Statistical analyses
The study population was divided randomly into two groups, the training and test sets (7:3) using the createDataPartition function of caret package in R. The demographic and clinical characteristics were compared between two groups using Fisher’s exact test, the chi-square test, and Wilcoxon rank sum test. Two-sided p values less than 0.05 were considered significant. A random survival forest (RSF) model was adopted to perform survival analyses of PFS and OS in the training set. An RSF is a nonparametric method to analyze right-censored survival data with multiple covariates and there is no need to fulfill any assumptions such as the proportional hazards assumption of classical Cox regressionAll statistical analyses were performed using R version 4.1.2 (The R Foundation for Statistical Computing, Vienna, Austria), with caret version 6.0.92, dplyr version 1.0.9, psych version 2.2.5, tidyverse version 1.3.1, gmodels version 2.18.1.1., survival version 3.3.1, randomForestSRC version 3.1.0 packages.