Receiver operating characteristic (ROC) curves were constructed to determine optimal cut-off values and assess diagnostic performance. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. A p-value <0.05 was considered statistically significant.

3.1 Demographics and Clinical Characteristics A total of 80 patients were enrolled, comprising 60 males (75%) and 20 females (25%), with a male-to-female ratio of 3:1. The mean age was 49.6 ± 15.2 years (median: 50 years, range: 13-80 years). The predominant age group was 41-60 years (46.3%), followed by 21-40 years (27.5%) (Table 1). Table 1: Demographic Characteristics of Study Population Parameter n (%) Gender Male 60 (75.0) Female 20 (25.0) Age Groups (years) ≤20 2 (2.5) 21-40 22 (27.5) 41-60 37 (46.3) >60 19 (23.8) Smoking History Current/Former smokers 62 (77.5) Non-smokers 18 (22.5) Table 1: demonstrates the demographic distribution with male predominance and peak incidence in middle-aged adults, consistent with tuberculosis epidemiology in endemic regions. 3.2 Clinical Presentation The most frequent presenting symptoms were cough (83.8%), fever (75.0%), dyspnea (67.5%), and chest pain (52.5%). Most patients presented with multiple symptoms concurrently (Table 2). Table 2: Clinical Presentation and Pleural Effusion Characteristics Parameter n (%) Symptoms Cough 67 (83.8) Fever 60 (75.0) Dyspnea 54 (67.5) Chest pain 42 (52.5) Effusion Laterality Right-sided 37 (46.3) Left-sided 36 (45.0) Bilateral 7 (8.8) Table 2 shows the clinical symptomatology with cough as the predominant symptom, and approximately equal distribution of right and left-sided effusions. 3.3 Etiological Diagnosis Following comprehensive diagnostic evaluation, tuberculosis was identified as the predominant etiology in 51 patients (63.8%), followed by malignancy in 27 patients (33.8%). Other causes included congestive heart failure and suppurative conditions, each accounting for 1.3% (Table 3). Table 3: Etiological Distribution of Pleural Effusions Etiology n (%) Tuberculosis 51 (63.8) Malignancy 27 (33.8) Congestive heart failure 1 (1.3) Suppurative 1 (1.3) Total 80 (100.0) Table 3 demonstrates the etiological spectrum with tuberculosis predominance, reflecting the high disease burden in the study population. 3.4 Biomarker Analysis 3.4.1 Neopterin Levels Mean pleural fluid neopterin concentrations were significantly elevated in tuberculous effusions compared to malignant effusions (7.92 ± 7.40 vs 4.48 ± 1.60 nmol/L, p<0.05). The overall study population demonstrated a mean neopterin level of 5.38 ± 5.96 nmol/L (Table 4). 3.4.2 Adenosine Deaminase Levels ADA levels were similarly elevated in tuberculous effusions versus malignant effusions (82.65 ± 49.25 vs 56.07 ± 47.47 IU/L, p<0.05). The overall mean ADA level was 75.84 ± 51.99 IU/L. Table 4: Comparative Biomarker Analysis in Tuberculous vs Malignant Pleural Effusions Biomarker Tuberculous (n=51) Malignant (n=27) p-value Neopterin (nmol/L) 7.92 ± 7.40 4.48 ± 1.60 <0.05 ADA (IU/L) 82.65 ± 49.25 56.07 ± 47.47 <0.05 Random blood glucose (mg/dL) 98.77 ± 15.10 108.07 ± 12.23 <0.05 Serum protein (g/dL) 5.19 ± 1.04 4.80 ± 1.56 0.24 Table 4 illustrates the significant elevation of both neopterin and ADA in tuberculous effusions, with notably higher glucose levels in malignant cases, possibly reflecting paraneoplastic phenomena. 3.5 Additional Laboratory Parameters Serum glucose levels were significantly higher in patients with malignant effusions (108.07 ± 12.23 vs 98.77 ± 15.10 mg/dL, p<0.05). No significant differences were observed in serum protein, urea, creatinine levels, or pleural fluid cell count differentials between groups (Table 5). Table 5: Additional Laboratory Parameters Parameter Tuberculous Malignant p-value Blood urea (mg/dL) 28.86 ± 5.45 27.67 ± 6.77 0.42 Serum creatinine (mg/dL) 1.07 ± 0.22 1.00 ± 0.21 0.19 Lymphocyte count (cells/mm) 85.69 ± 12.37 85.56 ± 14.76 0.97 Neutrophil count (cells/mm) 14.31 ± 12.37 14.07 ± 13.38 0.93 Table 5 demonstrates no significant differences in renal function parameters or pleural fluid cellular composition between tuberculous and malignant effusions. 3.6 Diagnostic Performance Analysis 3.6.1 ROC Curve Analysis ROC curve analysis revealed an area under the curve (AUC) of 0.629 (95% CI: 0.501-0.756) for neopterin and 0.661 (95% CI: 0.531-0.791) for ADA. The difference between the two biomarkers was not statistically significant (p>0.05). 3.6.2 Sensitivity and Specificity At an optimal cut-off value of 4.3 nmol/L, pleural fluid neopterin demonstrated 70.0% sensitivity and 48.1% specificity for tuberculous effusion diagnosis. ADA, at a cut-off of 54.0 IU/L, showed 73.5% sensitivity and 59.3% specificity (Table 6). Table 6: Diagnostic Performance Characteristics Biomarker Cut-off Sensitivity (%) Specificity (%) AUC (95% CI) Neopterin 4.3 nmol/L 70.0 48.1 0.629 (0.501-0.756) ADA 54.0 IU/L 73.5 59.3 0.661 (0.531-0.791) Table 6 shows comparable sensitivity between neopterin and ADA, though ADA demonstrates superior specificity for tuberculous effusion diagnosis. 3.7 Diagnostic Confirmation Pleural biopsy provided diagnostic confirmation in 67.5% of cases, with positive results for tuberculosis in 54 patients. Bronchoscopy was positive for malignancy in 33.8% of cases, providing supportive evidence for neoplastic etiology.

