Development of IRL classifier for prediction of prognosis in TETs patients in TCGA database
(A) Time-independent ROC curves with AUC values to evaluate predictive efficacy of IRL classifier based on RFS. (B) Kaplan–Meier estimates of patients’ RFS and time using the median risk score cut-off which divided patients into low-risk and high-risk groups. (C) Correlation between IRL score and RFS. (D) Time-independent ROC curves with AUC values to evaluate predictive efficacy of IRL classifier based on OS. (E) Kaplan–Meier estimates of patients’ OS and time using the median risk score cut-off which divided patients into low-risk and high-risk groups. (F) Correlation between IRL score and OS. (G) Time-independent ROC curves with AUC values to evaluate predictive efficacy of IRL classifier based on DSS. (H) Kaplan–Meier estimates of patients’ DSS and time using the median risk score cut-off which divided patients into low-risk and high-risk groups. (I) Correlation between IRL score and DSS.