Diagnostic value of pleural fluid neuron-specific enolase for malignant pleural effusion

Introduction

Pleural effusion is a common condition associated with over 60 different diseases. It can be classified into malignant pleural effusion (MPE) and benign pleural effusion (BPE). MPE occurs when the pleural effusion is caused by primary or metastatic cancers affecting the pleura, with lung cancer and breast cancer being the most frequent causes (1). BPE is defined as a pleural effusion caused by benign disorders such as pleural infection or heart failure (HF), mainly composed of tuberculous pleural effusion (TPE), parapneumonic pleural effusion (PPE) and cardiogenic pleural effusion (2). The differentiation between BPE and MPE is a crucial point in managing pleural effusion because the prognoses of MPE and BPE differ significantly (3). The median survival of MPE is less than 1 year. By contrast, BPE has a median survival of more than 1 year (4). The diagnosis of MPE should be made cautiously because a misdiagnosis is a disaster for a patient.

The gold standards for MPE are effusion cytology, pleural biopsy, and thoracoscopy (5). However, these diagnostic tools have inherent limitations. Cytology is a less invasive diagnostic tool with a short turnaround time; however, its sensitivity is only 58.2%, and subjectivity remains problematic (6). Pleural biopsy and thoracoscopy are invasive procedures and pose operation-related complications, such as bleeding and infection (7). Serum or pleural fluid tumor markers [e.g., carcinoembryonic antigen (8), and carbohydrate antigen 50 (CA50) (9)] are useful diagnostic tools for MPE because they offer advantages of rapidness, less invasiveness, objectivity, and easy accessibility (10). However, these tumor markers are inadequate to confirm or rule out MPE when used alone. For instance, a meta-analysis found that pleural carcinoembryonic antigen had a specificity of 0.94 for MPE, while its sensitivity was only 0.54 (8). Therefore, combining multiple tumor markers could be a promising diagnostic approach for MPE (11). It is crucial to assess the diagnostic accuracy of a single tumor marker because it is the basis for developing a diagnostic algorithm with multiple tumor markers.

Neuron-specific enolase (NSE) is involved in the glycolytic pathway and is mainly expressed in neural and endocrine tissues (12). Accumulated evidence indicates that NSE has diagnostic utility in small cell lung cancer (SCLC) (13) and neuroblastoma (14). Some studies also reveal that pleural fluid NSE helps the diagnosis of MPE (15). However, the available evidence is not always consistent. A study indicated that NSE had high accuracy in diagnosing MPE (16), but inadequate accuracy was also reported in another study (17). A meta-analysis with 14 studies reveals that the pooled sensitivity and specificity of NSE were 0.53 [95% confidence interval (CI): 0.38–0.67] and 0.85 (95% CI: 0.75–0.91), respectively (18). Significant heterogeneity is observed across published studies, but the sources of the heterogeneity remain largely unknown. This study aimed to assess the accuracy of NSE for MPE and explore the sources of heterogeneity among previous studies. We present this article in accordance with the STARD reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1538/rc) (19).

Methods

Participants

We prospectively recruited participants from two centers in China. The first center is The Affiliated Hospital of Inner Mongolia Medical University (Hohhot cohort), where recruitment took place from September 2018 to July 2021. The second center is the Affiliated Changshu Hospital of Nantong University (Changshu cohort), with recruitment from June 2020 to July 2021. The inclusion criterion was participants with an undiagnosed pleural effusion. We also included the participants transferred to our hospitals from other hospitals with a history of pleural effusion, but the underlying cause was unclear despite thoracentesis and pleural biopsy being performed. The following participants were excluded from the study: (I) those with a history of pleural effusion within the past three months, where the cause is clear; (II) individuals under 18 years of age; (III) pregnant individuals; (IV) those with insufficient pleural fluid specimens for research; (V) participants who developed pleural effusion during hospitalization; and (VI) those with pleural effusion resulting from trauma or surgery. After admission, the participants’ pleural fluid specimen was collected in an anticoagulant-free tube. The specimen was centrifuged within four hours after collection, and the supernatant was aliquoted and stored between −80 and −70 °C.

