#######################KM曲线
rm(list = ls())   #清理环境
library(survival)
library(survminer)
df = read.csv("../rawdata/xxx.csv",row.names = 1)
# 1.0 sex categorica
fit_stage = survfit(Surv(time = survival_time,event = survival_state)~T_stage,
                  data=df)
# about the argument of ggsurvplot , please see http://www.sci666.net/55393.html
ggsurvplot(fit_stage,
           pval = T, # P-value
           conf.int = F, # confidence interval
           risk.table = T, # the table below the plot
           palette = "npg", # change the color
           legend = c(0.8,0.8), # the possion of legend
           legend.title = "T_stage", # the title of legend
           legend.labs = c("1","2","3","4"), # the label of legend 数量需与T_stage一致
           xlab = "Follow up time (months)" # the label of x-axis
)