Ratio of carcinoembryonic antigen in pleural fluid and serum for the diagnosis of malignant pleural effusion

Diagnostic algorithm based on ratio of ascites-serum tumor markers is superior to tumor markers in the differentiation of benign ascites from malignant ascites

BACKGROUND

Differential diagnosis between benign ascites and malignant ascites remains challenging in clinical practice, the aim of our study is to determine the differential value of the ratio of ascitic-serum tumor markers between benign ascites and malignant ascites.

METHODS

418 patients with new-onset ascites were retrospectively enrolled in this study. The pertinent data of patients enrolled were collected; diagnostic value of tumor markers, ascites-serum tumor marker ratio, and diagnostic algorithm based on ascitic tumor markers and ascites-serum tumor marker ratio in patients with ascites were investigated.

RESULTS

81.25% of the patients with benign ascites had low (<1) ratio of ascites-serum tumor markers (Max [A/S CEA, A/S CA15-3, A/S CA19-9]); and 91.88% of patients with benign ascites had the ratio of ascites-serum tumor marker less than 1.5. On the other hand, 94.96% of the patients with malignant ascites had high (≥1) ratio of ascites-serum tumor markers; and 97.29% of patients with malignant ascites had the ratio of ascites-serum tumor markers more than 0.67. Finally, diagnostic algorithm based on ascitic tumor markers and ascites-serum tumor marker ratio showed 96.37% of the sensitivity, and 94.37% of the accuracy in the diagnosis of malignant ascites, while ascitic tumor markers with a sensitivity of 78.29%, and an accuracy of 84.93%.

CONCLUSIONS

Diagnostic algorithm based on ascitic tumor markers and ascites-serum tumor marker ratio exhibited an excellent performance in distinguishing benign and malignant ascites, which should be recommended in patients with new-onset ascites in clinical practice.

Tumor markers determination in malignant pleural effusion: pearls and pitfalls

Serum and pleural fluid tumor markers are well-recognized auxiliary diagnostic tools for malignant pleural effusion (MPE). Here, we discuss some pearls and pitfalls regarding the role of tumor markers in MPE management. The following issues are discussed in this article: What is the appropriate clinical scenario for evaluating pleural tumor markers? Which tumor markers should be advocated for diagnosing MPE? Can extremely high levels of tumor markers be employed to establish a diagnosis of MPE? Does the serum-to-pleural fluid ratio of a tumor marker have the same diagnostic efficacy as the measurement of that marker alone in the pleural fluid? Can tumor markers be used to estimate the risk of specific cancers? What should be considered when interpreting the diagnostic accuracy of tumor markers? How should tumor marker studies be performed? We addressed these issues with published works, particularly systematic reviews and meta-analyses.

A simple and efficient clinical prediction scoring system to identify malignant pleural effusion

BACKGROUND

Early diagnosis of malignant pleural effusion (MPE) is of great significance. Current prediction models are not simple enough to be widely used in heavy clinical work.

OBJECTIVES

We aimed to develop a simple and efficient clinical prediction scoring system to distinguish MPE from benign pleural effusion (BPE).

DESIGN

This retrospective study involved patients with MPE or BPE who were admitted in West China Hospital from December 2010 to September 2016.

METHODS

Patients were divided into training, testing, and validation set. Prediction model was developed from training set and modified to a scoring system. The diagnostic efficacy and clinical benefits of the scoring system were estimated in all three sets.

RESULTS

Finally, 598 cases of MPE and 1094 cases of BPE were included. Serum neuron-specific enolase, serum cytokeratin 19 fragment (CYFRA21-1), pleural carcinoembryonic antigen (CEA), and ratio of pleural CEA to serum CEA were selected to establish the prediction models in training set, which were modified to the scoring system with scores of 6, 8, 10, and 9 points, respectively. Patients with scores >12 points have high MPE risk while ⩽12 points have low MPE risk. The scoring system has a high predictive value and good clinical benefits to differentiate MPE from BPE or lung-specific MPE from BPE.

CONCLUSION

This study developed a simple clinical prediction scoring system and was proven to have good clinical benefits, and it may help clinicians to separate MPE from BPE.

