Diagnostic value of tumor markers for lung adenocarcinoma-associated malignant pleural effusion: a validation study and meta-analysis

Use of tumor markers in distinguishing lung adenocarcinoma-associated malignant pleural effusion from tuberculous pleural effusion

BACKGROUND

The distinction between lung adenocarcinoma-associated malignant pleural effusion (MPE) and tuberculous pleural effusion (TPE) continues to pose a challenge. This study sought to assess the supplementary value of tumor markers in enabling a differential diagnosis.

METHODS

Data concerning tumor markers, which included carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), cancer antigen 153 (CA153), cancer antigen 724 (CA724), neuron-specific enolase (NSE), cytokeratin19 fragment (Cyfra21-1), and squamous cell carcinoma antigen (SCCA), in both serum and pleural effusion samples, were retrospectively compiled from lung adenocarcinoma-associated MPE and TPE patients. A comparative analysis of tumor marker concentrations between the two groups was performed to assess diagnostic utility, followed by a multiple logistic regression to control for confounding variables.

RESULTS

While gender, serum CA125 and SCCA, and pleural effusion SCCA manifested comparability between the groups, distinctions were noted in patient age and the concentration of other tumor markers in serum and pleural effusion, which were notably elevated in the MPE group. Multiple logistic regression demonstrated a positive association between the risk of lung adenocarcinoma-associated MPE and levels of CEA and CA153 in serum and pleural effusion, as well as Cyfra21-1 in serum (P < 0.05). The odds ratio for CEA surpassed that of CA153 and Cyfra21-1.

CONCLUSIONS

CEA and CA153 in serum and pleural effusion, and Cyfra21-1 in serum emerge as biomarkers possessing supplementary diagnostic value in distinguishing lung adenocarcinoma-associated MPE from TPE. The diagnostic efficacy of CEA is superior to CA153 and Cyfra21-1. Conversely, the utility of CA125, CA724, NSE, and SCCA appears constrained.

Pleural Carcinoembryonic Antigen and Maximum Standardized Uptake Value as Predictive Indicators of Visceral Pleural Invasion in Clinical T1N0M0 Lung Adenocarcinoma

Background

Visceral pleural invasion (VPI) is a poor prognostic factor that contributes to the upstaging of early lung cancers. However, the preoperative assessment of VPI presents challenges. This study was conducted to examine intraoperative pleural carcinoembryonic antigen (pCEA) level and maximum standardized uptake value (SUVmax) as predictive markers of VPI in patients with clinical T1N0M0 lung adenocarcinoma.

Methods

A retrospective review was conducted of the medical records of 613 patients who underwent intraoperative pCEA sampling and lung resection for non-small cell lung cancer. Of these, 390 individuals with clinical stage I adenocarcinoma and tumors ≤30 mm were included. Based on computed tomography findings, these patients were divided into pleural contact (n=186) and non-pleural contact (n=204) groups. A receiver operating characteristic (ROC) curve was constructed to analyze the association between pCEA and SUVmax in relation to VPI. Additionally, logistic regression analysis was performed to evaluate risk factors for VPI in each group.

Results

ROC curve analysis revealed that pCEA level greater than 2.565 ng/mL (area under the curve [AUC]=0.751) and SUVmax above 4.25 (AUC=0.801) were highly predictive of VPI in patients exhibiting pleural contact. Based on multivariable analysis, pCEA (odds ratio [OR], 3.00; 95% confidence interval [CI], 1.14-7.87; p=0.026) and SUVmax (OR, 5.25; 95% CI, 1.90-14.50; p=0.001) were significant risk factors for VPI in the pleural contact group.

Conclusion

In patients with clinical stage I lung adenocarcinoma exhibiting pleural contact, pCEA and SUVmax are potential predictive indicators of VPI. These markers may be helpful in planning for lung cancer surgery.

