Head-to-head comparison of the diagnostic accuracy of pleural fluid, serum carcinoembryonic antigen, and their ratio for malignant pleural effusion: a systematic review and meta-analysis

Introduction

Pleural effusion is common in clinical practice and can be caused by more than 60 disorders, including tuberculous pleurisy, congestive heart failure, malignancy and pneumonia (1,2). Pleural effusions caused by cancers are termed malignant pleural effusion (MPE). In contrast, pleural effusion not secondary to malignancy is defined as benign pleural effusion (BPE), also termed non-MPE. Lung, breast, gastrointestinal, and ovarian cancers are common causes of MPE (3,4). MPE is an indicator of advanced cancer, with a median survival of less than 1 year (5). In addition to cancer, other benign diseases (e.g., tuberculous pleurisy, congestive heart failure, pneumonia) can also cause pleural effusion (1,6). The differentiation between MPE and BPE is critical in the etiological diagnosis of pleural effusion. Currently, the gold standards for the MPE are effusion cytology and histology (7,8). Although the specificity of cytology is 1.00, its sensitivity is less than 0.60 (9). A biopsy guided by imaging or followed by thoracoscopy is required in patients with negative cytology (8). Thoracoscopy, followed by biopsy, is the most widely used diagnostic tool, with a diagnostic yield >90% (10,11). However, it is invasive and can cause operation-related complications such as bleeding and infection (12,13).

The development of non-invasive or mini-invasive diagnostic tools with fewer operation-related complications is of great value in improving the management of pleural effusion. Ultrasound represents a non-invasive diagnostic option, and a recent study indicated that it could separate exudates from transudates with high accuracy (14). However, no studies have reported its value in discriminating between BPE and MPE. Positron emission tomography-computed tomography (PET-CT) is another non-invasive diagnostic tool for MPE with high accuracy (15), but its high cost, unique instrument, and radiation limit its clinical application. Pleural fluid and serum biomarkers are alternative diagnostic tools for MPE due to their advantages of easy access, objectivity, and rapidity (16,17). High tumor marker concentrations are associated with a high probability of MPE and thus encourage pulmonologists to order further diagnostic procedures, such as a histological examination or repeated cytology (18). Accumulating studies have demonstrated that pleural fluid and serum carcinoembryonic antigen (CEA) are valuable diagnostic markers for MPE (19). Previous systematic reviews and meta-analyses showed that the pooled sensitivity and specificity of pleural fluid CEA for MPE were 0.60 and 0.97, respectively (20,21). Meanwhile, the sensitivity and specificity of serum CEA were 0.40–0.60 and 0.80–0.90, respectively (22,23). In addition, some studies reported that pleural fluid to serum CEA ratio (CR) is also helpful for diagnosing MPE, with a sensitivity and specificity of 0.60–0.85 and 0.92–0.99, respectively (24,25). However, the findings of available studies are not always consistent. No systematic review or meta-analysis has compared the diagnostic accuracy of pleural fluid, serum CEA, and CR head-to-head. This systematic review and meta-analysis examined their diagnostic value for MPE head-to-head. We present this article in accordance with the PRISMA-DTA reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2152/rc) (26).

Methods

Search strategy

We searched the PubMed and Web of Science databases to identify eligible studies published before 5 June 2024. The search algorithm in the PubMed database was ((“Carcinoembryonic Antigen”[Mesh]) OR (“CEA”) or (“Carcinoembryonic Antigen”)) AND ((“Pleural Effusion, Malignant”[Mesh]) OR (“malignant pleural effusion*”) OR (“pleural effusion*”)). The search strategy for the Web of Science database was similar to that for PubMed.

Inclusion and exclusion criteria

The inclusion criteria for this systematic review and meta-analysis were (I) studies simultaneously investigating the diagnostic accuracy of pleural fluid, serum CEA, and CR for MPE; (II) the sensitivities and specificities of serum and pleural CEA were reported, allowing us to construct a two-by-two table. The exclusion criteria were (I) animal studies; (II) non-English publications; (III) conference abstracts, editorials, literature reviews, and comments.