LDH/ADA ratio in pleural fluid for the diagnosis of infectious pleurisy

Pleural effusion (PE) is a common medical concern, often requiring thoracentesis for a definitive diagnosis. An elevated pleural fluid adenosine deaminase (ADA) may indicate tuberculosis, but this is not always the case. This study aimed to evaluate the accuracy of biomarkers determined in pleural fluid and propose a new diagnostic strategy for PE in patients with high levels of ADA in pleural fluid. This retrospective analysis studied patients with PE who received thoracentesis for the first time with an ADA level of > 33 U/L in the pleural fluid analysis at two tertiary hospitals from March 2019 to March 2023. Demographic and clinical data, as well as pleural fluid biomarkers and their ratios, were studied and compared between different PE groups, and a decision tree was developed. During the study period, 259 patients were enrolled, with four different types of PE: parapneumonic (PPE) 155, tuberculosis (TPE) 41, malignant (MPE) 50, and miscellaneous 13. Biomarkers and their ratios performed well in the differential diagnosis of PE, with the LDH/ADA ratio distinguishing between PPE and non-PPE with sensitivity and specificity of 98.06% and 98.08%, respectively. The combination of LDH/ADA ratio, ADA, and mononuclear cell percentage was identified as important factors for creating a decision tree with an overall accuracy of 89.96%. The pleural fluid LDH/ADA ratio was a useful diagnostic for distinguishing PPE from non-PPE, and a decision tree with an accuracy of 89.96% was created to differentiate the four forms of PE in clinical situations.

Novel clinical radiomic nomogram method for differentiating malignant from non-malignant pleural effusions

Objectives

To establish a clinical radiomics nomogram that differentiates malignant and non-malignant pleural effusions.

Methods

A total of 146 patients with malignant pleural effusion (MPE) and 93 patients with non-MPE (NMPE) were included. The ROI image features of chest lesions were extracted using CT. Univariate analysis was performed, and least absolute shrinkage selection operator and multivariate logistic analysis were used to screen radiomics features and calculate the radiomics score. A nomogram was constructed by combining clinical factors with radiomics scores. ROC curve and decision curve analysis (DCA) were used to evaluate the prediction effect.

Results

After screening, 19 radiomics features and 2 clinical factors were selected as optimal predictors to establish a combined model and construct a nomogram. The AUC of the combined model was 0.968 (95% confidence interval [CI] = 0.944-0.986) in the training cohort and 0.873 (95% CI = 0.796-0.940) in the validation cohort. The AUC value of the combined model was significantly higher than those of the clinical and radiomics models (0.968 vs. 0.874 vs. 0.878, respectively). This was similar in the validation cohort (0.873, 0.764, and 0.808, respectively). DCA confirmed the clinical utility of the radiomics nomogram.

Conclusion

CT-based radiomics showed better diagnostic accuracy and model fit than clinical and radiological features in distinguishing MPE from NMPE. The combination of both achieved better diagnostic performance. These findings support the clinical application of the nomogram in diagnosing MPE using chest CT.

Pleural CEA, CA-15-3, CYFRA 21-1, CA-19-9, CA-125 discriminating malignant from benign pleural effusions: Diagnostic cancer biomarkers

INTRODUCTION

There is a need for a rapid, accurate, less-invasive approach to distinguishing malignant from benign pleural effusions. We investigated the diagnostic value of five pleural tumor markers in exudative pleural effusions.

METHODS

By immunochemiluminescence assay, we measured pleural concentrations of tumor markers. We used the receiver operating characteristic curve analysis to assess their diagnostic values.

RESULTS

A total of 281 patients were enrolled. All tumor markers were significantly higher in malignant pleural effusions than benign ones. The area under the curve of carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 15-3, cytokeratin fragment 19 (CYFRA) 21-1, CA-19-9, and CA-125 were 0.81, 0.78, 0.75, 0.65, and 0.65, respectively. Combined markers of CEA + CA-15-3 and CEA + CA-15-3 + CYFRA 21-1 had a sensitivity of 87% and 94%, and specificity of 75% and 58%, respectively. We designed a diagnostic algorithm by combining pleural cytology with pleural tumor marker assay. CEA + CYFRA 21-1 + CA-19-9 + CA-15-3 was the best tumor markers panel detecting 96% of cytologically negative malignant pleural effusions, with a negative predictive value of 98%.