Lung cancer tumor markers in serous effusions and other body fluids

From its onset and during its progression, lung cancer may affect various extrapulmonary structures. These include the serous membranes, the pleura and pericardium, and less frequently the central nervous system, with leptomeningeal involvement. In these cases, fluid accumulates in the serous membranes which may contain substances secreted by the tumor. Measuring the concentrations of these substances can provide useful information for elucidating the origin of the fluid accumulation, either in pleural and pericardial effusions or in cerebrospinal fluid. This paper describes the histological types of lung cancer that most frequently affect the serosa and leptomeninges. It also reviews the literature on tumor markers in different fluids and makes recommendations for their interpretation.

The Diagnosis of Malignant Pleural Effusion Using Tumor-Marker Combinations: A Cost-Effectiveness Analysis Based on a Stacking Model

PURPOSE

By incorporating the cost of multiple tumor-marker tests, this work aims to comprehensively evaluate the financial burden of patients and the accuracy of machine learning models in diagnosing malignant pleural effusion (MPE) using tumor-marker combinations.

METHODS

Carcinoembryonic antigen (CEA), carbohydrate antigen (CA)19-9, CA125, and CA15-3 were collected from pleural effusion (PE) and peripheral blood (PB) of 319 patients with pleural effusion. A stacked ensemble (stacking) model based on five machine learning models was utilized to evaluate the diagnostic accuracy of tumor markers. We evaluated the discriminatory accuracy of various tumor-marker combinations using the area under the curve (AUC), sensitivity, and specificity. To evaluate the cost-effectiveness of different tumor-marker combinations, a comprehensive score (C-score) with a tuning parameter w was proposed.

RESULTS

In most scenarios, the stacking model outperformed the five individual machine learning models in terms of AUC. Among the eight tumor markers, the CEA in PE (PE.CEA) showed the best AUC of 0.902. Among all tumor-marker combinations, the PE.CA19-9 + PE.CA15-3 + PE.CEA + PB.CEA combination (C9 combination) achieved the highest AUC of 0.946. When w puts more weight on the cost, the highest C-score was achieved with the single PE.CEA marker. As w puts over 0.8 weight on AUC, the C-score favored diagnostic models with more expensive tumor-marker combinations. Specifically, when w was set to 0.99, the C9 combination achieved the best C-score.

CONCLUSION

The stacking diagnostic model using PE.CEA is a relatively accurate and affordable choice in diagnosing MPE for patients without medical insurance or in a low economic level. The stacking model using the combination PE.CA19-9 + PE.CA15-3 + PE.CEA + PB.CEA is the most accurate diagnostic model and the best choice for patients without an economic burden. From a cost-effectiveness perspective, the stacking diagnostic model with PE.CA19-9 + PE.CA15-3 + PE.CEA combination is particularly recommended, as it gains the best trade-off between the low cost and high effectiveness.

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.

DNA Methylation Analysis of the SHOX2 and RASSF1A Panel Using Cell-Free DNA in the Diagnosis of Malignant Pleural Effusion

Objectives

The differential diagnosis of pleural effusion (PE) is a common but major challenge in clinical practice. This study aimed to establish a strategy based on a PE-cell-free DNA (cfDNA) methylation detection system for the differential diagnosis of malignant pleural effusion (MPE) and benign pleural effusion (BPE).

Methods

A total of 104 patients with PE were enrolled in this study, among which 50 patients had MPE, 9 malignant tumor patients had PE of indefinite causes, and the other 45 patients were classified as benign controls. The methylation status of short stature homeobox 2 (SHOX2) and RAS association domain family 1, isoform A (RASSF1A) was detected using PE-cfDNA specimens by real-time fluorescence quantitative PCR. Total methylation (TM) was defined as the combination of the methylation levels of SHOX2 and RASSF1A. The electrochemiluminescence immunoassay was applied to evaluate the levels of multiple serum tumor markers.

Results

The PE-cfDNA methylation status of either SHOX2 or RASSF1A was much higher in MPE samples than in benign controls. The combination of SHOX2 and RASSF1A methylation in PE yielded a diagnostic sensitivity of 96% and a specificity of 100%, respectively. When compared with the corresponding serum tumor marker detection results, TM showed the highest diagnostic efficiency (AUC = 0.985). Furthermore, the combination of the SHOX2 and RASSF1A methylation panels using PE-cfDNA could apparently improve the differential diagnostic efficacy of BPE and MPE and could help compensate for the deficiency of cytology.