Ethics statement and informed consent

This study received approval from the ethics committees of The Affiliated Hospital of Inner Mongolia Medical University (No. 2018011) and the Affiliated Changshu Hospital of Nantong University (No. 2020-KY-009). This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from all individual participants.

Clinical trials registration

This study was prospectively registered at the Chinese Clinical Registry (www.chictr.org.cn). The registration number is ChiCTR1800017449, and the registration date is July 30, 2018.

Diagnostic criteria

MPE, TPE, PPE, and cardiogenic pleural effusion were defined according to published guidelines (20-23). In short, MPE was diagnosed through cytology or histology. For patients with negative cytology and who cannot or are unwilling to undergo a pleural biopsy, MPE was defined by the evidence of a primary tumor, clinical features (including imaging findings of pleural nodules, thickening, pulmonary masses, or bloody and exudative effusions with rapid progression), and ruling out other causes of BPE. Cardiogenic pleural effusion was diagnosed through medical imaging features, clinical signs and symptoms, laboratory tests (serum natriuretic peptides), and responses to anti-HF therapy. The diagnosis of TPE was based on pleural biopsy, culture for Mycobacterium tuberculosis (Mtb), or acid-fast staining. In patients at high risk for TPE, for example, those with lymphocytic exudate or adenosine deaminase (ADA) levels exceeding 35 U/L, who had negative microbiological results and were either unwilling or unable to undergo pleural biopsy, TPE was diagnosed based on the patients’ response to anti-tuberculosis treatment and the exclusion of other causes of pleural effusion. PPE was confirmed by effusion bacterial culture, response to antibiotic therapy, medical imaging features (encapsulation), and pleural biopsy. The NSE concentration was masked to physicians who made the final diagnoses in both centers.

NSE and routine biochemical analyses

We recorded the levels of glucose, ADA, leukocytes, lactate dehydrogenase (LDH), and protein in the patient’s pleural fluid with their medical records. We used the Roche Cobas electrochemiluminescence analyzer to detect NSE. Laboratory technicians who determined NSE were unaware of the subject’s clinical details.

Literature retrieval

To analyze the correlation between the prevalence of HF in the studied cohort and the diagnostic accuracy of NSE, we included all relevant studies from a meta-analysis published in 2017 (18). In addition, we also searched the PubMed database to identify relevant studies published after 2017. The search algorithm was (“neuron-specific enolase” OR NSE) AND (“pleural effusion” OR “pleural fluid”). The last search time was December 1, 2024. The inclusion criteria were studies investigating the diagnostic accuracy of pleural fluid NSE for MPE. Studies published not in English, animal studies, case reports, editorials, or comments were excluded.

Statistical analysis

Continuous data were presented as medians with interquartile ranges (IQRs), while categorical data were reported as absolute numbers and percentages. We employed the Kolmogorov-Smirnov method to test the normality of the continuous data. We used the Mann-Whitney U test and the Kruskal-Wallis H test to compare continuous data, if appropriate. Categorical variables were compared using the Chi-square test. Additionally, we conducted receiver operating characteristic (ROC) curve analysis to evaluate the diagnostic accuracy of NSE for MPE. The ROC curve is a graph that illustrates all potential combinations of sensitivity and specificity of an index test at various thresholds. The area under the curve (AUC) is a comprehensive indicator that reflects the diagnostic accuracy of an index test. Unlike sensitivity and specificity, which depend on the threshold, the AUC is a threshold-independent diagnostic metric. The decision curve analysis (DCA) was used to assess the net benefit of NSE (24). Unlike ROC curve analysis, which focuses on the diagnostic accuracy of an index test, DCA curves focus on the potential net benefit of adding a new diagnostic tool to the diagnostic pathway for a specific disease. All statistical analyses and graphs were performed using GraphPad Prism, and R. P<0.05 was considered statistically significant.