CONCLUSIONS

Although cytology is specific enough, it has less sensitivity in identifying malignant pleural fluids. As a result, the main gap is detecting malignant pleural effusions with negative cytology. CEA was the best single marker, followed by CA-15-3 and CYFRA 21-1. Through both cytology and suggested panels of tumor markers, malignant and benign pleural effusions could be truly diagnosed with an accuracy of about 98% without the need for more invasive procedures, except for the cohort with negative cytology and a positive tumor markers panel, which require more investigations.

Diagnosis of malignant pleural effusion with combinations of multiple tumor markers: A comparison study of five machine learning models

BACKGROUND

To evaluate the diagnostic value of combinations of tumor markers carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 125, CA153, and CA19-9 in identifying malignant pleural effusion (MPE) from non-malignant pleural effusion (non-MPE) using machine learning, and compare the performance of popular machine learning methods.

METHODS

A total of 319 samples were collected from patients with pleural effusion in Beijing and Wuhan, China, from January 2018 to June 2020. Five machine learning methods including Logistic regression, extreme gradient boosting (XGBoost), Bayesian additive regression tree, random forest, and support vector machine were applied to evaluate the diagnostic performance. Sensitivity, specificity, Youden's index, and the area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of different diagnostic models.

RESULTS

For diagnostic models with a single tumor marker, the model using CEA, constructed by XGBoost, performed best (AUC = 0.895, sensitivity = 0.80), and the model with CA153, also by XGBoost, showed the largest specificity 0.98. Among all combinations of tumor markers, the combination of CEA and CA153 achieved the best performance (AUC = 0.921, sensitivity = 0.85) in identifying MPE under the diagnostic model constructed by XGBoost.

CONCLUSIONS

Diagnostic models for MPE with a combination of multiple tumor markers outperformed the models with a single tumor marker, particularly in sensitivity. Using machine learning methods, especially XGBoost, could comprehensively improve the diagnostic accuracy of MPE.

Development and validation of a machine learning model for differential diagnosis of malignant pleural effusion using routine laboratory data

BACKGROUND

The differential diagnosis of malignant pleural effusion (MPE) and benign pleural effusion (BPE) presents a clinical challenge. In recent years, the use of artificial intelligence (AI) machine learning models for disease diagnosis has increased.

OBJECTIVE

This study aimed to develop and validate a diagnostic model for early differentiation between MPE and BPE based on routine laboratory data.

DESIGN

This was a retrospective observational cohort study.

METHODS

A total of 2352 newly diagnosed patients with pleural effusion (PE), between January 2008 and March 2021, were eventually enrolled. Among them, 1435, 466, and 451 participants were randomly assigned to the training, validation, and testing cohorts in a ratio of 3:1:1. Clinical parameters, including age, sex, and laboratory parameters of PE patients, were abstracted for analysis. Based on 81 candidate laboratory variables, five machine learning models, namely extreme gradient boosting (XGBoost) model, logistic regression (LR) model, random forest (RF) model, support vector machine (SVM) model, and multilayer perceptron (MLP) model were developed. Their respective diagnostic performances for MPE were evaluated by receiver operating characteristic (ROC) curves.

RESULTS

Among the five models, the XGBoost model exhibited the best diagnostic performance for MPE (area under the curve (AUC): 0.903, 0.918, and 0.886 in the training, validation, and testing cohorts, respectively). Additionally, the XGBoost model outperformed carcinoembryonic antigen (CEA) levels in pleural fluid (PF), serum, and the PF/serum ratio (AUC: 0.726, 0.699, and 0.692 in the training cohort; 0.763, 0.695, and 0.731 in the validation cohort; and 0.722, 0.729, and 0.693 in the testing cohort, respectively). Furthermore, compared with CEA, the XGBoost model demonstrated greater diagnostic power and sensitivity in diagnosing lung cancer-induced MPE.