Conclusions

Our results indicated that SHOX2 and RASSF1A methylation panel detection could accurately classify BPE and MPE diseases and showed better diagnostic performance than traditional serum parameters. The SHOX2 and RASSF1A methylation detection of PE-cfDNA could be a potentially effective complementary tool for cytology in the process of differential diagnosis. In summary, PE-cfDNA could be used as a promising non-invasive analyte for the auxiliary diagnosis 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.

Risk Factors and Impact on Outcomes of Lung Cancer Patients Concurrent with Deep Vein Thrombosis

PURPOSE

Many investigations on prognostic factors in lung cancer have been conducted; however, little is known regarding the outcomes of lung cancer cases complicated by deep vein thrombosis (DVT). This study aimed to determine the risk factors and impact on outcomes of lung cancer patients concurrent with DVT.

METHODS

Lung cancer patients who underwent lower-extremity venous ultrasound were enrolled in this study. The patients were divided into a DVT group and a non-DVT group. Demographic information, clinical characteristics, and survival were analyzed by t-test, Wilcoxon test, chi-squared test, and logistic regression analysis.

RESULTS

Of the 160 enrolled lung cancer patients, DVT was detected in 30 patients. Among the DVT group, adenocarcinoma was the most common histological type (27/30, 90.00%). Lung cancer complicated with DVT was associated with advanced stage, more severe myocardial injury, and a hypercoagulable state (P < .05). Differences in driver genes between the two groups were not significant. Radiologically, lung cancer patients with DVT were more likely to present with pericardial effusion and pleural effusion than patients without DVT (P < .05). Following multivariable logistic regression analysis, advanced stage (OR 5.368, [95%CI 1.871-18.165], P = .021), NT-proBNP >300 pg/ml (OR 5.575, [95%CI 1.733-3.722], P = .018), D-dimer >5 mg/L (OR 8.449, [95%CI 4.323-18.536], P = .004), CRP >12 mg/L (OR 6.687, [95%CI 1.967-13.617], P = .010), and serum CEA >25 ng/ml (OR 4.755, [95%CI 1.358-3.123], P = .029) were independent risk factors for adenocarcinoma complicated with DVT. Finally, survival analysis revealed that the occurrence of DVT resulted in a poorer prognosis despite anticoagulant therapy (P < .05).

CONCLUSION

DVT is a potential complication in patients with lung adenocarcinoma and could represent a prognostic marker for unfavorable outcome. It is essential to screen for DVT in high-risk adenocarcinoma patients.

Construction and analysis of expression profile of exosomal lncRNAs in pleural effusion in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly malignant tumor with a very low five-year survival rate. In this study, we aimed to identify differentially expressed long-chain non-coding RNA (lncRNAs) and mRNAs from benign and malignant pleural effusion exosomes.

METHODS

We used gene microassay and quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR) to detect and verify differentially expressed mRNAs and lncRNAs in benign and malignant pleural effusion exosomes. Gene Ontology (GO) functional significance and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway significance enrichment analyses were performed to identify the difference in biological processes and functions between different mRNAs. We selected the lncRNA ZBED5-AS1 with an upregulated differential fold of 3.003 and conducted a preliminary study on its cellular function.

RESULTS

Gene microassay results revealed that 177 differentially expressed lncRNAs were upregulated, and 215 were downregulated. The top 10 upregulated were FMN1, AL118505.1, LINC00452, AL109811.2, CATG00000040683.1, AC137932.1, AC008619.1, AL450344.1, AC092718.6, and ZBED5-AS1. The top 10 downregulated were TEX41, G067726, JAZF1-AS1, AC027328.1, AL445645.1, AL022345.4, AC008572.1, AC123777.1, AC093714.1, and PHKG1. For the mRNAs, 79 were upregulated, and 123 were notably downregulated. GO analysis revealed that the upregulated differential mRNAs were mainly involved in "cellular response to acidic pH" (biological processes), "endoplasmic reticulum part" (cellular components), and "at DNA binding, cyclase activity" (molecular functions). KEGG pathways were found to be related to V. cholerae infection, Parkinson's disease, and cell adhesion molecules. RT-qPCR showed that ZBED5-AS1 was highly expressed in LUAD tissues, cells, and benign and malignant pleural fluid exosomes. Overexpression of ZBED5-AS1 could significantly promote the proliferation, migration, invasion, and colony formation of LUAD cells, and knockdown had the opposite consequence.