Results

Characteristics of the participants

The participant selection process has been outlined in our previous work (25). We initially enrolled a total of 232 participants. However, 21 participants were excluded from the study for the following reasons: 15 had unknown etiology, 2 withdrew their consent, and 4 had a history of cancer or pleural effusion. Consequently, we finalized the enrollment with 211 participants, comprising 153 from the Hohhot cohort and 58 from the Changshu cohort. The baseline characteristics of these participants are detailed in Table 1. Participants with MPE had significantly higher pleural fluid LDH activity and protein concentration compared to those with BPE. However, there was no significant difference between BPE and MPE in terms of pleural fluid leukocyte count, glucose, ADA, as well as serum protein and LDH. The BPE group consisted of 42 cases of PPE, 33 cases of TPE, 28 cases of HF, and 16 cases of other diseases.

Comparison of pleural fluid NSE levels between the MPE and BPE

As shown in Figure 1A, the median NSE level in the Hohhot cohort was 13.7 (IQR, 5.9–25.8) ng/mL in MPE and 6.2 (IQR, 3.2–12.7) ng/mL in BPE, with a statistically significant difference (P<0.001). In the Changshu cohort, the median pleural NSE level was 35.46 (IQR, 13.26–134.18) ng/mL in MPE and 22.8 (IQR, 7.2–42.4) ng/mL in BPE, with a marginal statistical significance (P=0.053). When both cohorts were combined, the median NSE level in MPE was 16.65 (IQR, 7.20–42.87) ng/mL, significantly higher than that in BPE [7.4 (IQR, 3.52–19.5) ng/mL, P<0.001].

Figure 1 Comparison of pleural fluid NSE between MPE and BPE. (A) NSE levels between MPE and BPE. (B) NSE in BPE. (C) NSE level in MPE caused by SCLC, NSCLC, and other cancers. BPE, benign pleural effusion; HF, heart failure; MPE, malignant pleural effusion; NSCLC, non-small cell lung cancer; NSE, neuron-specific enolase; PPE, parapneumonic pleural effusion; SCLC, small cell lung cancer; TPE, tuberculous pleural effusion.

As shown in Figure 1B, NSE differed significantly among patients with benign etiologies (P<0.05 for all cohorts). Figure 1C shows the association between MPE types and NSE level. We failed to find a significant difference in the pleural NSE levels and the types of MPE (P=0.31). Additionally, pleural fluid NSE was not significantly correlated with age, with a coefficient of −0.06 (P=0.38).

Diagnostic accuracy and net benefit of NSE for MPE

Figure 2A illustrates the ROC curves for NSE in all cohorts. The diagnostic accuracy of NSE is detailed in Table 2. In the Hohhot cohort, the AUC for NSE was 0.68 (95% CI: 0.59–0.77). At a threshold of 13.92 ng/mL, the sensitivity was 0.50 (95% CI: 0.38–0.62), while the specificity was 0.79 (95% CI: 0.70–0.86). In the Changshu cohort, the AUC was 0.65 (95% CI: 0.51–0.79), with a sensitivity of 0.42 (95% CI: 0.26–0.61) and a specificity of 0.84 (95% CI: 0.68–0.93) at a threshold of 62.50 ng/mL. The decision curves for NSE in both cohorts were close to the two reference lines (Figure 2B), indicating that the net benefit of NSE was low.

Figure 2 ROC curves (A) and decision curve analysis (B,C) of NSE for MPE. AUC, area under the curve; CI, confidence interval; MPE, malignant pleural effusion; NSE, neuron-specific enolase; ROC, receiver operating characteristic.