CONCLUSION

The development of a machine learning model utilizing routine laboratory biomarkers significantly enhances the diagnostic capability for distinguishing between MPE and BPE. The XGBoost model emerges as a valuable tool for the diagnosis of MPE.

Diagnostic accuracy of pleural fluid to serum carcinoembryonic antigen ratio and delta value for malignant pleural effusion: findings from two cohorts

BACKGROUND

Pleural fluid (PF) carcinoembryonic antigen (CEA) is a widely used diagnostic marker for malignant pleural effusion (MPE). Recent studies revealed that PF to serum CEA was also a promising diagnostic parameter for MPE.

OBJECTIVE

We aimed to investigate whether PF to serum CEA ratio and delta CEA (PF minus serum CEA) provided added value to PF CEA in diagnosing MPE.

METHODS

Patients with pleural effusion in a retrospective cohort (BUFF) and a prospective cohort (SIMPLE) were included. The clinical characteristics of the patients were extracted from their medical records. The diagnostic value of CEA ratio and delta CEA was estimated by a receiver operating characteristics (ROC) curve, net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

RESULTS

A total of 148 patients in the BUFF cohort and 164 patients in the SIMPLE cohort were enrolled. The BUFF cohort had 46 MPE patients and 102 benign pleural effusion (BPE) patients, and the SIMPLE cohort had 85 MPE patients and 79 BPE patients. In both cohorts, MPE patients had significantly higher PF CEA, serum CEA, CEA ratio, and delta CEA. The area under ROC curves (AUCs) of PF CEA, CEA ratio, and delta CEA were 0.78 (95% CI: 0.67-0.88), 0.80 (95% CI: 0.72-0.89) and 0.83 (95% CI: 0.75-0.91) in the BUFF cohort, and 0.89 (95% CI: 0.83-0.94), 0.86 (95% CI: 0.80-0.92), and 0.84 (95% CI: 0.78-0.91) in the SIMPLE cohort. The differences between the AUCs of PF CEA, CEA ratio, and delta CEA did not reach statistical significance. The continuous NRI and IDI of CEA ratio and delta CEA were <0.

CONCLUSION

CEA ratio and delta value cannot provide added diagnostic value to PF CEA. The simultaneous determination of serum and PF CEA should not be adopted in clinical practice.

New biomarkers for the diagnosis of pleural effusion

Background

Persistent undiagnosed effusion is present in approximately 15% of all causes of exudative effusion. Pleural effusion caused by immunoglobulin G4 (IgG4) is a new type of pleural effusion. Tumor markers such as Carcinoembryonic antigen (CEA) may play a role in the diagnosis of malignant pleural effusion. This study aimed to evaluate the use of serum Immunoglobulin G4 and carcinoembryonic antigen in diagnosing pleural effusion.

Methods

This observational descriptive cross-sectional study comprised 89 individuals with exudative pleural effusion who visited the Assiut university hospital's chest department. All patients were examined and asked about their medical history. Also, chest X-ray, MSCT chest, transthoracic ultrasonography, pleural fluid analysis and cytology, serum level of carcinoembryonic antigen, and immunoglobulin G4 were performed. In addition, pleural biopsy, bronchoscopy, and thoracoscopy were performed when required.

Results

In comparison to another diagnosis, the level of serum IgG 4 was observed to be substantially greater in individuals with IgG4-associated effusion (725± 225.45). Patients with malignant mesothelioma (70± 16.24) and metastatic adenocarcinoma (93.52± 19.34) had lower levels of IgG4. In contrast, the serum level of CEA was significantly higher in individuals with malignant mesothelioma (79.50± 29.47) and metastatic adenocarcinoma (68.71± 28.98). Patients with para-pneumonic effusion had a minor serum level of CEA (0.36 ± 0.26). At cutoff point > 152 mg/dl serum IgG-4 had 100% sensitivity and 94% specificity in the diagnosis of IgG4 related pleural effusion with an overall accuracy of 95.3% and area under the curve of 0.97. At the cutoff point > 5 ng/ml serum CEA had 77% sensitivity and 100% specificity in diagnosing malignant pleural effusion with an overall accuracy of 91.1% and area under the curve of 0.88.

