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Fig. 3 | BMC Neurology

Fig. 3

From: Identification of an endoplasmic reticulum stress-related signature associated with clinical prognosis and immune therapy in glioma

Fig. 3

Prediction of the 7-gene signature of glioma patients in the TCGA and CGGA datasets. (A) Kaplan–Meier algorithm among the high-risk group and low-risk group from the TCGA dataset. (B) The ROC algorithm indicates the specificity and sensitivity to predict survival based on the ERS-related signature from the TCGA database. (C) The risk curve represents the risk score and distribution of 665 cases from the TCGA database. (D) The survival status graph shows the difference in survival time of 665 cases from the TCGA database (each point represents a sample, C-D). (E) Univariate Cox regression algorithm of clinical and pathological features for survival rate from the TCGA dataset. (F) Multivariate Cox regression algorithm of clinical and pathological features for survival rate from the TCGA dataset. **P < 0.01; ***P < 0.001

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BMC Neurology

ISSN: 1471-2377

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