The prevalence of HF patients affected the diagnostic accuracy of NSE

Figure 1B shows that HF patients had the lowest NSE among all types of BPE. Therefore, we hypothesized that a high prevalence of HF in the studied cohort could result in higher AUC. To test this hypothesis, we retrieved the PubMed database to identify all published studies concerning the diagnostic value of pleural fluid NSE for MPE. Table 3 summarizes the characteristics of 19 eligible studies. Among them, 13 (including this study) reported the prevalence of HF in the cohort and thus were included in data analysis. Figure 3 shows a positive correlation between the prevalence of HF patients and the AUC of NSE, with a correlation coefficient of 0.70 (P=0.007).

Figure 3 The relationship between the prevalence of HF in the studied cohort and the AUC of NSE. AUC, area under the curve; HF, heart failure; NSE, neuron-specific enolase.

Discussion

The primary findings of this study were: (I) MPE patients had significantly higher NSE than BPE patients; (II) pleural fluid NSE had an AUC of <0.70 for MPE, and its net benefit was low; (III) the prevalence of HF patients was correlated with the AUCs in previous studies. These results suggest that the overall diagnostic value of pleural fluid NSE for MPE is relatively low, and the prevalence of HF patients in the cohort can partially explain the heterogeneity across available studies.

Many tumor markers are helpful for the diagnosis of MPE, such as carcinoembryonic antigen, CA15-3, and cytokeratin 19 fragments (Cyfra21-1) (41). Evidence from the systematic review and meta-analysis suggests these tumor markers have sensitivities of approximately 0.50 and specificities of >0.90 (42). In comparison, the NSE showed a sensitivity and specificity of only 0.29 and 0.86, respectively, which is lower than other tumor markers. Sensitivity and specificity are common metrics used to assess how well a test can accurately identify a condition. However, these measures can be influenced by the threshold chosen. On the other hand, the AUC is a threshold-independent metric that provides a comprehensive assessment of diagnostic accuracy. The AUC ranges from 0.50 to 1.00, with a higher AUC indicating better diagnostic accuracy. In our study, the AUC of NSE was 0.66. Therefore, we concluded that the overall diagnostic accuracy of NSE is inferior to traditional tumor markers such as carcinoembryonic antigen and CA15-3, and it is not a preferred marker for diagnosing MPE.

Compared to published studies, a strength of this study is that we used a decision curve to analyze the net benefit of NSE determination. Net benefit and diagnostic accuracy are two different issues in diagnostic test accuracy studies. Diagnostic accuracy reflects the consistency between index tests and reference standards, but it does not consider the impact of the index test on the clinical consequences of participants. Although the index test can benefit participants with true positive results, the hazard caused by a false positive index test is problematic. Therefore, we analyzed the net benefit of NSE using DCA and found that the decision curve for NSE was close to the reference line, suggesting that the net benefit of NSE is limited. To the best of our knowledge, this is the first study investigating the net benefit of NSE. The second strength lies in our investigation of the heterogeneity across previous studies. So far, 19 studies have investigated (Table 3) the accuracy of NSE for MPE, but their findings were heterogeneous. We reviewed their characteristics and found a positive correlation between the prevalence of HF patients and the AUC of NSE. Consequently, we conclude that a higher prevalence of HF patients in the study cohort may lead to a high diagnostic accuracy.

There are several limitations in this study. First, the sample size is small, especially in the Changshu cohort. This limitation prevents us from conducting subgroup analyses to explore factors that may influence the diagnostic accuracy of NSE. Second, due to the cross-sectional design of our study, we were unable to investigate the prognostic value of NSE in patients with MPE. Third, we used frozen pleural fluid specimens to determine NSE, but the long-term stability of NSE in frozen pleural fluid is unknown. However, we have studied the stability of CEA in pleural fluid and found that it is stable under −80 to −70 °C, suggesting that pleural tumor markers are stable under such a condition (43). Fourth, we did not compare the diagnostic accuracy of NSE with other tumor markers. Additionally, we did not investigate whether the combination of NSE with other tumor markers could improve the diagnostic accuracy. Fifth, the NSE level is affected by hemolysis (44), but erythrocyte count and cell-free hemoglobin level in pleural fluid were not routinely tested in our hospital, and thus, the confounding effect of hemolysis on NSE is unknown. Sixth, the MPE patients in this study were predominantly caused by NSCLC, with a limited number of SCLC cases.