Conclusion

Serum IgG4 higher than 152 mg/dl has good diagnostic accuracy in cases of undiagnosed pleural effusion. Carcinoembryonic antigen aids in diagnosing malignant pleural effusion with a cutoff point higher than 5 ng/ml in serum.

Trial registration

ClinicalTrials.gov registration ID NCT03260088

Evaluation of serum and pleural levels tumor M2-pyruvate kinase in lung cancer patients with pleural effusion

Objective

To evaluate the diagnostic value of tumor M2-pyruvate kinase (TuM2-PK) and carcinoembryonic antigen (CEA) levels in both pleural effusion and serum in the differential diagnosis of benign and malignant pleural effusion.

Methods

This prospective study was conducted among 80 patients with benign pleural effusion (BPE group) and 125 patients with malignant pleural effusion associated with lung cancer (MPE group). The levels of TuM2-PK and CEA were measured by using sandwich enzyme-linked immunosorbent assay and electrochemiluminescence. The receiver-operating characteristic curve (ROC) analysis was used to confirm the cutoff value to evaluate the diagnostic efficiency of TuM2-PK and CEA.

Results

The TuM2-PK and CEA levels in pleural effusion and serum, and their ratio (P/S) were higher in MPE group than that in BPE group (P < 0.05). In pleural effusion and serum, the diagnostic efficiency of combined TuM2-PK and CEA for MPE was superior to either single detection.

Conclusions

The combined detection of TuM2-PK and CEA has a high sensitivity for diagnosis of MPE and might provide method for rapid and accurate diagnosis of patients.

Discrimination of Malignant Pleural Mesothelioma Cell Lines Using Amino Acid Metabolomics with HPLC

Malignant pleural mesothelioma (MPM) is a malignancy closely associated with asbestos exposure. Although early diagnosis provides a chance of effective treatment and better prognosis, invasive biopsy and cytological procedure are required for definitive diagnosis. In this study, we developed a method to differentiate between MPM and control cell lines, named "amino acid metabolomics," consisting in the assessment of the balance of their amino acid levels in the cell culture medium. Culture media of MESO-1 (MPM cell line) and Met-5A (control) cells were used in this study to evaluate amino acid levels using HPLC, following the fluorescence derivatization method. The time-dependent changes in amino acid levels were visualized on the score plot following principal component analysis, and the results revealed differential changes in amino acid levels between the two cell culture supernatants. A discriminative model based on linear discriminant analysis could distinguish MPM and control cells.

Diagnostic value of periostin in lung cancer-related malignant pleural effusion

BACKGROUND

Periostin (POSTN) is an extracellular matrix protein that is overexpressed in lung cancer and is considered an effective diagnostic and prognostic biomarker for lung cancer. The purpose of this study was to investigate the diagnostic performance of POSTN and to further evaluate the diagnostic value of POSTN combined with carcinoembryonic antigen (CEA) and cancer ratio [CR: serum lactate dehydrogenase (LDH)/pleural effusion adenosine deaminase (PE ADA)] in lung cancer-related malignant PE (MPE).

METHODS

A total of 108 patients with PE, including 54 with lung cancer and 54 with benign lung disease, were enrolled in this study. The POSTN levels of PE and serum were detected using an enzyme-linked immunosorbent assay. Information on the expression of PE and serum CEA, serum LDH, and PE ADA was collected from medical records.

RESULTS

The levels of PE POSTN in MPE of patients with lung cancer were significantly higher than those in patients with benign PE (p < 0.0001). The receiver operating characteristic (ROC) curve indicated that the diagnostic sensitivity and specificity of PE POSTN for lung cancer-related MPE were respectively 77.78% and 68.52% when the cutoff value was determined to be 53.45 ng/ml. The ROC curve analysis demonstrated that PE POSTN has a high diagnostic value in MPE associated with lung cancer [area under the curve (AUC) = 0.764], and the combination of PE POSTN, PE CEA, and CR can improve the diagnostic accuracy of lung cancer-related MPE (AUC = 0.948).

