getsurvplot <- function(feature,feature_name,df,labs=c("ctDNA Negative","ctDNA Positive")){

  s_fit = as.formula(paste0('Surv(DFS,DFS_status)~', feature))

  fit = surv_fit(s_fit,data=df)

  p =  ggsurvplot(fit, risk.table = TRUE,legend.labs=labs,risk.table.title = "No. at risk",

                  palette = c("#003B63","#9E333E"),legend = 'none',

                  title=feature_name,xlab="Days from surgery",ylab="Recurrence-free Survival",

                  conf.int= F,break.time.by = 90,axes.offset=F,fontsize = 5,

                  tables.theme = theme_cleantable(base_family= 'Arial'),

                  risk.table.height = 0.2,censor.size=2, size = 0.3,

                  ggtheme = theme(

                    axis.text = element_text(size=12),

                    panel.background = element_rect(fill = "white"),

                    plot.title = element_text(hjust = 0.5),

                    plot.background = element_blank(),

                    axis.line = element_line(colour = "black"),

                    axis.title = element_text(size=14,face = 'bold', family="sans"),

                    legend.text = element_text(size=14, family="sans"),

                    legend.title = element_text(size=14, family="sans"),

                    title = element_text(size=14,face = 'bold', family="sans"),

                    # panel.grid.major.y = element_line(colour = "grey"),

                    #panel.grid.minor.y = element_line(colour = "darkgrey")

                  ))

  res<-coxph(s_fit,data=df)

  pval = summary(res)$logtest[3]

  if (pval<0.0001){

    pcut = "P < .0001"

  }else if (pval<0.001){

    pcut = "P < .001"

  }else if(pval<0.01){

    pcut = "P < .01"

  }else if(pval<0.05){

    pcut= "P < .05"

  }else{

    pcut= paste0("P = ",round(pval,2))

  }

  p$plot = p$plot+

    ggplot2::annotate("text",x = 30, y = 0.10,size=5,hjust = 0,

                      label = paste0("Log-rank ",pcut,

                                     "\n",

                                     "HR: ",round(summary(res)$conf.int[1],2)," (",

                                     "95%CI: ",round(summary(res)$conf.int[3],2),"-",

                                     round(summary(res)$conf.int[4],2),")"

                      )

    )

  p$table <- p$table + theme(panel.grid.major.y = element_blank(),axis.text.y = element_text(hjust=0,size=14, family="sans"),

                             plot.title = element_text(hjust = 0,size=14,face = 'bold', family="sans"),

                             text = element_text(size=12, family="sans")

  )

  return(p)

}

getATplot = function(title,AT_df){

  res_pos = summary(coxph(Surv(DFS,DFS_status)~AdjuvantTherapy_status,

                          subset(AT_df, P2_stat=="Pos"&PathologicStage %in% c("IIA","IIB","IIIA","IIIB"))))

  pval_pos = res_pos$sctest[3]

  res_neg = summary(coxph(Surv(DFS,DFS_status)~AdjuvantTherapy_status,

                          subset(AT_df, P2_stat=="Neg"&PathologicStage %in% c("IIA","IIB","IIIA","IIIB"))))

  pval_neg = res_neg$sctest[3]

  res_ACT = summary(coxph(Surv(DFS,DFS_status)~P2_stat,

                          subset(AT_df, AdjuvantTherapy_status==1&PathologicStage %in% c("IIA","IIB","IIIA","IIIB"))))

  pval_ACT = res_ACT$sctest[3]

  res_nonACT = summary(coxph(Surv(DFS,DFS_status)~P2_stat,

                             subset(AT_df, AdjuvantTherapy_status==0&PathologicStage %in% c("IIA","IIB","IIIA","IIIB"))))

  pval_nonACT = res_nonACT$sctest[3]

  transp = function(pval){

    if (pval<0.0001){

      pcut = "p < .0001"

    }else if (pval<0.001){

      pcut = "p < .001"

    }else if(pval<0.01){

      pcut = "p < .01"

    }else if(pval<0.05){

      pcut= "p < .05"

    }else{

      pcut= paste0("p = ",round(pval,2))

    }

    return(pcut)

  }

  p = ggsurvplot(survfit(Surv(DFS,DFS_status)~Postsurgical_detection+AdjuvantTherapy_status,

                         subset(AT_df, PathologicStage %in% c("IIA","IIB","IIIA","IIIB"))), 

                 risk.table = TRUE,legend = 'none',risk.table.title = "No. at risk",

                 legend.labs=c("no  neg","yes  neg",

                               "no  pos","yes  pos"),

                 palette = c("cornflowerblue","green","brown4","darkorange2"),

                 xlab="Days from surgery",ylab="Recurrence-free Survival",

                 conf.int= F,break.time.by = 90,axes.offset=F,fontsize = 4,censor.size=2, size = 0.5,

                 tables.theme = theme_cleantable(base_family= 'Courier'),

                 risk.table.height = 0.3,title =title,

                 ggtheme = theme(

                   axis.text = element_text(size=12),

                   panel.background = element_rect(fill = "white"),

                   plot.title = element_text(hjust = 0.5),

                   plot.background = element_blank(),

                   axis.line = element_line(colour = "black"),

                   axis.title = element_text(size=14,face = 'bold'),

                   legend.text = element_text(size=14),

                   legend.title = element_text(size=14),

                   title = element_text(size=14,face = 'bold'),

                   # panel.grid.major.y = element_line(colour = "grey"),

                   #panel.grid.minor.y = element_line(colour = "darkgrey")

                 ))

  p$plot = p$plot+

    ggplot2::annotate("text",x = 10, y = 0.10,size=5,hjust = 0,vjust=0,

                      label = paste0(

                        "ACT patients, ctDNA pos vs neg: ",transp(pval_ACT) ,"; ",

                        "non-ACT patients, ctDNA pos vs neg: ",transp(pval_nonACT) ,"\n",

                        "ctDNA negative, ACT vs non-ACT: ",transp(pval_neg) ,"; ",

                        "ctDNA positive, ACT vs non-ACT: ",transp(pval_pos)

                      )

    )

  p$table <- p$table + theme(panel.grid.major.y = element_blank(),axis.text.y = element_text(hjust=0,size=14),

                             plot.title = element_text(hjust = 0,size=10,face = 'bold'),

                             text = element_text(size=10)

  )

  p

}