Clinical value of jointly detection pleural fluid Midkine, pleural fluid adenosine deaminase, and pleural fluid carbohydrate antigen 125 in the identification of nonsmall cell lung cancer-associated malignant pleural effusion

Novel clinical biomarkers in blood and pleural effusion for diagnosing patients with tuberculosis distinguishing from malignant tumor

Pleural effusion (PE) is a common manifestation of tuberculosis (TB) and malignant tumors but tuberculous PE (TPE) is difficult to distinguish from malignant PE (MPE), especially by noninvasive detection indicators. This study aimed to find effective detection indices in blood and PE for differentiating TB from a malignant tumor. A total of 815 patients who were diagnosed with TB or cancer in Hubei Shiyan Taihe Hospital from 2014 to 2017 were collected. Amongst them, 717 were found to have PE by thoracoscopy. Clinical characteristics, patients' blood parameters and PE indicator information were summarized for analysis. Patients with MPE had higher percentages to be bloody and negative of Rivalta test in PE than those with TPE. For clinical indicators, comparison of the specific parameters in blood showed that 18 indicators were higher in the TPE group than in the MPE group. By contrast, 12 indicators were higher in the MPE group than in the TPE group (P < .01). In addition, in PE tests, 3 parameters were higher in the TPE group, whereas other 4 parameters were higher in the MPE group (P < .01). Then, for clinical diagnosing practice, ROC analysis and principal component analysis were applied. The top 6 relevant indicators with area under curve over 0.70 were screened out as follows: hydrothorax adenosine dehydrogenase (pADA, 0.90), hydrothorax high-sensitivity C reactive protein (0.79), percentage of blood monocyte (sMONp, 0.75), blood high-sensitivity C reactive protein (sHsCRP, 0.73), erythrocyte sedimentation rate (0.71) and blood D-dimer (0.70). Moreover, logistic regression model revealed that a specific combination of 3 biomarkers, namely, pADA, sMONp and sHsCRP, could enhance the distinguishment of TB from malignant tumor with PE (area under curve = 0.944, 95% confidence interval = 0.925-0.964). The diagnostic function of the top single marker pADA in patients from different groups was analyzed and it was found to maintain high specificity and sensitivity. The 6 indicators, namely, pADA, hydrothorax high-sensitivity C reactive protein, sMONp, sHsCRP, sESR and blood D-dimer, showed significant diagnostic value for clinicians. Further, the combination of pADA, sMONp and sHsCRP has high accuracy for differential diagnosis for the first time. Most interestingly, the single marker pADA maintained high specificity and sensitivity in patients with different statuses and thus has great value for rapid and accurate diagnosis of suspected cases.

Diagnostic value of adenosine deaminase in bronchoalveolar lavage fluid for patients with lung cancer

BACKGROUND

Lung cancer is both the most common seen malignity and cause of cancer-related deaths worldwide. Adenosine deaminase (ADA) is a hydrolytic enzyme that catalyses the conversion of adenosine to inosine in the purine metabolism pathway. Studies examining ADA levels in bronchoalveolar lavage (BAL) fluids of patients with lung malignancy are very limited in the literature. Our aim examine the clinical significance of ADA levels in BAL fluids of patients with lung malignancy.

METHODS

A total of 89 patients undergoing fiberoptic bronchoscopy (FOB) with different indications from December 2017 to December 2018 were included in this study. The patients were divided into two groups as malignancy and non-malignancy groups. Demographic, laboratory data and ADA levels in bronchoalveolar lavage (BAL) were compared between the two groups. In addition, ADA levels in BAL were compared among the histopathological subtypes of patients in the malignant group.

RESULTS

The mean age of the patients was 58.2 ± 14.5 years with 86% of male gender. ADA enzyme levels were statistically higher in the malignant patient group compared with the non-malignant group (37.2 [17.6-71] vs 17.1 [9-35.3], P < .001). When the patients in the malignant group were compared in terms of ADA levels according to their histopathological types, a statistically significant difference was obtained in small cell carcinoma patients (49 [12.5-75.3], P = .005).

CONCLUSION

ADA levels in BAL may be a diagnostic biomarker in lung malignancies. In patients where a biopsy cannot be taken or histopathological typing cannot be performed because of tissue insufficiency, ADA levels in BAL can be an auxiliary parameter in making malignancy / histopathological diagnosis accompanied by radiological and clinical findings.

Exploring the value of pleural fluid biomarkers for complementary pleural effusion disease examination

OBJECTIVE

Pleural fluid biomarkers are beneficial for the complementary diagnosis of pleural effusion etiologies. This study focuses on the multidimensional evaluation of deep learning to investigate the pleural effusion biomarkers value and the diagnostic utility of combining these markers, in distinguishing pleural effusion etiologies.

