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
}
Datasets
Models
