Predicting the Clinical Outcome of Triple-Negative Breast Cancer Based on the Gene Expression Characteristics of Necroptosis and Different Molecular Subtypes

Figure 8

Nomogram of prognostic risk model in RNAseq data set combined with the clinical and pathological characteristics. (a) Patients with the full-scale annotations (RS, gender, age, and TNM Stage) were employed for constructing the survival decision tree and optimizing the risk stratification. (b) Significant differences noted in OS values noted in the 4 risk subgroups. (c, d) A comparative analysis between groups. (e, f) Univariate and multivariate Cox regression analyses of the RS and clinicopathological traits. (g) In comparison to the different clinicopathological features, the nomogram showed the highest capacity for OS prediction. (h) Nomograph model. (i) Calibration curve regarding nomograph in 2, 3, and 5 years. (j) Decision curve regarding nomograph. ns: no significance. , , , and .

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