This study demonstrates the potential diagnostic utility of pleural fluid neopterin as a biomarker for differentiating tuberculous from malignant pleural effusions, though with limitations that require careful interpretation. 4.1 Demographic and Clinical Patterns The observed male predominance (75%) and peak incidence in the 41-60 year age group align with established epidemiological patterns of tuberculosis in endemic regions [15,16]. The high prevalence of smoking (77.5%) in our cohort may reflect both the increased susceptibility to tuberculosis and malignancy associated with tobacco use [17,18]. The predominance of tuberculosis (63.8%) over malignancy (33.8%) as the primary cause of pleural effusion differs from patterns observed in developed countries, where malignancy typically predominates [19,20]. This distribution reflects the continued high burden of tuberculosis in the Indian subcontinent and emphasizes the clinical relevance of developing improved diagnostic tools for tuberculous effusions [21]. 4.2 Biomarker Performance and Mechanistic Insights The significantly elevated neopterin levels in tuberculous compared to malignant effusions (7.92 vs 4.48 nmol/L, p<0.05) support the biological rationale for this biomarker. Neopterin production by activated macrophages under IFN-γ stimulation reflects the robust Th1-mediated immune response characteristic of tuberculous inflammation [22,23]. Our findings corroborate previous studies by Cok et al., who reported median neopterin levels of 13.15 nmol/L in tuberculous versus 2.44 nmol/L in malignant effusions [24]. Similarly, Koşar et al. demonstrated significantly higher neopterin levels in tuberculous compared to malignant effusions [25]. The absolute values in our study were lower than some previous reports, potentially reflecting population differences, analytical variations, or disease severity factors. 4.3 Comparative Analysis with ADA Both neopterin and ADA demonstrated significant elevation in tuberculous effusions, reflecting their shared dependence on cellular immune activation. The correlation between these biomarkers is consistent with their common pathway of macrophage activation under IFN-γ stimulation [26,27]. However, ADA demonstrated superior specificity (59.3% vs 48.1%) while maintaining comparable sensitivity (73.5% vs 70.0%). This performance difference may reflect the more established role of ADA in tuberculous inflammation and its validation across diverse populations [28,29]. The AUC values (0.661 for ADA vs 0.629 for neopterin) suggest modest diagnostic performance for both biomarkers, indicating that neither provides sufficient accuracy for standalone diagnosis. This emphasizes the need for integrated diagnostic approaches combining clinical, radiological, and multiple biochemical parameters [30]. 4.4 Clinical Implications and Limitations The moderate sensitivity and specificity of neopterin limit its utility as a primary diagnostic tool. However, its potential role as an adjunctive biomarker in combination with established parameters merits consideration. The relatively straightforward ELISA-based measurement could facilitate implementation in resource-limited settings where tuberculosis burden is highest [31]. Several limitations must be acknowledged. The relatively small sample size (n=80) may limit statistical power and generalizability. The absence of a longitudinal design precludes assessment of neopterin's utility in treatment monitoring or prognostic evaluation. Additionally, the study did not evaluate potential confounding factors such as concurrent infections, immunosuppression, or medication effects that could influence neopterin levels [32,33]. 4.5 Biochemical Observations The significantly higher glucose levels in malignant effusions (108.07 vs 98.77 mg/dL, p<0.05) represents an interesting finding that may reflect paraneoplastic phenomena or insulin resistance associated with malignancy [34]. This observation warrants further investigation as a potential complementary diagnostic parameter. The absence of significant differences in conventional parameters such as protein levels, cell counts, and renal function markers between groups reinforces the challenge of differential diagnosis and the need for specific biomarkers [35]. 4.6 Future Research Directions Future studies should focus on larger, multicenter cohorts with standardized diagnostic protocols to better define neopterin's diagnostic performance across diverse populations. Investigation of neopterin in combination with other emerging biomarkers, such as interferon-gamma release assays, cytokines, and matrix metalloproteinases, could enhance diagnostic accuracy [36,37]. Longitudinal studies evaluating neopterin's role in treatment monitoring and prognostic assessment would provide valuable clinical insights. Additionally, economic analyses comparing neopterin measurement costs with diagnostic benefits could inform implementation strategies in resource-limited settings [38].

