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clinical validation.R
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clinical validation.R
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rm(list = ls())
library(dplyr)
library(data.table)
library(tidyr)
library(tibble)
library(survival)
library(survminer)
library(timeROC)
library(pROC)
library(export)
library(ggsci)
load('sampleclin.rda')
# -------------------------------------------------------------------------
kmp <- function(data,legend,main){
mytheme <- theme_survminer(font.legend = c(14,"plain", "black"),
font.x = c(14,"plain", "black"),
font.y = c(14,"plain", "black"),
legend = "top")
cut <- surv_cutpoint(data,'OS.time','OS','RS',minprop = 0.1)
cat <- surv_categorize(cut)
fit <- survfit(Surv(OS.time,OS)~RS,cat)
pp <- ggsurvplot(fit,data = cat,
palette= pal_nejm()(2),
conf.int=FALSE,size=1.3,
pval=T,pval.method = T,
legend.labs=c('High-risk','Low-risk'),
legend.title="",
legend=legend,
xlab="Time(years)",
ylab='Overall survival',
ggtheme = mytheme)
return(ggpar(pp,main = main))
}
table(my$IC)
kmp(my,legend = c(0.84,0.97),main = NULL)
graph2pdf(file='All-patients.pdf',width=4.2,height=4)
# -------------------------------------------------------------------------
kmp <- function(data,legend,main){
mytheme <- theme_survminer(font.legend = c(14,"plain", "black"),
font.x = c(14,"plain", "black"),
font.y = c(14,"plain", "black"),
legend = "top")
cut <- surv_cutpoint(data,'RFS.time','RFS','RS',minprop = 0.1)
cat <- surv_categorize(cut)
fit <- survfit(Surv(RFS.time,RFS)~RS,cat)
pp <- ggsurvplot(fit,data = cat,
palette= pal_nejm()(2),
conf.int=FALSE,size=1.3,
pval=T,pval.method = T,
legend.labs=c('High-risk','Low-risk'),
legend.title="",
legend=legend,
xlab="Time(years)",
ylab='Recurrence-free survival',
ggtheme = mytheme)
return(ggpar(pp,main = main))
}
kmp(my,legend = c(0.84,0.97),main = NULL)
graph2pdf(file='All-patients-rfs.pdf',width=4.2,height=4)
#kmp(my[my$IC==1,],legend = c(0.84,0.97),main = 'Patients with ICI (n = 65)')
#graph2pdf(file='Patients with immunotherapy-rfs.pdf',width=4.2,height=4)
#kmp(my[my$IC==0,],legend = c(0.84,0.97),main = 'Patients without ICI (n = 167)')
#graph2pdf(file='Patients without immunotherapy-rfs.pdf',width=4.2,height=4)
# -------------------------------------------------------------------------
x <- summary(coxph(Surv(OS.time,OS)~.,my[,c(1,2,5:13)]))
y <- data.frame(id=rownames(x$coefficients),
HR=x$coefficients[,2],
HR.95L=x$conf.int[,"lower .95"],
HR.95H=x$conf.int[,'upper .95'],
pvalue=x$coefficients[,"Pr(>|z|)"])
y <- y[c(1:6,10,7:9),]
y[,-1] <- apply(y[,-1],2,as.numeric)
rt <- y
gene <- rt$id
hr <- sprintf("%.3f",rt$"HR")
hrLow <- sprintf("%.3f",rt$"HR.95L")
hrHigh <- sprintf("%.3f",rt$"HR.95H")
Hazard.ratio <- paste0(hr," (",hrLow,"-",hrHigh,")")
pVal <- ifelse(rt$pvalue<0.001, "<0.001", sprintf("%.3f", rt$pvalue))
if(T){
n <- nrow(rt)
nRow <- n+1
ylim <- c(1,nRow)
layout(matrix(c(1,2),nc=2),width=c(3,2))
#绘制森林图左边的基因信息
xlim = c(0,2.6)
par(mar=c(4,2.5,2,0))
plot(1,xlim=xlim,ylim=ylim,type="n",axes=F,xlab="",ylab="")
text.cex=1
text(0.5,n:1,gene,adj=0,cex=text.cex)
text(1.65,n:1,pVal,adj=1,cex=text.cex);
text(1.5+0.2,n+1,'P-value',cex=text.cex,font=2,adj=1)
text(2.6,n:1,Hazard.ratio,adj=1,cex=text.cex)
text(2.45,n+1,'HR (95% CI)',cex=text.cex,font=2,adj=1,)
#绘制森林图
par(mar=c(4,0,2,1),mgp=c(2,0.5,0))
xlim = c(0,6)
plot(1,xlim=xlim,ylim=ylim,type="n",axes=F,ylab="",xaxs="i",xlab="")
arrows(as.numeric(hrLow),n:1,as.numeric(hrHigh),n:1,angle=0,code=3,length=0.05,col="black",lwd=2.5)
abline(v=1,col="gray",lty=2,lwd=1.5)
boxcolor = '#67AB9F'
points(as.numeric(hr), n:1, pch = 15, cex=2,col = boxcolor)
axis(1)
}
library(export)
graph2pdf(file="inhouse-multicox.pdf", width = 10,height = 4.7)
# -------------------------------------------------------------------------
x <- summary(coxph(Surv(RFS.time,RFS)~.,my[,c(3,4,5:13)]))
