4.6 Article

A High-Accuracy Model Based on Plasma miRNAs Diagnoses Intrahepatic Cholangiocarcinoma: A Single Center with 1001 Samples

Journal

DIAGNOSTICS
Volume 11, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/diagnostics11040610

Keywords

intrahepatic cholangiocarcinoma; CA19-9; microRNA; diagnosis; circulating biomarker

Funding

  1. Clinical Study Project of Zhongshan [2020ZSLC48]
  2. National Key R&D Program of China [2019YFC1315800, 2019YFC1315802]
  3. National Natural Science Foundation of China [81830102, 81772578, 81401929]
  4. Shanghai Rising Star Program [16QA1401000]

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This study demonstrated the diagnostic value of plasma miR-21, miR-122, and CA19-9 in iCCA, and established a novel three-marker model with high accuracy for differentiating iCCA from controls. This model showed great clinical value, especially for diagnosing early iCCA and CA19-9 negative iCCA.
Objectives: Intrahepatic cholangiocarcinoma (iCCA) is a highly malignant cancer. More than 70% of patients are diagnosed at an advanced stage. The aim of this study was to evaluate the diagnostic value of plasma miR-21, miR-122, and CA19-9, hoping to establish a novel model to improve the accuracy for diagnosing iCCA. Materials and methods: Plasma miR-21 and miR-122 were detected in 359 iCCA patients and 642 controls (healthy, benign liver lesions, other malignant liver tumors). All 1001 samples were allocated to training cohort (n = 668) and validation cohort (n = 333) in a chronological order. A logistic regression model was applied to combine these markers. Area under the receiver operating characteristic curve (AUC) was used as an accuracy index to evaluate the diagnostic performance. Results: Plasma miR-21 and miR-122 were significantly higher in iCCA patients than those in controls. Higher plasma miR-21 level was significantly correlated with larger tumor size (p = 0.030). A three-marker model was constructed by using miR-21, miR-122 and CA19-9, which showed an AUC of 0.853 (95% CI: 0.824-0.879; sensitivity: 73.0%, specificity: 87.4%) to differentiate iCCA from controls. These results were subsequently confirmed in the validation cohort with an AUC of 0.866 (0.825-0.901). The results were similar for diagnosing early (stages 0-I) iCCA patients (AUC: 0.848) and CA19-9(negative) iCCA patients (AUC: 0.795). Conclusions: We established a novel three-marker model with a high accuracy based on a large number of participants to differentiate iCCA from controls. This model showed a great clinical value especially for the diagnosis of early iCCA and CA19-9(negative) iCCA.

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