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Fig. 3 | Clinical Epigenetics

Fig. 3

From: Random forest-based modelling to detect biomarkers for prostate cancer progression

Fig. 3

Performance analysis of the model in the test and validation datasets. a, c, e ROC curve analysis of the model’s performance in the test set (a), ICGC PCa cohort (c) and TCGA PRAD cohort (e). The x-axis shows the model’s specificity while the y-axis shows the sensitivity. Red dot represents the performance of the model when a cut-off of 0.5 is used during classification. b, d, f Kaplan-Meier curves using PSA recurrence-free survival as an outcome in the test set (b), in the ICGC PCa cohort (d) and in the TCGA-PRAD cohort (f), based on the predicted prognostic categories (blue: good prognosis, red: poor prognosis). p values were calculated using log-rank test

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