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Fig. 4 | Journal of Translational Medicine

Fig. 4

From: A machine learning framework develops a DNA replication stress model for predicting clinical outcomes and therapeutic vulnerability in primary prostate cancer

Fig. 4

The 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)

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