CONCLUSION

POSTN can be used as a potential marker for lung cancer-related MPE diagnosis.

Laboratory and radiological discrimination between tuberculous and malignant pleural effusions with high adenosine deaminase levels

BACKGROUND/AIMS

Pleural fluid adenosine deaminase (ADA) levels are useful in discriminating tuberculous pleural effusions (TPEs) from malignant pleural effusions (MPEs). However, some patients with MPE exhibit high-ADA levels, which may mimic TPEs. There is limited data regarding the differential diagnosis between high-ADA MPE and high-ADA TPE. This study aimed to identify the predictors for distinguishing high-ADA MPEs from high-ADA TPEs.

METHODS

Patients with TPE and MPE with pleural fluid ADA levels ≥ 40 IU/L were included in this study. Clinical, laboratory, and radiological data were compared between the two groups. Independent predictors and their diagnostic performance for high-ADA MPEs were evaluated using multivariate logistic regression analysis and receiver operating characteristic curve.

RESULTS

A total of 200 patients (high-ADA MPE, n = 30, and high-ADA TPE, n = 170) were retrospectively included. In the multivariate analysis, pleural fluid ADA, pleural fluid carcinoembryonic antigen (CEA), and pleural nodularity were independent discriminators between high-ADA MPE and high-ADA TPE groups. Using pleural ADA level of 40 to 56 IU/L (3 points), pleural CEA level ≥ 6 ng/mL (6 points), and presence of pleural nodularity (3 points) for predicting high-ADA MPEs, a sum score ≥ 6 points yielded a sensitivity of 90%, specificity of 96%, positive predictive value of 82%, negative predictive value of 98%, and area under the receiver operating characteristic curve of 0.965.

CONCLUSION

A scoring system using three parameters may be helpful in guiding the differential diagnosis between high-ADA MPEs and high-ADA TPEs.

Development and Validation of a Scoring System for Early Diagnosis of Malignant Pleural Effusion Based on a Nomogram

Background

The diagnostic value of clinical and laboratory features to differentiate between malignant pleural effusion (MPE) and benign pleural effusion (BPE) has not yet been established.

Objectives

The present study aimed to develop and validate the diagnostic accuracy of a scoring system based on a nomogram to distinguish MPE from BPE.

Methods

A total of 1,239 eligible patients with PE were recruited in this study and randomly divided into a training set and an internal validation set at a ratio of 7:3. Logistic regression analysis was performed in the training set, and a nomogram was developed using selected predictors. The diagnostic accuracy of an innovative scoring system based on the nomogram was established and validated in the training, internal validation, and external validation sets (n = 217). The discriminatory power and the calibration and clinical values of the prediction model were evaluated.

Results

Seven variables [effusion carcinoembryonic antigen (CEA), effusion adenosine deaminase (ADA), erythrocyte sedimentation rate (ESR), PE/serum CEA ratio (CEA ratio), effusion carbohydrate antigen 19-9 (CA19-9), effusion cytokeratin 19 fragment (CYFRA 21-1), and serum lactate dehydrogenase (LDH)/effusion ADA ratio (cancer ratio, CR)] were validated and used to develop a nomogram. The prediction model showed both good discrimination and calibration capabilities for all sets. A scoring system was established based on the nomogram scores to distinguish MPE from BPE. The scoring system showed favorable diagnostic performance in the training set [area under the curve (AUC) = 0.955, 95% confidence interval (CI) = 0.942-0.968], the internal validation set (AUC = 0.952, 95% CI = 0.932-0.973), and the external validation set (AUC = 0.973, 95% CI = 0.956-0.990). In addition, the scoring system achieved satisfactory discriminative abilities at separating lung cancer-associated MPE from tuberculous pleurisy effusion (TPE) in the combined training and validation sets.

Conclusions

The present study developed and validated a scoring system based on seven parameters. The scoring system exhibited a reliable diagnostic performance in distinguishing MPE from BPE and might guide clinical decision-making.

Diagnostic accuracy of the cancer ratio for the prediction of malignant pleural effusion: evidence from a validation study and meta-analysis

OBJECTIVE

This study aimed to assess the diagnostic accuracy of serum LDH to pleural ADA ratio (cancer ratio, CR)for malignant pleural effusion (MPE) through an original study and meta-analysis.