Two systematic reviewers independently screened all retrieved studies. Any disagreements were resolved by consensus. The literature screening was a two-round process. The first round excluded irrelevant studies by reading the titles and abstracts. The second round was to determine the eligibility of the remaining studies by reading the full text.

Data extraction and quality assessment

We extracted the following data from all included studies: first author, country, year of publication, sample size, design, CEA assay, definition of MPE, area under the curve (AUC) of CEA, sensitivity, specificity, and corresponding threshold. A two-by-two table was constructed according to sensitivity, specificity, and the sample sizes of MPE and BPE. The table has the numbers of true positive (TP), false positive (FP), false negative (FN), and true negative (TN) patients.

The revised Quality Assessment for Diagnostic Accuracy Studies tool (QUADAS-2), which the Cochrane group recommends, assessed the quality of eligible studies (27).

Statistical analysis

We used a bivariate model to pool the combined sensitivities and specificities of pleural fluid CEA, serum CEA, and CR (28). The diagnostic odds ratios (DORs), positive likelihood ratios (PLRs), and negative likelihood ratios (NLRs) were calculated with the pooled sensitivity and specificity. A summary receiver operating characteristic (sROC) curve was constructed to determine the diagnostic accuracy of serum CEA, pleural fluid CEA, and CR. The AUC of sROC was used to measure the overall diagnostic performance (29). The inconsistency index (I²) was used to assess the heterogeneity across eligible studies (30). The positive predictive value (PPV) and negative predictive value (NPV) at different prevalences were calculated using a Fagan plot. The Deeks’ test and funnel plot were used to estimate the degree of publication bias (31). All statistical analyses were performed using Stata 16.0 (Stata Corp LP, College Station, TX, USA).

Results

Characteristics of the included studies

Figure 1 is a flowchart of the study screening process. Finally, seven studies met the inclusion criteria for analysis. A total of 1,964 patients were included, including 1,148 MPEs and 816 BPEs. The characteristics of these studies are shown in Table 1. Among the included studies, five were from China (22,32-35), and the other two were from Croatia (23) and Poland (36). Three were prospective (23,33,36), two were retrospective (22,34), one had both prospective and retrospective cohorts (32), and another one did not report the study type (35). Six used electrochemical analysis to detect pleural fluid CEA (22,23,32,33,35,36), and one used Luminex (34).

Figure 1 A flowchart for the study selection.

Quality assessment

The quality assessment of the included studies is shown in Table 2. Four studies had a high-risk-in-patient selection (22,33-35). The MPE group in three of them was only composed of lung cancer (33-35), and the BPE group in one of them only included tuberculous pleural effusion (TPE) (22). Six studies did not use a prespecified CEA threshold (22,23,33-36), and the index test domains of these studies were labeled high risk. One study did not include all participants in the final data analysis, and its flow and timing domain was labeled high (32).

Diagnostic accuracy of CEA for MPE

Table 3 summarizes the sensitivities, specificities, and AUCs of pleural fluid CEA, serum CEA, and CR. The AUCs of pleural fluid CEA ranged from 0.75 to 0.98, and those of serum CEA ranged from 0.61 to 0.90. CR had AUCs ranging from 0.79 to 0.90. Figures 2-4 show the forest plots of sensitivity and specificity for pleural fluid CEA, serum CEA, and CR for diagnosing MPE. The results of the meta-analysis are summarized in Table 4. The pooled sensitivities [95% confidence intervals (CIs)] of pleural fluid CEA, serum CEA, and CR were 0.82 (0.68–0.91), 0.64 (0.51–0.76), and 0.80 (0.69–0.88), respectively. The pooled specificities (95% CIs) were 0.92 (0.88–0.95), 0.86 (0.78–0.91), and 0.86 (0.78–0.92), respectively. The sROC curves of pleural fluid CEA, serum CEA, and CR are shown in Figure 5. The AUCs (95% CIs) of pleural fluid CEA, serum CEA, and CR were 0.95 (0.93–0.96), 0.84 (0.81–0.87), and 0.90 (0.87–0.93), respectively.

