Construction of DCV Prediction Model

A DCV prediction model was constructed using the Group A CSF/PBD3 dataset. The model used the 26 miRNAs (“variables,” Supplementary File 1) that did not have any missing data across all 3 patient groups. Among the 26 miRNAs, the expression levels of 7 miRNAs exhibited perfect discrimination between DCV+ and DCV- patient groups in the Group A dataset (Supplementary Figure 2 and Supplementary File 1). These seven miRNAs each served as individual predictors in a consensus predictive tool. The remaining 19 miRNAs were used to generate a decision tree using the Recursive partitioning and regression trees (Therneau and Atkinson, 2019) (Rpart) algorithm in R.