Identification of a ten-long noncoding RNA signature for predicting the survival and immune status of patients with bladder urothelial carcinoma based on the GEO database: a superior machine learning model

XuDong Mao; ShiHan Chen; GongHui Li

doi:doi:10.18632/aging.202553

← Back

Research Paper Volume 13, Issue 5 pp 6957—6981

Identification of a ten-long noncoding RNA signature for predicting the survival and immune status of patients with bladder urothelial carcinoma based on the GEO database: a superior machine learning model

Figure 6. Forest plots showing the hazard ratios (HRs) with 95% confidence intervals (95% CIs) based on the multivariate Cox regression results. (A) Risk score and tumour stage are dependent of age, sex and histopathological grade in GSE32894. (B) Risk score is dependent of sex, age, tumour stage, histopathological grade and concomitant CIS in GSE32894.