Figure 2 Forest plots depicting the sensitivity and specificity of pleural CEA for MPE. CEA, carcinoembryonic antigen; CI, confidence interval; MPE, malignant pleural effusion.

Figure 3 Forest plots depicting the sensitivity and specificity of serum CEA for MPE. CEA, carcinoembryonic antigen; CI, confidence interval; MPE, malignant pleural effusion.

Figure 4 Forest plots depicting the sensitivity and specificity of CR for MPE. CEA, carcinoembryonic antigen; CI, confidence interval; CR, pleural fluid to serum CEA ratio; MPE, malignant pleural effusion.

Figure 5 The sROC curves of CEA. AUC, area under the curve; CEA, carcinoembryonic antigen; CR, pleural fluid to serum CEA ratio; SENS, sensitivity; SPEC, specificity; sROC, summary receiver operating characteristic.

The Fagan plots of pleural fluid CEA, serum CEA, and CR are shown in Figure 6. Assuming the prevalence of MPE was 50% in the target population, the PPVs for pleural fluid CEA were 92%, 82%, and 85%, respectively. The corresponding NPVs were 16%, 29%, and 19%, respectively.

Figure 6 Fagan diagrams depicting the predictive values of pleural fluid CEA, serum CEA, and CR for MPE. CEA, carcinoembryonic antigen; CR, pleural fluid to serum CEA ratio; LR, likelihood ratio; MPE, malignant pleural effusion.

Publication bias

Figure 7 shows no significant publication bias was observed for pleural fluid CEA and CR (P=0.45, P=0.11), while serum CEA had significant publication bias (P=0.02).

Figure 7 The funnel plots assess the potential publication bias. CEA, carcinoembryonic antigen; CR, pleural fluid to serum CEA ratio.

Discussion

Many studies have evaluated the diagnostic value of pleural fluid, serum CEA and CR for MPE. Still, no meta-analysis has been conducted to compare their diagnostic value head-to-head. To our knowledge, this is the first systematic review and meta-analysis comparing the diagnostic value of pleural effusion, serum CEA, and CR for MPE with a head-to-head comparison design. Seven studies with 1,964 patients were included, and the main findings were: first, the AUC, pooled sensitivity, and specificity of pleural fluid CEA were higher than those of serum CEA and CR, indicating that the diagnostic accuracy of pleural effusion CEA for MPE was higher than that of serum and CR. Second, pleural fluid CEA and CR had no publication bias. In contrast, serum CEA had, indicating that the diagnostic value of serum CEA may have been overestimated across studies comparing the diagnostic accuracy of serum CEA and pleural fluid CEA in a head-to-head manner. Taken together, these findings do not support the simultaneous testing of pleural fluid and serum CEA for diagnosing MPE.

Sensitivity and specificity are basic metrics of a diagnostic test. They reflect the abilities of a diagnostic test to confirm or exclude target diseases. However, they have the disadvantage of being threshold-dependent. A higher CEA threshold yields higher specificity but with lower sensitivity, and vice versa (37-39). We found that the threshold used for pleural fluid CEA in all eligible studies ranged between 2.2 and 5.0 ng/mL. We thus conclude that pleural CEA has a sensitivity of 0.82 and specificity of 0.92 at the threshold of around 4 ng/mL. A higher threshold may decrease the sensitivity and increase the specificity.

