Combining serum miRNAs, CEA, and CYFRA21-1 with imaging and clinical features to distinguish benign and malignant pulmonary nodules: a pilot study : Xianfeng Li et al.: Combining biomarker, imaging, and clinical features to distinguish pulmonary nodules

World J Surg Oncol. 2017 May 25;15(1):107. doi: 10.1186/s12957-017-1171-y.

Abstract

BACKGROUND: Our study was designed to improve the accuracy of determining whether pulmonary nodules are benign or malignant.

Methods: We evaluated the clinical and imaging features and serum markers: neuron specific enolase (NSE), carcino-embryonic antigen (CEA), cytokeratin fragment antigen 21-1 (CYFRA 21-1), miRNA-21-5p, and miR-574-5pof in 39 patients with pathology information. Factors that differed significantly between those with benign versus malignant pulmonary nodules were used to establish a prediction model for identifying malignant nodules.

Results: The studied nodules were 51.3% malignant and 48.7% benign. Age, smoking status, nodule diameter, history of emphysema, vascular sign, burr sign, CYFRA21-1, CEA, miRNA-21-5p, and miRNA-574-5p differed significantly between the benign and malignant nodule groups. Serum levels of CYRFA21-1 and CEA could be used to distinguish between malignant and benign nodules with a positive predictive value (PPV) of 80.0%, a negative predictive value (NPV) of 84.2%, and an area under the receiver operating characteristics curve (AUC) of 0.863. Using the serum levels of miRNA-21-5p and miRNA-574-5p, the PPV was 55%, the NPV was 84.2%, and the AUC was 0.797. When all four serum markers were combined, the PPV was 80%, the NPV was 89.5%, and the AUC was 0.921. We established a prediction model for malignant nodules, including clinical features, imaging features, and serum markers. In cross-validation, the ratio of discriminant conformance was 95%.

Conclusions: Serum levels of miRNA-21-5p and miRNA-574-5p are significantly higher in patients with malignant nodules than in patients with benign nodules and are potential serum biomarkers. Our prediction model could improve malignant nodule diagnosis.

Keywords: Biomarker; Diagnosis; Imaging; Lung cancer; Pulmonary nodule.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Antigens, Neoplasm / blood*
  • Biomarkers, Tumor / analysis*
  • Carcinoembryonic Antigen / blood*
  • Diagnosis, Differential
  • Female
  • Follow-Up Studies
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Keratin-19 / blood*
  • Lung Neoplasms / blood
  • Lung Neoplasms / diagnosis*
  • Lung Neoplasms / diagnostic imaging
  • Male
  • MicroRNAs / blood*
  • Middle Aged
  • Multiple Pulmonary Nodules / blood
  • Multiple Pulmonary Nodules / diagnosis*
  • Multiple Pulmonary Nodules / diagnostic imaging
  • Neoplasm Staging
  • Pilot Projects
  • Prognosis
  • ROC Curve
  • Solitary Pulmonary Nodule / blood
  • Solitary Pulmonary Nodule / diagnosis*
  • Solitary Pulmonary Nodule / diagnostic imaging
  • Tomography, X-Ray Computed
  • Young Adult

Substances

  • Antigens, Neoplasm
  • Biomarkers, Tumor
  • Carcinoembryonic Antigen
  • Keratin-19
  • MicroRNAs
  • antigen CYFRA21.1