Conclusions

In summary, our study found that the AUC of NSE for MPE was below 0.70. Previous studies reported (37) that the AUCs of other routine tumor markers were above 0.80. Therefore, NSE should not be advocated as a preferred diagnostic marker for MPE. However, it would be valuable to investigate whether NSE can provide additional diagnostic value beyond other tumor markers. Additionally, we found that the prevalence of HF patients in the studied cohort affected the diagnostic accuracy of NSE. This finding may partially explain the sources of heterogeneity across previous studies. Considering the small sample size in our study, larger studies are needed to validate our findings.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1538/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1538/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1538/prf

Funding: This work was supported by the Foundation of Inner Mongolia Medical University (No. YKD2022MS019), Suzhou Multicenter Clinical Study Project for Major Diseases (No. DZXYJ202416), Changshu’s Health Talent and Technology Project (No. KCH202504) and the Key Project of the Department of Education of Inner Mongolia Autonomous Region (No. NJZZ23008).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1538/coif). All authors report the funding from the Foundation of Inner Mongolia Medical University (No. YKD2022MS019), Suzhou Multicenter Clinical Study Project for Major Diseases (No. DZXYJ202416), Changshu’s Health Talent and Technology Project (No. KCH202504) and the Key Project of the Department of Education of Inner Mongolia Autonomous Region (No. NJZZ23008). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the ethics committees of the Affiliated Hospital of Inner Mongolia Medical University (No. 2018011) and the Affiliated Changshu Hospital of Nantong University (No. 2020-KY-009). Written informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Gayen S. Malignant Pleural Effusion: Presentation, Diagnosis, and Management. Am J Med 2022;135:1188-92. [Crossref] [PubMed]
2. Porcel JM, Esquerda A, Vives M, et al. Etiology of pleural effusions: analysis of more than 3,000 consecutive thoracenteses. Arch Bronconeumol 2014;50:161-5. [Crossref] [PubMed]
3. Quek JC, Tan QL, Allen JC, et al. Malignant pleural effusion survival prognostication in an Asian population. Respirology 2020;25:1283-91. [Crossref] [PubMed]
4. Walker SP, Morley AJ, Stadon L, et al. Nonmalignant Pleural Effusions: A Prospective Study of 356 Consecutive Unselected Patients. Chest 2017;151:1099-105. [Crossref] [PubMed]
5. Jany B, Welte T. Pleural Effusion in Adults-Etiology, Diagnosis, and Treatment. Dtsch Arztebl Int 2019;116:377-86. [Crossref] [PubMed]
6. Kassirian S, Hinton SN, Cuninghame S, et al. Diagnostic sensitivity of pleural fluid cytology in malignant pleural effusions: systematic review and meta-analysis. Thorax 2023;78:32-40. [Crossref] [PubMed]
7. Deschuyteneer EP, De Keukeleire T. Diagnostic value and safety of thoracoscopic pleural biopsies in pleural exudative effusions of unknown origin, including follow-up. BMJ Open Respir Res 2022;9:e001161. [Crossref] [PubMed]
8. Shi HZ, Liang QL, Jiang J, et al. Diagnostic value of carcinoembryonic antigen in malignant pleural effusion: a meta-analysis. Respirology 2008;13:518-27. [Crossref] [PubMed]
9. Cha SN, Niu Y, Wen JX, et al. Pleural carbohydrate antigen 50 and malignant pleural effusion: a prospective, double-blind diagnostic accuracy test. Transl Lung Cancer Res 2024;13:1061-8. [Crossref] [PubMed]