In contrast to sensitivity and specificity, the AUC of sROC is a global indicator for evaluating the accuracy of diagnostic tests because it is not affected by the threshold used (40). We found that the AUC of pleural fluid CEA was higher than that of serum CEA and CR, and there was no overlap between the 95% confidence intervals, indicating that the overall diagnostic value of pleural fluid CEA is superior to that of serum CEA and CR. In other words, serum CEA testing does not provide added diagnostic value when combined with pleural fluid CEA. Therefore, serum CEA detection should not be advocated. DOR combines the advantages of sensitivity and specificity, thus representing a global diagnostic test measure (41). DOR ranges from 0 to infinity, with a higher value indicating superior diagnostic accuracy of the biomarkers (41). Our study found that the DORs [95% CIs] of pleural fluid CEA, serum CEA, and CR were 56 [29–106], 11 [7–16], and 25 [16–41], respectively. The DOR of pleural fluid CEA was 56, indicating that the probability of positive CEA in MPE is 56 times higher than in BPE. The DOR of pleural CEA was higher than that of CR and serum CEA, indicating the overall diagnostic value of pleural effusion CEA is higher than that of serum CEA and CR.

PLR and NLR are indicators that diagnose or exclude the target disease (42). It is well recognized that PLR >10 and NLR <0.1 are strong evidence to confirm and exclude the target disease (42,43). Our study found that the PLR and NLR for pleural fluid CEA were 11 (95% CI: 7–17) and 0.19 (95% CI: 0.11–0.35), respectively. Meanwhile, serum CEA and CR had PLRs of 5 (95% CI: 3–6) and 6 (95% CI: 4–9) and NLRs of 0.42 (95% CI: 0.31–0.56) and 0.23 (95% CI: 0.15–0.35). Therefore, patients with positive pleural fluid CEA have a high risk of MPE. Considering the outcomes of the misdiagnosis of MPE are devasting, we believe that CEA cannot be used to confirm MPE when used alone. It is worth noting that the many included studies set the diagnostic threshold of CEA at around 5 ng/mL, a specificity of >90%, and a PLR of 11 was obtained. If the diagnostic threshold of CEA is increased, the specificity and PLR could be improved. Several studies have found 100% specificity for MPE in non-purulent pleural fluid specimens with CEA >50 ng/mL (32,34,44). Therefore, we propose that CEA above 5 ng/mL is inadequate to diagnose MPE, although the likelihood of MPE is very high. Based on the findings of previous studies, we concluded MPE can be diagnosed in non-purulent pleural fluid specimens when CEA >50 ng/mL (18). By contrast, the NLR of pleural fluid CEA was 19%. These findings also support our conclusion that CEA cannot be used to exclude MPE when used alone. In parallel, serum CEA and CR cannot be used to verify or exclude MPE.

We used the QUADAS-2 tool to assess the quality of the included studies (27). We found some design limitations in previous studies. Some studies did not avoid inappropriate exclusions, which may impair the representativeness of subjects. For example, a study excluded patients with renal insufficiency, diabetes, and liver cirrhosis (33), and these patients are also at risk for pleural effusion. In addition, the BPE patients in a study only included TPE (22). Notably, many studies used a data-driven threshold, which may overestimate the diagnostic accuracy of CEA (45).

Although this is the first meta-analysis to compare pleural fluid and serum CEA for diagnosing MPE head-to-head, there are some limitations in this study. First, the number of included studies and the total sample size were small, and the precision of the pooled metrics needs to be further improved. Second, some of the included studies had study design weaknesses, which may affect the reliability of our meta-analysis. For example, some included studies only enrolled lung cancer patients in the MPE group, and some were retrospective designs. These design weaknesses make the studied cohorts lack representativeness and may introduce bias. Some included studies did not use the prespecified CEA threshold to calculate sensitivity and specificity. Instead, they used a data-driven selection of thresholds. This strategy may overestimate the diagnostic accuracy of CEA (45). Third, two CEA assays were used in eligible studies, but the agreement between these two assays remains unknown. Fourth, the disease spectrum of participants, particularly the composition of MPE, varied across included studies, making the findings of our study not easy to interpret. Fifth, most of the included studies were from China and Eastern Europe, and the generalization of our findings needs to be validated by studies from other regions. Finally, some included studies were not reported according to the Standards for Reporting of Diagnostic Accuracy Studies (STARD) guidelines, making us unable to assess the quality of these studies.