CONCLUSION

The pleural effusion exosomes from patients with LUAD include several improperly expressed genes, and lncRNA-ZBED5-AS1 is a new biomarker that aids in our understanding of the occurrence and progression of LUAD.

Diagnostic Value of Six Tumor Markers for Malignant Pleural Effusion in 1,230 Patients: A Single-Center Retrospective Study

Background: The diagnostic value of tumor markers in pleural effusion (PE) and serum for malignant pleural effusion (MPE) is still in debate. This study aimed to evaluate the diagnostic value of six tumor markers in PE, serum, and the corresponding PE/serum (PE/S) ratio in distinguishing MPE from benign pleural effusion (BPE).

Methods: A total of 1,230 patients with PE (452 MPEs and 778 BPEs) were retrospectively included in the study. PE and serum levels of carcinoembryonic antigen (CEA), carbohydrate antigen 15-3 (CA15-3), carbohydrate antigen 125 (CA125), carbohydrate antigen 19-9 (CA19-9), cytokeratin 19 fragment (CYFRA 21-1), and neuron-specific enolase (NSE) were measured. The area under the curve (AUC) was used to assess the single and combined diagnostic values of the six tumor markers for MPE.

Results: The levels of the six tumor markers in PE, serum, and PE/S were significantly higher in MPE than that in BPE, except for serum CA125. PE CEA showed the highest AUC [0.890 (0.871–0.907)] at a cut-off value of 3.7 ng/ml compared to any single tumor marker using receiver operating characteristic (ROC) analysis. The specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) of PE CEA were 74.1%, 95.5%, 90.5%, 86.4%, 16.47, and 0.27, respectively. The combination of PE CEA and serum CYFRA21-1 showed the best diagnostic performance with an AUC of 0.934 (sensitivity, 79.9%; specificity, 95.7%, PPV, 90.5; PLR, 17.35) among all two or three combinations. Besides, serum CYFRA21-1 was the best diagnostic tumor marker in distinguishing cytology-negative MPE from BPE at a cut-off value of 3.0 ng/ml.

Conclusion: PE CEA was the best diagnostic tumor marker in distinguishing MPE from BPE. Serum CYFRA21-1 was the best diagnostic tumor marker in distinguishing cytology-negative MPE from BPE. The combination of PE CEA and serum CYFRA21-1 could increase the diagnostic performance in distinguishing MPE from BPE and cytology-negative MPE from BPE.

Predicting the nature of pleural effusion in patients with lung adenocarcinoma based on 18F-FDG PET/CT

Background

This study aims to establish a predictive model on the basis of ¹⁸F-FDG PET/CT for diagnosing the nature of pleural effusion (PE) in patients with lung adenocarcinoma.

Methods

Lung adenocarcinoma patients with PE who underwent ¹⁸F-FDG PET/CT were collected and divided into training and test cohorts. PET/CT parameters and clinical information in the training cohort were collected to estimate the independent predictive factors of malignant pleural effusion (MPE) and to establish a predictive model. This model was then applied to the test cohort to evaluate the diagnostic efficacy.

Results

A total of 413 lung adenocarcinoma patients with PE were enrolled in this study, including 245 patients with MPE and 168 patients with benign PE (BPE). The patients were divided into training (289 patients) and test (124 patients) cohorts. CEA, SUVmax of tumor and attachment to the pleura, obstructive atelectasis or pneumonia, SUVmax of pleura, and SUVmax of PE were identified as independent significant factors of MPE and were used to construct a predictive model, which was graphically represented as a nomogram. This predictive model showed good discrimination with the area under the curve (AUC) of 0.970 (95% CI 0.954–0.986) and good calibration. Application of the nomogram in the test cohort still gave good discrimination with AUC of 0.979 (95% CI 0.961–0.998) and good calibration. Decision curve analysis demonstrated that this nomogram was clinically useful.