10. Zheng WQ, Hu ZD. Pleural fluid biochemical analysis: the past, present and future. Clin Chem Lab Med 2023;61:921-34. [Crossref] [PubMed]
11. Yang Y, Liu YL, Shi HZ. Diagnostic Accuracy of Combinations of Tumor Markers for Malignant Pleural Effusion: An Updated Meta-Analysis. Respiration 2017;94:62-9. [Crossref] [PubMed]
12. Xu CM, Luo YL, Li S, et al. Multifunctional neuron-specific enolase: its role in lung diseases. Biosci Rep 2019;39:BSR20192732. [Crossref] [PubMed]
13. Lu L, Zha Z, Zhang P, et al. NSE, positively regulated by LINC00657-miR-93-5p axis, promotes small cell lung cancer (SCLC) invasion and epithelial-mesenchymal transition (EMT) process. Int J Med Sci 2021;18:3768-79. [Crossref] [PubMed]
14. Li J, Qi Z, Chen M, et al. Clinical value of combined serum CA125, NSE and 24-hour urine VMA for the prediction of recurrence in children with neuroblastoma. Ital J Pediatr 2023;49:102. [Crossref] [PubMed]
15. Thi Huyen P, Li M, Li L, et al. Exploring the value of pleural fluid biomarkers for complementary pleural effusion disease examination. Comput Biol Chem 2021;94:107559. [Crossref] [PubMed]
16. Kuralay F, Tokgöz Z, Cömlekci A. Diagnostic usefulness of tumour marker levels in pleural effusions of malignant and benign origin. Clin Chim Acta 2000;300:43-55. [Crossref] [PubMed]
17. Gu Y, Zhai K, Shi HZ. Clinical Value of Tumor Markers for Determining Cause of Pleural Effusion. Chin Med J (Engl) 2016;129:253-8. [Crossref] [PubMed]
18. Zhu J, Feng M, Liang L, et al. Is neuron-specific enolase useful for diagnosing malignant pleural effusions? evidence from a validation study and meta-analysis. BMC Cancer 2017;17:590. [Crossref] [PubMed]
19. Bossuyt PM, Reitsma JB, Bruns DE, et al. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ 2015;351:h5527. [Crossref] [PubMed]
20. Hooper C, Lee YC, Maskell N, et al. Investigation of a unilateral pleural effusion in adults: British Thoracic Society Pleural Disease Guideline 2010. Thorax 2010;65:ii4-17. [Crossref] [PubMed]
21. Roberts ME, Neville E, Berrisford RG, et al. Management of a malignant pleural effusion: British Thoracic Society Pleural Disease Guideline 2010. Thorax 2010;65:ii32-40. [Crossref] [PubMed]
22. Davies HE, Davies RJ, Davies CW, et al. Management of pleural infection in adults: British Thoracic Society Pleural Disease Guideline 2010. Thorax 2010;65:ii41-53. [Crossref] [PubMed]
23. Feller-Kopman DJ, Reddy CB, DeCamp MM, et al. Management of Malignant Pleural Effusions. An Official ATS/STS/STR Clinical Practice Guideline. Am J Respir Crit Care Med 2018;198:839-49. [Crossref] [PubMed]
24. Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making 2006;26:565-74. [Crossref] [PubMed]
25. Yang Q, Niu Y, Wen JX, et al. Value of human epididymis secretory protein 4 in differentiating malignant from benign pleural effusion: an analysis of two cohorts. Ther Adv Respir Dis 2023;17:17534666231216566. [Crossref] [PubMed]
26. Pettersson T, Klockars M, Fröseth B. Neuron-specific enolase in the diagnosis of small-cell lung cancer with pleural effusion: a negative report. Eur Respir J 1988;1:698-700.
27. Menard O, Dousset B, Jacob C, et al. Improvement of the diagnosis of the cause of pleural effusion in patients with lung cancer by simultaneous quantification of carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) pleural levels. Eur J Cancer 1993;29A:1806-9. [Crossref] [PubMed]