Conclusions

Our meta-analysis revealed that the diagnostic value of pleural fluid CEA was superior to serum CEA and CR. Therefore, serum CEA determination should not be advocated. Considering the limitations of this meta-analysis, it remains necessary to perform large sample size studies to compare the diagnostic accuracy of pleural fluid and serum CEA for MPE in the future.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA-DTA reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2152/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2152/prf

Funding: This work was supported by the Program for Young Talents of Science and Technology in the Universities of Inner Mongolia Autonomous Region (No. NJYT22018).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2152/coif). The authors have no 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.

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. Jany B, Welte T. Pleural Effusion in Adults-Etiology, Diagnosis, and Treatment. Dtsch Arztebl Int 2019;116:377-86. [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. Psallidas I, Kalomenidis I, Porcel JM, et al. Malignant pleural effusion: from bench to bedside. Eur Respir Rev 2016;25:189-98. [Crossref] [PubMed]
4. Bielsa S, Salud A, Martínez M, et al. Prognostic significance of pleural fluid data in patients with malignant effusion. Eur J Intern Med 2008;19:334-9. [Crossref] [PubMed]
5. Gayen S. Malignant Pleural Effusion: Presentation, Diagnosis, and Management. Am J Med 2022;135:1188-92. [Crossref] [PubMed]
6. Tian P, Qiu R, Wang M, et al. Prevalence, Causes, and Health Care Burden of Pleural Effusions Among Hospitalized Adults in China. JAMA Netw Open 2021;4:e2120306. [Crossref] [PubMed]
7. Botana Rial M, Pérez Pallarés J, Cases Viedma E, et al. Diagnosis and Treatment of Pleural Effusion. Recommendations of the Spanish Society of Pulmonology and Thoracic Surgery. Update 2022. Arch Bronconeumol 2023;59:27-35. [Crossref] [PubMed]
8. Asciak R, Rahman NM. Malignant Pleural Effusion: From Diagnostics to Therapeutics. Clin Chest Med 2018;39:181-93. [Crossref] [PubMed]
9. 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]
10. Liu XT, Dong XL, Zhang Y, et al. Diagnostic value and safety of medical thoracoscopy for pleural effusion of different causes. World J Clin Cases 2022;10:3088-100. [Crossref] [PubMed]
11. Colt HG. Thoracoscopy: window to the pleural space. Chest 1999;116:1409-15. [Crossref] [PubMed]
12. Wan YY, Zhai CC, Lin XS, et al. Safety and complications of medical thoracoscopy in the management of pleural diseases. BMC Pulm Med 2019;19:125. [Crossref] [PubMed]
13. Martinez-Zayas G, Molina S, Ost DE. Sensitivity and complications of thoracentesis and thoracoscopy: a meta-analysis. Eur Respir Rev 2022;31:220053. [Crossref] [PubMed]
14. Gardiner A, Ling R, Chan YH, et al. DUETS for Light’s in separating exudate from transudate. Respirology 2024;29:976-84. [Crossref] [PubMed]
15. Fjaellegaard K, Koefod Petersen J, Reuter S, et al. Positron emission tomography-computed tomography (PET-CT) in suspected malignant pleural effusion. An updated systematic review and meta-analysis. Lung Cancer 2021;162:106-18. [Crossref] [PubMed]
16. Zheng WQ, Hu ZD. Pleural fluid biochemical analysis: the past, present and future. Clin Chem Lab Med 2023;61:921-34. [Crossref] [PubMed]
17. 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]
18. Zheng WQ, Porcel JM, Hu ZD. Tumor markers determination in malignant pleural effusion: pearls and pitfalls. Clin Chem Lab Med 2025;63:515-20. [Crossref] [PubMed]
19. Radjenovic-Petkovic T, Pejcic T, Nastasijević-Borovac D, et al. Diagnostic value of CEA in pleural fluid for differential diagnosis of benign and malign pleural effusion. Med Arh 2009;63:141-2.