Pleural fluid neopterin levels are significantly elevated in tuberculous pleural effusions compared to malignant effusions, providing diagnostic information comparable to adenosine deaminase. However, the moderate sensitivity (70.0%) and specificity (48.1%) limit its utility as a standalone diagnostic tool. The findings suggest that neopterin may serve as an adjunctive biomarker in pleural fluid analysis, particularly in settings where tuberculosis prevalence is high and diagnostic resources are limited. The correlation with ADA levels supports the biological rationale for neopterin as a marker of cellular immune activation in tuberculous inflammation. Clinical implementation should consider neopterin as part of a comprehensive diagnostic approach rather than a replacement for established methods. Further research with larger cohorts and standardized protocols is needed to better define the optimal role of neopterin in pleural effusion evaluation and to explore its potential in combination with other emerging biomarkers. The study contributes to the growing body of evidence supporting the development of immunological biomarkers for tuberculosis diagnosis, addressing a critical need in high-burden, resource-limited settings where rapid and accurate diagnosis remains challenging.

1. Broaddus VC, Light RW. Pleural effusion. In: Murray and Nadel's Textbook of Respiratory Medicine. 6th ed. Philadelphia: Elsevier; 2016. p. 1396-1424. 2. Hassan T, Al-Alawi M, Chotirmall SH, McElvaney NG. Pleural fluid analysis: standstill or a work in progress? Pulm Med. 2012;2012:716235. 3. Light RW, Macgregor MI, Luchsinger PC, Ball Jr WC. Pleural effusions: the diagnostic separation of transudates and exudates. Ann Intern Med. 1972;77(4):507-13. 4. Aggarwal AN, Gupta D, Jindal SK. Diagnosis of tuberculous pleural effusion. Indian J Chest Dis Allied Sci. 1999;41(2):89-100. 5. Fuchs D, Weiss G, Wachter H. Neopterin, biochemistry and clinical use as a marker for cellular immune reactions. Int Arch Allergy Immunol. 1993;101(1):1-6. 6. Eisenhut M. Neopterin in diagnosis and monitoring of infectious diseases. J Biomarkers. 2013;2013:196432. 7. Wachter H, Fuchs D, Hausen A, Reibnegger G, Werner ER. Neopterin as marker for activation of cellular immunity: immunologic basis and clinical application. Adv Clin Chem. 1989;27:81-141. 8. Flynn JL, Chan J. Immunology of tuberculosis. Annu Rev Immunol. 2001;19:93-129. 9. Immanuel C, Swamy R, Kannapiran M, et al. Neopterin as a marker for cell-mediated immunity in patients with pulmonary tuberculosis. Int J Tuberc Lung Dis. 1997;1(2):175-80. 10. Mohamed KH, Mobasher AA, Yousef AR, et al. BAL neopterin: a novel marker for cell-mediated immunity in patients with pulmonary tuberculosis and lung cancer. Chest. 2001;119(3):776-80. 11. Valdés L, Alvarez D, San José E, et al. Value of adenosine deaminase in the diagnosis of tuberculous pleural effusions in young patients in a region of high prevalence of tuberculosis. Thorax. 1995;50(6):600-3. 12. Aggarwal AN, Agarwal R, Sehgal IS, et al. Meta-analysis of Indian studies evaluating adenosine deaminase for diagnosing tuberculous pleural effusion. Int J Tuberc Lung Dis. 2016;20(10):1386-91. 13. Cesur S, Aslan T, Hoca NT, et al. Clinical importance of serum neopterin level in patients with pulmonary tuberculosis. Int J Mycobacteriol. 2014;3(1):5-8. 14. Baganha MF, Mota-Pinto A, Pêgo MA, et al. Neopterin in tuberculous and neoplastic pleural fluids. Lung. 1992;170(3):155-61. 15. Balasubramanian R, Garg R, Santha T, et al. Gender disparities in tuberculosis: report from a rural DOTS programme in south India. Int J Tuberc Lung Dis. 2004;8(3):323-32. 