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

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.

Construction and validation of a prognostic risk model for breast cancer based on protein expression

Breast cancer (BRCA) is the primary cause of mortality among females globally. The combination of advanced genomic analysis with proteomics characterization to construct a protein prognostic model will help to screen effective biomarkers and find new therapeutic directions. This study obtained proteomics data from The Cancer Proteome Atlas (TCPA) dataset and clinical data from The Cancer Genome Atlas (TCGA) dataset. Kaplan–Meier and Cox regression analyses were used to construct a prognostic risk model, which was consisted of 6 proteins (CASPASE7CLEAVEDD198, NFKBP65-pS536, PCADHERIN, P27, X4EBP1-pT70, and EIF4G). Based on risk curves, survival curves, receiver operating characteristic curves, and independent prognostic analysis, the protein prognostic model could be viewed as an independent factor to accurately predict the survival time of BRCA patients. We further validated that this prognostic model had good predictive performance in the GSE88770 dataset. The expression of 6 proteins was significantly associated with the overall survival of BRCA patients. The 6 proteins and encoding genes were differentially expressed in normal and primary tumor tissues and in different BRCA stages. In addition, we verified the expression of 3 differential proteins by immunohistochemistry and found that CDH3 and EIF4G1 were significantly higher in breast cancer tissues. Functional enrichment analysis indicated that the 6 genes were mainly related to the HIF-1 signaling pathway and the PI3K-AKT signaling pathway. This study suggested that the prognosis-related proteins might serve as new biomarkers for BRCA diagnosis, and that the risk model could be used to predict the prognosis of BRCA patients.

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.

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.

Comparison between closed pleural biopsy and medical thoracoscopy for the diagnosis of undiagnosed exudative pleural effusions: a systematic review and meta-analysis

Background

Exudative pleural effusion (EPE) is a common diagnostic challenge. The utility of medical thoracoscopy (MT) and closed pleural biopsy (CPB) to aid in the diagnosis of EPE has been reported in many published studies. Herein, we perform a systematic review and meta-analysis to compare the diagnostic yield and safety of CPB and MT in EPE.

Methods

Four databases were searched for studies reporting the diagnostic yield of CPB and MT for EPE. The quality of the included studies was evaluated according to the quality assessment of diagnostic accuracy studies (QUADAS) tool. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and complication risks were compared between the two groups.

Results

Ten studies dealing with CPB and twenty-three studies dealing with MT for the diagnosis of EPE were included in this meta-analysis. Pooled sensitivity, specificity, PLR, NLR and DOR of CPB group was 77%, 99%, 32.55, 0.22, 165.71, respectively, while pooled sensitivity, specificity, PLR, NLR and DOR of MT group was 93%, 100%, 10.82, 0.08, 162.81, respectively. The area under the summary receiver operating characteristic (SROC) curve of CPB and MT were both 0.97. The ability of CPB to diagnose non-malignant diseases was like MT (69% vs. 68%), while the ability was lower than that of MT to diagnose malignant diseases (72% vs. 92%). The pooled diagnostic accuracy of CPB and MT for mesothelioma was 26% (95% CI, 14–38%) and 42% (95% CI, 22–62%) (P<0.001), respectively. The rate of complications with CBP was lower than that reported for MT.

Conclusions

CBP is a relatively accurate tool with a lower complication rate compared to MT in the diagnosis of EPE, especially in diagnosing non-malignant diseases. We confirm the utility of MT in the diagnostic workup of malignancy (especially mesothelioma); however, in selected cases, CPB could be used as the first diagnostic approach with a favorable safety profile.

Use of cholesterol and soluble tumour markers CEA and syndecan-2 in pleural effusions in cases of inconclusive cytology

Aims

In order to improve diagnostics in pleural effusions, additional value of effusion cholesterol, carcinoembryonic antigen (CEA) and syndecan-2 assays to cytology was studied.

Methods

Biomarkers were measured in effusion supernatants from 247 patients, of whom 126 had malignant pleural involvement, and their additional diagnostic efficacy to cytology was assessed.

Results

Syndecan-2 measurement, although gave detectable concentrations in all effusions with highest median value in mesotheliomas, was non-discriminative between different pathological conditions. CEA concentrations exceeding 5 ng/mL cut-off point indicated carcinomas, regardless of pleural involvement, which gave a sensitivity of 62% and specificity of 100% for carcinoma. Cholesterol concentration over 1.21 mmol/L cut-off value indicated neoplastic pleural involvement with 99% sensitivity and ‘merely’ 69% specificity, the latter mainly due to raised levels being associated also with benign inflammatory effusions. Combined CEA and cholesterol determinations increased the sensitivity for diagnosing carcinomatosis from 70% with cytology alone to 84% and established the correct diagnosis in 16 of 31 carcinomatosis cases with inconclusive cytology. Cholesterol measurement alone, with elevated level, in combination with absence of substantial number of inflammatory cells in effusion sediment proved to be a magnificent marker for neoplastic pleural involvement with 99% efficacy, and recognised all 36 such cases with inconclusive cytology.

Conclusions

Simultaneous measurement of CEA and cholesterol concentrations in effusion, or at least cholesterol alone, in combination with non-inflammatory fluid cytology, provides additional specific information about neoplastic pleural involvement, and can therefore be used as an adjunct to cytology, above all, in inconclusive cases.

[Detection of carcinoembryonic antigen levels in pleural effusion and serum and their ratio for differential diagnosis of pleural effusion resulting from tuberculosis and lung cancer]

OBJECTIVE

To study the clinical value of detecting carcinoembryonic antigen levels in pleural effusion (PCEA) and serum (SCEA) and their ratio (P/S) in the differential diagnosis of pleural effusions resulting from tuberculosis and lung cancer.

METHODS

This retrospectively study was conducted among 82 patients with pleural effusion caused by pulmonary tuberculous (TB; control group) and 120 patients with pleural effusion resulting from lung cancer in our hospital between April, 2016 and March, 2018. PCEA, SCEA and P/S were compared between the two groups and among the subgroups of lung cancer patients with squamous cell carcinoma (SqCa), adenocarcinoma (ACA), small cell carcinoma (SCLC). The receiveroperating characteristic curve (ROC) analysis was used to confirm the optimal critical value to evaluate the diagnostic efficiency of different combinations of PCEA, SCEA and P/S.

RESULTS

PCEA, SCEA and P/S were significantly higher in the overall cancer patients and in all the 3 subgroups of cancer patients than in the patients with TB (P &lt; 0.05). The areas under the ROC curve of PCEA, SCEA and P/S were 0.925, 0.866 and 0.796, respectively; PCEA had the highest diagnostic value, whose diagnostic sensitivity, specificity, accurate rate, and diagnostic threshold were 83.33%, 96.34, 88.61%, and 3.26 ng/ml, respectively; SCEA had the lowest diagnostic performance; the diagnostic performance of P/S was between that of SCEA and PCEA, but its combination with SCEA greatly improved the diagnostic performance and reduced the rates of misdiagnosis and missed diagnosis. Parallel tests showed that the 3 indexes combined had significantly higher diagnostic sensitivity than each or any two of the single indexes (P &lt; 0.05), but the diagnostic specificity did not differ significantly. The area under the ROC curve of combined detections of the 3 indexes was 0.941 for diagnosis of lung cancer-related pleural effusion, higher than those of any other combinations of the indexes.

CONCLUSIONS

The combined detection of PCEA, SCEA and P/S has a high sensitivity for diagnosis of lung cancer-related pleural effusion and provides important information for rapid and accurate diagnosis of suspected cases.