20. 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]
21. 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]
22. 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]
23. Volarić D, Flego V, Žauhar G, et al. Diagnostic value of tumour markers in pleural effusions. Biochem Med (Zagreb) 2018;28:010706. [Crossref] [PubMed]
24. Hackner K, Errhalt P, Handzhiev S. Ratio of carcinoembryonic antigen in pleural fluid and serum for the diagnosis of malignant pleural effusion. Ther Adv Med Oncol 2019;11:1758835919850341. [Crossref] [PubMed]
25. Trapé J, Sant F, Franquesa J, et al. Evaluation of two strategies for the interpretation of tumour markers in pleural effusions. Respir Res 2017;18:103. [Crossref] [PubMed]
26. McInnes MDF, Moher D, Thombs BD, et al. Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement. JAMA 2018;319:388-96. [Crossref] [PubMed]
27. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011;155:529-36. [Crossref] [PubMed]
28. Reitsma JB, Glas AS, Rutjes AW, et al. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 2005;58:982-90. [Crossref] [PubMed]
29. Walter SD. Properties of the summary receiver operating characteristic (SROC) curve for diagnostic test data. Stat Med 2002;21:1237-56. [Crossref] [PubMed]
30. Higgins JP, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta-analyses. BMJ 2003;327:557-60. [Crossref] [PubMed]
31. Deeks JJ, Macaskill P, Irwig L. The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol 2005;58:882-93. [Crossref] [PubMed]
32. Jiang MP, Wen JX, Hai L, et al. Diagnostic accuracy of pleural fluid to serum carcinoembryonic antigen ratio and delta value for malignant pleural effusion: findings from two cohorts. Ther Adv Respir Dis 2023;17:17534666231155745. [Crossref] [PubMed]
33. Tu Y, Wu Y, Lu Y, et al. Development of risk prediction models for lung cancer based on tumor markers and radiological signs. J Clin Lab Anal 2021;35:e23682. [Crossref] [PubMed]
34. 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]
35. Zhai K, Wang W, Wang Y, et al. Diagnostic accuracy of tumor markers for malignant pleural effusion: a derivation and validation study. J Thorac Dis 2017;9:5220-9. [Crossref] [PubMed]
36. 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]
37. Dickie GL. Statistical notes. Defining sensitivity and specificity. BMJ 1994;309:539. [Crossref] [PubMed]
38. Linnet K, Bossuyt PM, Moons KG, et al. Quantifying the Accuracy of a Diagnostic Test or Marker. Clinical Chemistry 2012;58:1292-301. [Crossref] [PubMed]
39. Monaghan TF, Rahman SN, Agudelo CW, et al. Foundational Statistical Principles in Medical Research: Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value. Medicina (Kaunas) 2021;57:503. [Crossref] [PubMed]
40. Reitsma JB, Moons KG, Bossuyt PM, et al. Systematic reviews of studies quantifying the accuracy of diagnostic tests and markers. Clin Chem 2012;58:1534-45. [Crossref] [PubMed]
41. Glas AS, Lijmer JG, Prins MH, et al. The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol 2003;56:1129-35. [Crossref] [PubMed]
42. Akobeng AK. Understanding diagnostic tests 2: likelihood ratios, pre- and post-test probabilities and their use in clinical practice. Acta Paediatr 2007;96:487-91. [Crossref] [PubMed]
43. Deeks JJ, Altman DG. Diagnostic tests 4: likelihood ratios. BMJ 2004;329:168-9. [Crossref] [PubMed]
44. Porcel JM, Civit C, Esquerda A, et al. Utility of CEA and CA 15-3 measurements in non-purulent pleural exudates in the diagnosis of malignancy: A single-center experience. Arch Bronconeumol 2017;53:427-31. [Crossref] [PubMed]
45. Leeflang MM, Moons KG, Reitsma JB, et al. Bias in sensitivity and specificity caused by data-driven selection of optimal cutoff values: mechanisms, magnitude, and solutions. Clin Chem 2008;54:729-37. [Crossref] [PubMed]