METHODS

Pleural effusion were divided into three groups according to the diagnosis and treatment guidelines: malignant pleural effusion (MPE), parapneumonic effusion (PPE), and congestive heart failure (CHF). First, the value of the biomarker was analyzed by a receiver operating characteristic (ROC) curve. Then by utilizing deep learning and entropy weight method (EWM), the clinical value of biomarkers was computed multidimensionally for complementary diagnosis of pleural effusion diseases.

RESULTS

There were significant differences in the six biomarkers, TP, ADA, CEA, CYFRA211, NSE, MNC% (p < 0.05) and no significant differences in three physical characteristics including color, transparency, specific gravity and six other biomarkers such as WBC, PNC%, MTC%, pH level, GLU, LDH (p > 0.05) among the three pleural effusion groups. The comprehensive test of pleural fluid biomarkers based on deep learning is of high accuracy. The clinical value of cytomorphology biomarkers WBC, MNC %, PNC %, MTC % was higher among pleural fluid biomarkers.

CONCLUSION

The clinical value of multi-dimensional analysis of biomarkers by deep learning and entropy weight method is different from the ROC curve analysis. It is suggested that during the clinical examination process, more attention should be paid to the cell morphology biomarkers, but the physical properties of the pleural fluid are less clinical significance.

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.

Multiplexed molecular profiling of lung cancer with malignant pleural effusion using next generation sequencing in Chinese patients

Lung cancer is the most common type of cancer and the leading cause of cancer-associated death worldwide. Malignant pleural effusion (MPE), which is observed in ~50% of advanced non-small cell lung cancer (NSCLC) cases, and most frequently in lung adenocarcinoma, is a common complication of stage III-IV NSCLC, and it can be used to predict a poor prognosis. In the present study, multiple oncogene mutations were detected, including 17 genes closely associated with initiation of advanced lung cancer, in 108 MPE samples using next generation sequencing (NGS). The NGS data of the present study had broader coverage, deeper sequencing depth and higher capture efficiency compared with NGS findings of previous studies on MPE. In the present study, using NGS, it was demonstrated that 93 patients (86%) harbored EGFR mutations and 62 patients possessed mutations in EGFR exons 18-21, which are targets of available treatment agents. EGFR L858R and exon 19 indel mutations were the most frequently observed alterations, with frequencies of 31 and 25%, respectively. In 1 patient, an EGFR amplification was identified and 6 patients possessed a T790M mutation. ALK + EML4 gene fusions were identified in 6 patients, a ROS1 + CD74 gene fusion was detected in 1 patient and 10 patients possessed a BIM (also known as BCL2L11) 2,903-bp intron deletion. In 4 patients, significant KRAS mutations (G12D, G12S, G13C and A146T) were observed, which are associated with resistance to afatinib, icotinib, erlotinib and gefitinib. There were 83 patients with ERBB2 mutations, but only two of these mutations were targets of available treatments. The results of the present study indicate that MPE is a reliable specimen for NGS based detection of somatic mutations.

[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 < 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 < 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.

Clinical value of jointly detection pleural fluid Midkine, pleural fluid adenosine deaminase, and pleural fluid carbohydrate antigen 125 in the identification of nonsmall cell lung cancer-associated malignant pleural effusion

BACKGROUND

Midkine (MK) level has been shown to be elevated in serum of patients with nonsmall cell lung cancer (NSCLC). However, the diagnostic value of MK in pleural effusion in NSCLC has not been well validated and established.

METHODS

Samples of NSCLC-associated malignant pleural effusions (MPE) and benign effusions (BPE) were collected. The pleural fluid MK (pMK), pleural fluid adenosine deaminase (pADA), pleural fluid lactate dehydrogenase (pLDH), pleural fluid glucose (pGLU), pleural fluid ferritin (pFER), pleural fluid CA199 (pCA199), pleural fluid CA125 (pCA125), pleural effusion white cell count (pWBC), and pleural effusion red cell count (pRBC) were analyzed, and the clinical data of each group were collected for statistical analysis.

RESULT

The level of pMK, pCA125, pMK + pCA125, and pMK + pCA125 + pADA in the MPE was significantly higher than the BPE group (P = .003, .000, .000, .000). The pADA level in the BPE was significantly higher than the MPE group (P = .003). It showed that the area under the ROC curve (AUC) (0.816) of jointly detection pMK, pCA125, and pADA was significantly higher than other markers for the diagnosis of MPE. Therefore, joint detection of pMK + pCA125 + pADA suggested that the sensitivity, specificity, and AUC was 82.54%, 74.19% at the cutoff 0.47 and diagnostic performance was higher than others.

CONCLUSION

Joint detection of pMK + pCA125 + pADA can be used as a good indicator for the identification of MPE of NSCLC.