Fig. 4From: A machine learning framework develops a DNA replication stress model for predicting clinical outcomes and therapeutic vulnerability in primary prostate cancerThe predictive performance of replication stress signature (RSS) was compared with that of clinical features and prognostic signatures. Comparison of C-index between RSS and clinical features in the A TCGA-PRAD, B DKFZ-PRAD, C GSE70768, D GSE70769, E GSE94767 datasets. Data are presented as mean ± 95% confidence interval. F Univariate Cox regression analysis of prognostic signatures in 5 prostate cancer cohorts. Dots represent log2(hazard ratio). The upper and lower bounds of the bars indicate log2(95% confidence interval). G Comparison of C-index between RSS and other prognostic signatures across cohorts. Dots represent the mean C-index while the upper and lower bounds of the bars indicate a 95% confidence interval. Comparison of Time-dependent area under the receiver operating characteristic curve (AUC) among prognostic signatures at H 1-, I 3-, and J 5-years in the TCGA-PRAD dataset. The asterisks are used to denote the statistical P value (*P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)Back to article page