Fig 1. Performance of the classifier in the training cohort.

(A) Receiver operating characteristic (ROC) curve of six-miR classifier predictive for response to first line systemic treatment for patients with mCRC based on the training cohort (n = 88), resulting in an area under the curve (AUC) of 0.78. Included in the classifier are miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p and miR-98-5p and four clinicopathological covariates; prior use of adjuvant therapy, the type of systemic treatment regimen, age and primary tumor differentiation. When excluding the miRs from the prediction algorithm the AUC drops to 0.35. The false positive rate (1-specificity) is depicted on the x-axis and, the sensitivity is depicted on the y-axis. (B) Boxplot of the internal cross validated predicted probabilities for clinical benefit. The median predicted probability for the 70 patients with clinical benefit was 0.90 (IQR: 0.77–0.97). For the 18 patients with progressive disease the median predicted probability for clinical benefit was 0.60 (IQR: 0.47–0.84). Predicted probabilities were calculated using the expression levels of the six selected miRs and four clinicopathological covariates. (C) Correlation between the predicted probabilities for clinical benefit (y-axis) with progression free survival (x-axis) of the training cohort. There is a significant correlation of 0.30 (spearman’s rho) (p = 0.006). (D) Correlation between the predicted probabilities for clinical benefit (y-axis) with overall survival (x-axis) of the training cohort. There is a correlation of 0.19 (spearman’s rho), which is not significant (p = 0.08).