28. Ferrer J, Villarino MA, Encabo G, et al. Diagnostic utility of CYFRA 21-1, carcinoembryonic antigen, CA 125, neuron specific enolase, and squamous cell antigen level determinations in the serum and pleural fluid of patients with pleural effusions. Cancer 1999;86:1488-95. [Crossref] [PubMed]
29. Miédougé M, Rouzaud P, Salama G, et al. Evaluation of seven tumour markers in pleural fluid for the diagnosis of malignant effusions. Br J Cancer 1999;81:1059-65. [Crossref] [PubMed]
30. Alataş F, Alataş O, Metintaş M, et al. Diagnostic value of CEA, CA 15-3, CA 19-9, CYFRA 21-1, NSE and TSA assay in pleural effusions. Lung Cancer 2001;31:9-16. [Crossref] [PubMed]
31. Ghayumi SM, Mehrabi S, Doroudchi M, et al. Diagnostic value of tumor markers for differentiating malignant and benign pleural effusions of Iranian patients. Pathol Oncol Res 2005;11:236-41. [Crossref] [PubMed]
32. Lee JH, Chang JH. Diagnostic utility of serum and pleural fluid carcinoembryonic antigen, neuron-specific enolase, and cytokeratin 19 fragments in patients with effusions from primary lung cancer. Chest 2005;128:2298-303. [Crossref] [PubMed]
33. Topolcan O, Holubec L, Polivkova V, et al. Tumor markers in pleural effusions. Anticancer Res 2007;27:1921-4.
34. Li CS, Cheng BC, Ge W, et al. Clinical value of CYFRA21-1, NSE, CA15-3, CA19-9 and CA125 assay in the elderly patients with pleural effusions. Int J Clin Pract 2007;61:444-8. [Crossref] [PubMed]
35. Korczynski P, Krenke R, Safianowska A, et al. Diagnostic utility of pleural fluid and serum markers in differentiation between malignant and non-malignant pleural effusions. Eur J Med Res 2009;14:128-33. [Crossref] [PubMed]
36. Valdés L, San-José E, Ferreiro L, et al. Combining clinical and analytical parameters improves prediction of malignant pleural effusion. Lung 2013;191:633-43. [Crossref] [PubMed]
37. Saba MA, Valeh T, Ehteram H, et al. Diagnostic Value of Neuron-Specific Enolase (NSE) and Cancer Antigen 15-3 (CA 15-3) in the Diagnosis of Pleural Effusions. Asian Pac J Cancer Prev 2017;18:257-61. [Crossref] [PubMed]
38. Volarić D, Flego V, Žauhar G, et al. Diagnostic value of tumour markers in pleural effusions. Biochem Med (Zagreb) 2018;28:010706. [Crossref] [PubMed]
39. Zhang H, Li C, Hu F, et al. Auxiliary diagnostic value of tumor biomarkers in pleural fluid for lung cancer-associated malignant pleural effusion. Respir Res 2020;21:284. [Crossref] [PubMed]
40. Fan X, Liu Y, Liang Z, et al. Diagnostic Value of Six Tumor Markers for Malignant Pleural Effusion in 1,230 Patients: A Single-Center Retrospective Study. Pathol Oncol Res 2022;28:1610280. [Crossref] [PubMed]
41. Zhang M, Yan L, Lippi G, et al. Pleural biomarkers in diagnostics of malignant pleural effusion: a narrative review. Transl Lung Cancer Res 2021;10:1557-70. [Crossref] [PubMed]
42. Nguyen AH, Miller EJ, Wichman CS, et al. Diagnostic value of tumor antigens in malignant pleural effusion: a meta-analysis. Transl Res 2015;166:432-9. [Crossref] [PubMed]
43. Yang DN, Niu Y, Wen JX, et al. Long-term stability of pleural fluid carcinoembryonic antigen and its effect on the diagnostic accuracy for malignant pleural effusion. Thorac Cancer 2023;14:2077-84. [Crossref] [PubMed]
44. Ruiz L, Munoz T, González A, et al. Routine data analysis for moderate hemolysis interference correction in neuron specific enolase quantification. Biochem Med (Zagreb) 2025;35:020802. [Crossref] [PubMed]