METHODS

We retrospectively collected data from 145 patients with MPE and 117 cases of benign pleural effusions (BPE). The diagnostic performance of CR and a typical biomarker of MPE, carcinoembryonic antigen (CEA), were analysed using the receiver operating characteristic (ROC) curves and the area under the curve (AUC) as a measure of accuracy. The overall diagnostic accuracy of CR was summarised by a standard diagnostic meta-analysis.

RESULTS

Significantly higher CR and pleural CEA values were observed in the MPE patients than in the BPE patients. At a cut-off value of 14.97, CR showed high sensitivity (0.91), low specificity (0.67), and high AUC (0.85). The combination of CEA and CR increased the AUC to 0.98. The meta-analysis included seven studies involving 2,078 patients. The pooled values for sensitivity, specificity, positive/negative likelihood ratio, and diagnostic odds ratio of CR were 0.96, 0.88, 7.70, 0.05, and 169, respectively. The AUC of the summary ROC of CR was 0.98.

CONCLUSION

CR has a high diagnostic accuracy for predicting MPE, especially when used in combination with pleural CEA.

Assessment of the diagnostic value of CEA, CA125, and CRP and their cut-off point for discrimination of exudative pleural effusions

Pleural effusion is divided into exudative and transudative effusion, and the distinction between exudate and transudate requires multiple investigations of biochemical parameters and their comparison in pleural fluid and serum. This study aimed to assess the diagnostic value of CEA, CA125, and CRP and their cut-off point for discrimination of exudative pleural effusions. This epidemiological and cross-sectional study was performed on 50 patients aged between 18 to 90 years with the diagnosis of exudative pleural effusion referred to Imam Khomeini Hospital in Ahvaz in 2018 and 2019. Demographic and clinical information of patients were collected. The pleural effusion was diagnosed based on physical examination and chest radiography. Pleural effusion was confirmed by thoracentesis. A pleural fluid sample was taken from all patients, and the levels of CEA, CA125, and CRP markers were measured in the pleural fluid. Differentiation of transudate and exudate pleural effusions was performed using Light criteria. The mean CEA and CA125 level of pleural fluid were significantly higher, and the mean CRP level of pleural fluid was significantly lower in patients with malignant diagnoses (P <0.05). Cut-off value with highest sensitivity and specificity in differentiating types of exudative pleural effusions was obtained for CEA tumor marker (greater than 49.8), CA125 tumor marker (greater than 814.02), and CRP marker (less than 7.56). Also, in differentiating types of exudative pleural effusions, CEA tumor marker had sensitivity (89.03%) and specificity (78.42%); CA125 tumor marker had sensitivity (53.18%) and specificity (62.44%), and CRP marker had sensitivity (82.16%), and specificity (89.05%) were. Although the tumor markers had high specificity in the present study, the low sensitivity of some of these tumor markers reduced their diagnostic value. On the other hand, given the numerous advantages of tumor markers, such as low cost and non-invasive, combining them with another can increase the diagnostic value and accuracy.

Pleural biomarkers in diagnostics of malignant pleural effusion: a narrative review

Although cytology and pleural biopsy of pleural effusion (PE) are the gold standards for diagnosing malignant pleural effusion (MPE), these tools’ diagnostic accuracy is plagued by some limitations such as low sensitivity, considerable inter-observer variation and invasiveness. The assessment of PE biomarkers may hence be seen as an objective and non-invasive diagnostic alternative in MPE diagnostics. In this review, we summarize the characteristics and diagnostic accuracy of available PE biomarkers, including carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), carbohydrate antigens 125 (CA125), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 15-3 (CA15-3), a fragment of cytokeratin 19 (CYFRA 21-1), chitinase-like proteins (CLPs), vascular endothelial growth factor (VEGF) and its soluble receptor, endostatin, calprotectin, cancer ratio, homocysteine, apolipoprotein E (Apo-E), B7 family members, matrix metalloproteinase (MMPs) and tissue-specific inhibitors of metalloproteinases (TIMPs), reactive oxygen species modulator 1 (Romo1), tumor-associated macrophages (TAMs) and monocytes, epigenetic markers (e.g., cell-free microRNA and mRNA). We summarized the evidence from systematic review and meta-analysis for traditional tumor markers’ diagnostic accuracy. According to the currently available evidence, we conclude that the traditional tumor markers have high specificity (around 0.90) but low sensitivity (around 0.50). The diagnostic accuracy of novel tumor markers needs to be validated by further studies. None of these tumor biomarkers would have sufficient diagnostic accuracy to confirm or exclude MPE when used alone. A multi-biomarker strategy, also encompassing the use of artificial intelligence algorithms, may be a valuable perspective for improving the diagnostic accuracy of MPE.

