Combining serum miRNAs, CEA, and CYFRA21-1 with imaging and clinical features to distinguish benign and malignant pulmonary nodules: a pilot study

Li, Xianfeng; Zhang, Qinghua; Jin, Xianyu; Cao, Lihua

doi:10.1186/s12957-017-1171-y

Cited by 31 publications

(16 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…26 Other studies have shown that lumps are more likely to be destructive if vessel convergence signs are present. 30 Furthermore, our models differed from other models in many ways, such as in target population and parameters. [18][19][20][21][22][23][24][25][26]31,32 On one hand, our models focused on patients with lung diseases and pleural effusion, in which 73.6% of cases were adenocarcinomatous in the lung cancer group, and 66.1% of subjects had tuberculosis in the benign group.…”

Section: Discussionmentioning

confidence: 96%

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

et al. 2020

Clinical Laboratory Analysis

View full text Add to dashboard Cite

Lung cancer is one of the leading causes of cancer-related deaths worldwide, accounting for about 787,000 deaths each year in China. 1,2 Many patients are identified in the advanced stages of lung cancer during initial diagnosis. The age-standardized 5-year relative survival of lung cancer was only 19.7% in China, but if diagnosed at an early stage, then surgical resection offers a favorable prognosis. 3-5 There are several methods for diagnosing lung cancer. The most commonly recommended method for screening lung cancer is computed tomography (CT), especially the low-dose CT (LDCT). Early screening of lung cancer through LDCT decreases the mortality rate by 20%. 6 Fluorodeoxyglucose positron emission tomography

show abstract

Section: Discussionmentioning

confidence: 96%

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

et al. 2020

Clinical Laboratory Analysis

View full text Add to dashboard Cite

show abstract

“…As a result, detecting miRNAs in serum was more convenience for clinical practice [ 79 , 80 ]. Also, combined miRNAs with serum protein markers, such as cytokeratin 19 fragment (CYFRA21-1), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer-associated antigen (CA) 125 and CA 19-9 maybe more effective in the diagnosis of lung cancer [ 58 , 81 ]. We also conducted subgroup analysis based on the source of controls; the source of controls could be mainly divided into healthy population and cancer-free controls.…”

Section: Discussionmentioning

confidence: 99%

The clinical use of circulating microRNAs as non-invasive diagnostic biomarkers for lung cancers

Yang

Zhou

et al. 2017

Oncotarget

View full text Add to dashboard Cite

Many studies have investigated the diagnostic role of circulating microRNAs (miRNAs) in patients with lung cancer; however, the results still remain inconclusive. An updated system review and meta-analysis was necessary to give a comprehensive evaluation of diagnostic role of circulating miRNAs in lung cancer. Eligible studies were searched in electronical databases. The sensitivity and specificity were used to plot the summary receiver operator characteristic (SROC) curve and calculate the area under the curve (AUC). The between-study heterogeneity was evaluated by Q test and I2 statistics. Subgroup analyses and meta-regression were further performed to explore the potential sources of heterogeneity. A total of 134 studies from 65 articles (6,919 patients with lung cancer and 7,064 controls) were included for analysis. Overall analysis showed that circulating miRNAs had a good diagnostic performance in lung cancers, with a sensitivity of 0.83, a specificity of 0.84, and an AUC of 0.90. Subgroup analysis suggested that combined miRNAs and Caucasian populations may yield relatively higher diagnostic performance. In addition, we found serum might serve as an ideal material to detecting miRNA as good diagnostic performance. We also found the diagnostic role of miRNAs in early stage lung cancer was still relatively high (the sensitivity, specificity and an AUC of stage I/II was 0.81, 0.82 and 0.88; and for stage I, it was 0.80, 0.81, and 0.88). We also identified a panel of miRNAs such as miR-21-5p, miR-223-3p, miR-155-5p and miR-126-3p might serve as potential biomarkers for lung cancer. As a result, circulating miRNAs, particularly the combination of multiple miRNAs, may serve as promising biomarkers for the diagnosis of lung cancer.

