The training set was used to screen survival-associated miRNAs and establish prognostic model. The test set was used to verify the reliability and accuracy of the prognostic model. Firstly, the multivariate cox regression analysis was used to screen differentially expressed miRNAs using age and sex as covariates. MiRNAs with p <0.05 by the multivariate cox analysis were selected as candidate biomarkers. Then, these candidate miRNAs were divided into high-expression and low-expression groups according to their respectively median expression level to further verify these screened survival-related miRNAs. The multi-gene predictive model was constructed according to these final survival-related miRNAs to predict the risk value of HCC patient, and the survival curve of different risk stratification was plotted to test whether the model could predict the survival of HCC patient. The Receiver Operating Characteristic (ROC) curve was drawn using the survivalROC R package (https://CRAN.R-project.org/package=survivalROC), and the reliability of the prediction model was evaluated based on the AUC curve. In addition, both sensitivity and specificity of prognostic model were verified in the test set.

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