16. Rao VG, Bhat J, Yadav R, et al. Prevalence of pulmonary tuberculosis—a baseline survey in central India. PLoS One. 2012;7(8):e43225. 17. Cornfield J, Haenszel W, Hammond EC, et al. Smoking and lung cancer: recent evidence and a discussion of some questions. Int J Epidemiol. 2009;38(5):1175-91. 18. Jee SH, Golub JE, Jo J, et al. Smoking and risk of tuberculosis incidence, mortality, and recurrence in South Korean men and women. Am J Epidemiol. 2009;170(12):1478-85. 19. Porcel JM, Light RW. Diagnostic approach to pleural effusion in adults. Am Fam Physician. 2006;73(7):1211-20. 20. Mayse ML. Non-malignant pleural effusions. In: Fishman AP, editor. Fishman's Pulmonary Diseases and Disorders. 4th ed. New York: McGraw-Hill; 2008. p. 1487-504. 21. WHO. Global tuberculosis report 2020. Geneva: World Health Organization; 2020. 22. Murray PJ. Macrophage Polarization. Annu Rev Physiol. 2017;79:541-66. 23. Schwarz G, Fuchs D, Leitner B, et al. 7,8-dihydroneopterin, a pteridine derivative involved in the bactericidal activity of human macrophages. Infect Immun. 1983;42(1):457-9. 24. Cok G, Parildar Z, Basol G, et al. Pleural fluid neopterin levels in tuberculous pleurisy. Clin Biochem. 2007;40(12):876-80. 25. Koşar F, Yurt S, Yiğitbaş BÇ, et al. Comparative value of pleural fluid adenosine deaminase and neopterin levels in the differential diagnosis of pleural effusions. Tuberk Toraks. 2015;63(4):243-9. 26. Werner-Felmayer G, Werner ER, Fuchs D, et al. Characteristics of interferon induced tryptophan metabolism in human cells in vitro. Biochim Biophys Acta. 1989;1012(2):140-7. 27. Dimakou K, Hillas G, Bakakos P. Adenosine deaminase activity and its isoenzymes in the sputum of patients with pulmonary tuberculosis. Int J Tuberc Lung Dis. 2009;13(6):744-8. 28. Mehta AA, Gupta AS, Ahmed S, Rajesh V. Diagnostic utility of adenosine deaminase in exudative pleural effusions. Lung India. 2014;31(2):142-8. 29. Arnold DT, Bhatnagar R, Fairbanks LD, et al. Pleural fluid adenosine deaminase (pfADA) in the diagnosis of tuberculous effusions in a low incidence population. PLoS One. 2015;10(2):e0113047. 30. Verma A, Dagaonkar RS, Marshall D, et al. Differentiating malignant from tubercular pleural effusion by cancer ratio plus (cancer ratio: pleural lymphocyte count). Can Respir J. 2016;2016:5021574. 31. Pai M, Behr MA, Dowdy D, et al. Tuberculosis. Nat Rev Dis Primers. 2016;2:16076. 32. Toygar M, Aydin I, Agilli M, et al. The relation between oxidative stress, inflammation, and neopterin in the paraquat-induced lung toxicity. Hum Exp Toxicol. 2015;34(2):198-204. 33. Uysal HK, Sohrabi P, Habip Z, et al. Neopterin and soluble CD14 levels as indicators of immune activation in cases with indeterminate pattern and true positive HIV-1 infection. PLoS One. 2016;11(3):e0152258. 34. Hall GC, Roberts CM, Boulis M, et al. Diabetes and the risk of lung cancer. Diabetes Care. 2005;28(3):590-4. 35. Samanta S, Sharma A, Das B, et al. Significance of total protein, albumin, globulin, serum effusion albumin gradient and LDH in the differential diagnosis of pleural effusion secondary to tuberculosis and cancer. J Clin Diagn Res. 2016;10(8):BC14-8. 36. Aggarwal AN, Agarwal R, Gupta D, et al. Interferon gamma release assays for diagnosis of pleural tuberculosis: a systematic review and meta-analysis. J Clin Microbiol. 2015;53(8):2451-9. 37. Yang L, Hu YJ, Li FG, et al. Analysis of cytokine levels in pleural effusions of tuberculous pleurisy and tuberculous empyema. Mediators Inflamm. 2016;2016:9529028. 38. Karkhanis VS, Joshi JM. Pleural effusion: diagnosis, treatment, and management. Open Access Emerg Med. 2012;4:31-52.