Conclusions

Our predictive model based on ¹⁸F-FDG PET/CT showed good diagnostic performance for PE, which was helpful to differentiate MPE from BPE in patients with lung adenocarcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13550-021-00850-2.

The diagnostic value of CEA for lung cancer-related malignant pleural effusion in China: a meta-analysis

Objective: To accurately evaluate the diagnostic value of carcinoembryonic antigen (CEA) for malignant pleural effusion associated with lung cancer in the Chinese population.Methods: Three English databases, PubMed, Embase and Web of Science, and two Chinese databases, China National Knowledge Infrastructure (CNKI) and Wanfang Data, up to 5 November 2020, were searched. The literature on the diagnosis of lung cancer-related malignant pleural effusion by CEA in the Chinese population were collected. The data was analyzed by Stata15.0 software.Results: A total of 15 studies were included in the meta-analysis. The combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio were 0.80 (95% CI: 0.74-0.84), 0.92 (95% CI: 0.89-0.95), 10.46 (95% CI: 7.29-15.00), 0.22 (95% CI: 0.17-0.28), 47.26 (95% CI: 28.84-77.44), respectively . The area under the receiver operating characteristic curve was 0.93 (95% CI: 0.91-0.95). No significant publication bias was found (P > 0.05)Conclusion: CEA has anexcellent diagnostic value for patients with lung cancer-related malignant pleural effusion in the Chinese population.

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.

Carbohydrate antigen 19-9 - tumor marker: Past, present, and future

Carbohydrate antigen 19-9 (CA 19-9) is a cell surface glycoprotein complex most commonly associated with pancreatic ductal adenocarcinoma (PDAC). Koprowski first described it in 1979 using a mouse monoclonal antibody in a colorectal carcinoma cell line. Historically, it is one of the most commonly used tumor markers for diagnosing, managing, and prognosticating PDAC. Additionally, elevated CA 19-9 levels are used as an indication for surgery in suspected benign pancreatic conditions. Another common application of CA 19-9 in the biliary tract includes its use as an adjunct in diagnosing cholangiocarcinoma. However, its clinical value is not limited to the hepatopancreatobiliary system. The reality is that the advancing literature has broadened the clinical value of CA 19-9. The potential value of CA 19-9 in patients' workup extends its reach to gastrointestinal cancers - such as colorectal and oesophageal cancer - and further beyond the gastrointestinal tract - including urological, gynecological, pulmonary, and thyroid pathologies. Apart from its role in investigations, CA 19-9 presents a potential therapeutic target in PDAC and acute pancreatitis. In a bid to consolidate its broad utility, we appraised and reviewed the biomarker's current utility and limitations in investigations and management, while discussing the potential applications for CA 19-9 in the works for the future.

Development of risk prediction models for lung cancer based on tumor markers and radiological signs

Background

Accurate prediction of malignancy risk for pulmonary lesions with pleural effusion improves early diagnosis of lung cancer. This study aimed to develop and validate a model to predict lung cancer.

Methods

Clinical data of 536 patients with pulmonary diseases were collected. The risk factors were identified by regression analysis. Three prediction models were developed. The predictive performances of the models were measured by the area under the curves (AUCs) and calibrated with 1000 bootstrap samples to minimize the over‐fitting bias. The net benefits of the models were evaluated by decision curve analysis. Finally, a separate cohort of 134 patients was used to validate the models externally.

Results

Seven independent risk factors were identified from 18 clinical variables, which included the pleural fluid carcinoembryonic antigen (CEA), serum cytokeratin‐19 fragment (CYFRA 21‐1), the ratio of CEA in the pleural fluid to serum, extrathoracic cancer history (>5 years), tumor size, vessel convergence, and lobulation. The AUCs of the three models were 0.976, 0.927, and 0.944 in the training set and 0.930, 0.845, and 0.944 in the external set, respectively. The accuracies of the three models were 89.6%, 81.4%, and 88.8%. Model 1 showed the best iteration fit (R² = 0.84, 0.68, and 0.73) and a higher net benefit on decision curve analysis when compared to the other two models.

