Fig. 4: Multivariate Cox regression analyses in the TCGA and SMC external validation cohorts. | Nature Communications

Fig. 4: Multivariate Cox regression analyses in the TCGA and SMC external validation cohorts.

From: Histopathologic image–based deep learning classifier for predicting platinum-based treatment responses in high-grade serous ovarian cancer

Fig. 4

The multivariate Cox regression analysis was conducted using six variables: age, FIGO stage, BRCA mutation status, HRD status, combined BRCA and HRD status, and PathoRiCH prediction. The data are presented with error bar representing 95% confidence interval. a In the TCGA cohort, PathoRiCH stood out as the most powerful independent prognostic factor (p = 6.57E-05), followed by FIGO stage (p = 0.005) and BRCA status (p = 0.32). b In the SMC cohort, FIGO stage (p = 0.004) and PathoRiCH (p = 0.39) stood out as significant independent prognostic factors.

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