Auxiliary diagnostic value of tumor biomarkers in pleural fluid for lung cancer-associated malignant pleural effusion

Background

Pleural effusion (PE) can be divided into benign pleural effusion (BPE) and malignant pleural effusion (MPE). There is no consensus on the identification of lung cancer-associated MPE using the optimal cut-off levels from five common tumor biomarkers (CEA, CYFRA 21-1, CA125, SCC-Ag, and NSE). Therefore, we aimed to find indicators for the auxiliary diagnosis of lung cancer-associated MPE by analyzing and then validating the optimal threshold levels of these biomarkers in pleural fluid (PF) and serum, as well as the PF/serum ratio.

Patients and method

The study has two sets of patients, i.e. the training set and the test set. In the training set, 348 patients with PE, between January 1, 2016 and December 31, 2017, were divided into BPE and MPE based on the cytological diagnosis. Subsequently, the optimal cut-off levels of tumor biomarkers were analyzed. In the test set, the diagnostic compliance rate was verified with 271 patients with PE from January 1, 2018 to July 31, 2019 to evaluate the auxiliary diagnostic value of the aforementioned indicators.

Result

In the training set, PF CEA at the cut-off value of 5.23 ng/ml was the most effective indicator for MPE compared with other tumor biomarkers (all p < 0.001). In the test set, PF CEA at the cut-off value of 5.23 ng/ml showed the highest sensitivity, specificity and accuracy, positive and negative predictive value among other tumor biomarkers, which were 99.0%, 69.1%, 91.6%, 90.7%, and 95.9%, respectively.

Conclusion

PF CEA at the cut-off level of 5.23 ng/ml was the most effective indicator for identifying lung cancer-associated MPE among the five common tumor biomarkers.

Development and validation of a novel scoring system developed from a nomogram to identify malignant pleural effusion

BACKGROUND

This study aimed to establish and validate a novel scoring system based on a nomogram for the differential diagnosis of malignant pleural effusion (MPE) and benign pleural effusion (BPE).

METHODS

Patients with PE and confirmed aetiology who underwent diagnostic thoracentesis were included in this study. One retrospective set (N = 1261) was used to develop and internally validate the predictive model. The clinical, radiological and laboratory features were collected and subjected to logistic regression analyses. The primary predictive model was displayed as a nomogram and then modified into a novel scoring system, which was externally validated in an independent set (N = 172).

FINDINGS

The novel scoring system was composed of fever (3 points), erythrocyte sedimentation rate (4 points), effusion adenosine deaminase (7 points), serum carcinoembryonic antigen (CEA) (4 points), effusion CEA (10 points) and effusion/serum CEA (8 points). With a cutoff value of 15 points, the area under the curve, specificity and sensitivity for identifying MPE were 0.913, 89.10%, and 82.63%, respectively, in the training set, 0.922, 93.48%, 81.51%, respectively, in the internal validation set and 0.912, 87.61%, 81.36%, respectively, in the external validation set. Moreover, this scoring system was exclusively applied to distinguish lung cancer with PE from tuberculous pleurisy and showed a favourable diagnostic performance in the training and validation sets.

INTERPRETATION

This novel scoring system was developed from a retrospective study and externally validated in an independent set based on six easily accessible clinical variables, and it exhibited good diagnostic performance for identifying MPE.

FUNDING

NFSC grants (no. 81572942, no. 81800094).