Conclusion

The advantageous model could assess the risk of lung cancer in patients with pleural effusion and act as a useful tool for early identification of lung cancer.

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.

Pro-cathepsin D as a diagnostic marker in differentiating malignant from benign pleural effusion: a retrospective cohort study

BACKGROUND

Malignant pleural effusion (MPE) causes substantial symptomatic burden in advanced malignancy. Although pleural fluid cytology is a commonly accepted gold standard of diagnosis, its low diagnostic yield is a challenge for clinicians. The aim of this study was to determine whether pro-cathepsin D can serve as a novel biomarker to discriminate between MPE and benign pleural effusion (BPE).

METHODS

This study included 81 consecutive patients with exudative pleural effusions who had underwent thoracentesis or pleural biopsy. Pleural fluid and serum were collected as a standard procedure for all individuals at the same time. The level of pro-cathepsin D was measured by the sandwich enzyme-linked immunosorbent assay method.

RESULTS

Though there were no significant differences in plasma pro-cathepsin D between the two groups, the level of pleural fluid pro-cathepsin D was significantly higher in the MPE group than the BPE group (0.651 versus 0.590 pg/mL, P = 0.034). The discriminative power of pleural fluid pro-cathepsin D for diagnosing MPE was moderate, with 81% sensitivity and 53% specificity at a pro-cathepsin D cut-off ≥0.596 pg/mL (area under the curve: 0.656). Positive and negative predictive values for MPE were 38 and 89%, respectively, with pro-cathepsin D cut-off value (> 0.596 pg/mL).

CONCLUSIONS

The level of pleural fluid pro-cathepsin D was found to be significantly higher in MPE than in BPE. Although results of this study could not support the sole use of pleural fluid pro-cathepsin D to diagnose MPE, pleural fluid pro-cathepsin D can be added to pre-existing diagnostic methods for ruling-in or ruling-out MPE.

Analysis of tumor markers in pleural effusion and serum to verify the correlations between serum tumor markers and tumor size, TNM stage of lung adenocarcinoma

BACKGROUND

The study of tumor markers (TM) in pleural effusion (PE) was not extensive.

METHODS

TM in PE and serum were analyzed to determine whether TM was expressed in intrathoracic and extrathoracic tissues. To further verify the correlations between serum TM and tumor size, TNM stage of lung adenocarcinoma.

RESULTS

Serum AFP was not correlated with tumor size, T stage, N stage, and M stage (P > .05). Serum CEA, serum CA125, serum CA15-3 were positively correlated with tumor size, T stage, N stage, M stage (P < .05). Serum CA19-9 was not significantly correlated with tumor size and T stage (P > .05), but was positively correlated with N stage and M stage (P < .05). The levels of PE CEA, PE CA125, PE CA15-3 were higher than those of serum CEA, serum CA125, serum CA15-3 (all P < .05). The level of PE AFP was lower than that of serum AFP (P < .05). The level of PE CA19-9 was not significantly different from that of serum CA19-9 (P > .05). The positive rates of PE CEA and PE CA125 were higher than those of serum CEA and serum CA125 (P < .05). The positive rates of PE AFP, PE CA15-3, PE CA19-9 were not significantly different from those of serum AFP, serum CA15-3, serum CA19-9 (P > .05).PE CEA, PE CA125, PE CA15-3 were moderately positively correlated with serum CEA, serum CA125, serum CA15-3, respectively (r = 0.597; r = 0.46; r = 0.583, all P < .05). However, PE AFP and PE CA19-9 were very strongly positively correlated with serum AFP and serum CA19-9, respectively (r = 0.888; r = 0.874, all P < .05).

CONCLUSION

The expression characteristics of TM in PE and serum supported the correlations between serum TM and tumor size, TNM stage of lung adenocarcinoma.