show abstract

“…Currently, traditional tumor-associated antigen (TAA) biomarkers, such as cytokeratin 19 fragment antigen 21-1 (CYFRA21-1), neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC), carbohydrate antigen (CA) 125, CA15-3, CA19-9, and CA72-4, remain widely used as reference diagnoses for lung cancer [ 9 , 10 ] (Isaksson, Jonsson et al 2017, Seijo, Peled et al 2019). Single markers have limited sensitivity and specificity, and combinations of tumor markers (TMs) can improve the diagnostic accuracy [ 12 – 15 ] (Yoon, Kwon et al 2016, Li, Zhang et al 2017, Liu, Teng et al 2017, Fang, Zhu et al 2018), but few studies have compared different panels of TAAs, and some of these biomarkers may be increased in patients with BLD. Therefore, the aim of this study was to identify the best potential combinations of these traditional tumor markers in distinguishing lung cancer patients from BLD controls.…”

Section: Introductionmentioning

confidence: 99%

Lack of Efficacy of Combined Carbohydrate Antigen Markers for Lung Cancer Diagnosis

et al. 2020

View full text Add to dashboard Cite

Background. Lung cancer (LC) is top-ranked in cancer incidence and is the leading cause of cancer death globally. Combining serum biomarkers can improve the accuracy of LC diagnosis. The identification of the best potential combination of traditional tumor markers is essential for LC diagnosis. Patients and Methods. Blood samples were collected from 132 LC cases and 118 benign lung disease (BLD) controls. The expression levels of ten serum tumor markers (CYFR21, CEA, NSE, SCC, CA15-3, CA 19-9, CA 125, CA50, CA242, and CA724) were assayed, and that the expression in the levels of tumor markers were evaluated, isolated, and combined in different patients. The performance of the biomarkers was analyzed by receiver operating characteristic (ROC) analyses, and the difference between combinations of biomarkers was compared by Chi-square ( χ 2 ) tests. Results. As single markers, CYFR21 and CEA showed good diagnostic efficacy for nonsmall cell lung cancer (NSCLC) patients, while NSE and CEA were the most sensitive in the diagnosis of small cell lung cancer (SCLC). The area under the curve (AUC) value was 0.854 for the panel of four biomarkers (CYFR21, CEA, NSE, and SCC), 0.875 for the panel of six biomarkers (CYFR21, CEA, NSE, SCC, CA125, and CA15-3), and 0.884 for the panel of ten markers (CYFR21, CEA, NSE, SCC, CA125, CA15-3, CA19-9, CA50, CA242, and CA724). With a higher sensitivity and negative predictive value (NPV), the diagnostic accuracy of the three panels was better than that of any single biomarker, but there were no statistically significant differences among them (all P values > 0.05). However, the panel of six carbohydrate antigen (CA) biomarkers (CA125, CA15-3, CA19-9, CA50, CA242, and CA724) showed a lower diagnostic value (AUC: 0.776, sensitivity: 59.8%, specificity: 73.0%, and NPV: 60.4%) than the three panels ( P value < 0.05). The performance was similar even when analyzed individually by LC subtypes. Conclusion. The biomarkers isolated are elevated for different types of lung cancer, and the panel of CYFR21, CEA, NSE, and SCC seems to be a promising serum biomarker for the diagnosis of lung cancer, while the combination with carbohydrate antigen markers does not improve the diagnostic efficacy.

show abstract

Combining serum miRNAs, CEA, and CYFRA21-1 with imaging and clinical features to distinguish benign and malignant pulmonary nodules: a pilot study

Cited by 31 publications

References 26 publications

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

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

The clinical use of circulating microRNAs as non-invasive diagnostic biomarkers for lung cancers

Lack of Efficacy of Combined Carbohydrate Antigen Markers for Lung Cancer Diagnosis

Contact Info

Product

Resources

About