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Fig. 4 | Hereditas

Fig. 4

From: Integrated multi-omics analysis and machine learning refine molecular subtypes and clinical outcome for hepatocellular carcinoma

Fig. 4

Evaluation of the CMLBS model. (A). Univariate and multivariate regression analysis of TCGA-LIHC cohort. (B). Univariate and multivariate regression analysis of ICGC-LIRI cohort. (C-D). The comparison of the C-index between the nomogram and other clinical characteristics in the TCGA-LIHC and ICGC-LIRI cohorts. (E-F). DCA analysis showing the net benefit by applying the nomogram and other clinical characteristics in the TCGA-LIHC and ICGC-LIRI cohorts. (G). Construction of the nomogram based on the CMLBS and clinical characteristics (including age, sex, and clinical stage) in the TCGA-LIHC cohort. (H). Heatmap of CMLBS distribution, patient survival, and expression profiles of 11 module genes that comprise CMLBS in the TCGA-LIHC cohort. (I). Heatmap of CMLBS distribution, patient survival, and expression profiles of 11 module genes that comprise CMLBS in the ICGC-LIRI cohort. (J). Calibration curve of the nomogram for 1, 3, and 5-year OS in the TCGA-LIHC cohort. (K). Calibration curve of the nomogram for 1 and 3-year OS in the ICGC-LIRI cohort

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