Laboratory Discrimination Between Neutrophilic Malignant and Parapneumonic Pleural Effusions

BACKGROUND

Malignant pleural effusion (MPE) occasionally demonstrates neutrophilic predominance, commonly found in parapneumonic pleural effusion (PPE). In comparison with lymphocytic MPE, neutrophilic MPE may have different characteristics associated with a more intense inflammatory response and poor prognosis. These characteristics of neutrophilic MPE may lead to inappropriate management and delayed diagnosis. Moreover, the limited diagnostic yield of microbiologic and cytologic tests makes early differential diagnosis between neutrophilic MPE and PPE more challenging. This study investigated objective laboratory findings to help distinguish neutrophilic MPE from PPE.

MATERIALS AND METHODS

A retrospective study was conducted on patients with neutrophilic MPE and PPE. Routine blood and pleural fluid data of the 2 groups were compared, and the diagnostic performances of predictors for neutrophilic MPE were assessed using receiver-operating characteristic curves.

RESULTS

Forty-one and 140 patients with neutrophilic MPE and PPE, respectively, were included. In final analysis, serum C-reactive protein, pleural fluid neutrophil-to-lymphocyte ratio, and pleural fluid carcinoembryonic antigen were significantly different between the 2 groups. With cut-off values of C-reactive protein <6.0 mg/dL, neutrophil-to-lymphocyte ratio <3.0 and carcinoembryonic antigen >8.0 ng/mL, the presence of any 2 or more parameters provided an area under the curve of 0.928 (95% CI, 0.851-0.999), yielding a sensitivity of 88%, specificity of 98%, positive predictive value of 92% and negative predictive value of 96% for identifying MPE.

CONCLUSIONS

MPE should be considered even in patients with neutrophilic exudative effusion, especially if at least 1 predictor for neutrophilic MPE is present. Our results may help guide differentiation of neutrophilic MPE from PPE.

Combination of icotinib and chemotherapy as first-line treatment for advanced lung adenocarcinoma in patients with sensitive EGFR mutations: A randomized controlled study

OBJECTIVE

To explore the efficacy and safety of icotinib with chemotherapy as first-line therapy for advanced lung adenocarcinoma in patients with sensitive epidermal growth factor receptor (EGFR) mutations.

METHODS

This prospective, randomized, controlled trial was conducted in 10 general hospitals in Shandong Province, China. Previously untreated patients with advanced lung adenocarcinoma and sensitive EGFR mutations were recruited between January 16, 2014 and December 31, 2016 and randomly allocated to the combination group (icotinib plus pemetrexed and carboplatin) or the icotinib only group. The patients were followed up until May 23, 2018. The primary endpoint was progression-free survival (PFS).

RESULTS

The efficacy analysis (intention-to-treat analysis) include 179 patients (n = 90 in the combination group and n = 89 in the icotinib only group). PFS was significantly longer in the combination group than in the icotinib only group (16.0 months vs. 10.0 months, hazard ratio [HR] = 0.59, 95% confidence interval [CI] 0.42-0.84, P = 0.003). The objective response rate and the disease control rate for the combination group were significantly higher than those for the icotinib only group (77.8% vs. 64.0%, χ² = 4.094, P = 0.043; 91.1% vs. 79.8%, χ² = 4.632, P = 0.031). However, overall survival did not differ between the two groups (36.0 months vs. 34.0 months, HR = 0.81, 95%CI 0.54-1.22, P = 0.309). The incidence rates of leukopenia and liver function damage of grades 3-4 were higher in the combination group than in the icotinib only group (12.2% vs. 0%, χ² = 11.086, P = 0.001; 12.2% vs. 3.5%, χ² = 4.488, P = 0.034). However, adverse events were resolved in most patients.

CONCLUSION

Use of the combination of icotinib and chemotherapy as first-line therapy significantly improved the PFS of advanced lung adenocarcinoma patients with sensitive EGFR mutations. Although the combination therapy increased the incidence of leukopenia and liver function damage, the observed adverse events were tolerable and manageable.

Carcinoembryonic antigen-positive pleural effusion in early stage non-small cell lung cancer without pleural infiltration

Carcinoembryonic antigen (CEA) is a tumor marker for detecting recurrences of adenocarcinomas such as colon cancer. In lung adenocarcinoma, CEA elevation can be found in both serum and malignant pleural effusion. However, CEA elevation in cytologically negative pleural effusion in the presence of adenocarcinoma without pleural infiltration has not been described. We here present the case of an 82-year-old man with incidental early stage adenocarcinoma of the right upper lobe showing CEA elevation in pleural fluid and serum despite negative cytological findings. Due to limited lung reserve the tumor was removed by wide wedge resection, but the visceral pleura was not affected and infiltration of the parietal pleura was ruled out by pleural biopsies. Serum and pleural CEA levels declined postoperatively as measured at 1 and 2 months follow-up. This case shows CEA elevation in serum and pleural fluid in early stage lung adenocarcinoma with negative cytology and no sign of pleural infiltration. Previous research revealed that CEA level in pleural effusion correlates to serum CEA and is significantly higher in adenocarcinoma of the lung than in other lung cancer entities. Firstly, this case suggests that determination of CEA levels can increase the diagnostic sensitivity in cases with cytologically negative pleural effusion suspicious of malignant origin and secondly, it contributes valuable information to the decision whether follow-up of pulmonary nodules or continuative diagnostics such as video-assisted thoracoscopic surgery (VATS) wedge resection is indicated.

Diagnostic value of tumour markers in pleural effusions

Introduction

We investigated whether tumour markers carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 125 (CA-125), and cytokeratin 19 fragment (CYFRA 21-1) in pleural effusions and serum can be used to distinguish pleural effusion aetiology.

Materials and methods

During the first thoracentesis, we measured pleural fluid and serum tumour marker concentrations and calculated the pleural fluid/serum ratio for patients diagnosed with pleural effusion, using electrochemiluminescence immunoassays. Receiver operating characteristic (ROC) analysis was carried out and the Hanley and McNeil method was used to test the significance of the difference between the areas under ROC curves (AUCs). In order to detect which tumour marker best discriminates between malignant and non-malignant pleural effusions and to establish the predictive value of those markers, discriminant function analysis (DFA) and logistic regression analysis were utilized.

Results

Serum tumour markers CYFRA 21-1 and NSE as well as pleural NSE were good predictors of pleural effusion malignancy and their combined model was found statistically significant (Chi-square = 28.415, P < 0.001). Respective ROC analysis showed significant discrimination value of the combination of these three markers (AUC = 0.79).

Conclusions

Serum markers showed superiority to pleural fluid markers in determining pleural fluid aetiology. Serum CYFRA 21-1 and NSE concentrations as well as pleural fluid NSE values had the highest clinical value in differentiating between malignant and non-malignant pleural effusions. The combination of these three markers produced a significant model to resolve pleural effusion aetiology.

A case report of lung adenocarcinoma with polyserous effusions as the onset symptom

RATIONALE

Coexistence of lung adenocarcinoma and polyserous effusions is quite rare. This complexity of etiology adds difficulty to the diagnosis and is likely to cause misdiagnosis and maldiagnosis.

PATIENT CONCERNS

A 43-year-old woman was admitted with symptoms of dry cough, chest suffocation, polyserous effusions, and generalized edema. Only a small number of heterocysts were detected in the ascites, and malignant cells were detected in the pleural and pericardial effusions. After cytology tests of pericardial, pleural effusions, and ascites, puncture biopsy of the left lung lesion was performed with CT guidance, and immunohistochemical tests were performed.

DIAGNOSES

The diagnosis of lung adenocarcinoma was histopathologically confirmed by puncture biopsy with CT guidance of the left lower lung lesion.

INTERVENTIONS

Combined treatments(pemetrexed/cisplatin) was administered after the left lung lesion immunohistochemistry.

OUTCOMES

The patient has survived more than 1 year after pemetrexed/cisplatin combination chemotherapy.

LESSONS

Coexistence of lung adenocarcinoma and polyserous effusions is quite rare. Close attention should be paid whenever a patient with coexistence of ascites, pleural effusion, and pericardial effusion. More diverse methods could be helpful to identify the diagnosis and avoid misdiagnosis. Patients with advanced lung adenocarcinoma need individualized therapy, including pemetrexed/cisplatin combination chemotherapy.