y <- data.frame(id=rownames(x$coefficients),
HR=x$coefficients[,2],
HR.95L=x$conf.int[,"lower .95"],
HR.95H=x$conf.int[,'upper .95'],
pvalue=x$coefficients[,"Pr(>|z|)"])
y <- y[c(1:6,10,7:9),]
rt <- y
gene <- rt$id
hr <- sprintf("%.3f",rt$"HR")
hrLow <- sprintf("%.3f",rt$"HR.95L")
hrHigh <- sprintf("%.3f",rt$"HR.95H")
Hazard.ratio <- paste0(hr," (",hrLow,"-",hrHigh,")")
pVal <- ifelse(rt$pvalue<0.001, "<0.001", sprintf("%.3f", rt$pvalue))
if(T){
n <- nrow(rt)
nRow <- n+1
ylim <- c(1,nRow)
layout(matrix(c(1,2),nc=2),width=c(3,2))
#绘制森林图左边的基因信息
xlim = c(0,2.6)
par(mar=c(4,2.5,2,0))
plot(1,xlim=xlim,ylim=ylim,type="n",axes=F,xlab="",ylab="")
text.cex=1
text(0.5,n:1,gene,adj=0,cex=text.cex)
text(1.65,n:1,pVal,adj=1,cex=text.cex);
text(1.5+0.2,n+1,'P-value',cex=text.cex,font=2,adj=1)
text(2.6,n:1,Hazard.ratio,adj=1,cex=text.cex)
text(2.45,n+1,'HR (95% CI)',cex=text.cex,font=2,adj=1,)
#绘制森林图
par(mar=c(4,0,2,1),mgp=c(2,0.5,0))
xlim = c(0,5)
plot(1,xlim=xlim,ylim=ylim,type="n",axes=F,ylab="",xaxs="i",xlab="")
arrows(as.numeric(hrLow),n:1,as.numeric(hrHigh),n:1,angle=0,code=3,length=0.05,col="black",lwd=2.5)
abline(v=1,col="gray",lty=2,lwd=1.5)
boxcolor = '#67AB9F'
points(as.numeric(hr), n:1, pch = 15, cex=2,col = boxcolor)
axis(1)
}
graph2pdf(file="inhouse-multicox-rfs.pdf", width = 10,height = 4.7)
# -------------------------------------------------------------------------
# -------------------------------------------------------------------------
tt <- timeROC(my$OS.time,my$OS,my$RS,cause = 1,weighting = 'marginal',times = c(1,3,5),ROC = T)
tp <- tt$TP%>%as.data.frame()%>%pivot_longer(cols = 1:3,names_to = 'time',values_to = 'tp')
fp <- tt$FP%>%as.data.frame()%>%pivot_longer(cols = 1:3,names_to = 'time',values_to = 'fp')
dd <- tp
dd$fp <- fp$fp
dd$time <- ifelse(dd$time=='t=1',"1-Year = 0.840",
ifelse(dd$time=='t=3','3-Year = 0.776','5-Year = 0.818'))
ggplot(dd,aes(fp,tp,color=time))+
geom_line(size=1)+
labs(x='1-Specificity',y='Sensitivity',color=NULL)+
theme_bw(base_rect_size = 1.5)+
geom_abline(slope = 1,color='grey70')+
theme(panel.grid =element_blank(),
axis.text = element_text(size=11),
axis.title = element_text(size=13),
legend.text = element_text(size=12),
legend.position = c(0.995,0.012),
legend.justification = c(1,0))+
scale_color_nejm()+
scale_x_continuous(expand = c(0.01,0.01))+
scale_y_continuous(expand = c(0.01,0.01))
ggsave(filename = 'inhouse-timeROC.pdf',width = 4.3,height = 4)
# -------------------------------------------------------------------------
fit <- roc(x$RR,x$RS,auc=T)
dd <- data.frame(x=1-fit$specificities,y=fit$sensitivities)
dd <- dd[order(dd$y,dd$x),]
dd$AUC <- 'IRLS'
tmp <- dd
ggplot(tmp,aes(x,y))+
geom_line(aes(group=AUC))
tmp$AUC2 <- ifelse(tmp$AUC=='IRLS','IRLS= 0.897',ifelse(tmp$AUC=='PD-L1','PD-L1 = 0.686 ***','CD8A= 0.725 **'))
tmp$AUC2 <- factor(tmp$AUC2,levels = unique(tmp$AUC2))
ggplot(tmp,aes(x,y,color=AUC2))+
geom_line(size=1)+
labs(x='1-Specificity',y='Sensitivity',color=NULL)+
theme_bw(base_rect_size = 1.5)+
geom_abline(slope = 1,color='grey70')+
theme(panel.grid =element_blank(),
axis.text = element_text(size=11),
axis.title = element_text(size=13),
legend.text = element_text(size=12),
legend.position = c(0.995,0.012),
legend.justification = c(1,0))+
scale_color_nejm()+
scale_x_continuous(expand = c(0.01,0.01))+
scale_y_continuous(expand = c(0.01,0.01))
ggsave(filename = 'IC-inhouse-timeROC.pdf',width = 4.3,height = 4)
if(F){
plot.roc(fit,print.thres = T,print.auc = T)
pdf(file = 'IC-roc.pdf',width = 4,height = 4)
plot.roc(fit,
axes=T, ## 是否显示xy轴
legacy.axes=T,
main=NULL, ## Title
col= "steelblue", ## 曲线颜色
lty=1, ## 曲线形状
lwd=3, ## 曲线粗细
identity=T, ## 是否显示对角线
identity.col="grey60", ## 对角线颜色
identity.lty=2, ## 对角线形状
identity.lwd=2, ## 对角线粗细
print.thres=F, ## 是否输出cut-off值
print.thres.pch=20, ## cut-off点的形状
print.thres.col="red", ## cut-off点和文本的颜色
print.thres.cex=1.2,
print.auc=T, ## 是否显示AUC
print.auc.pattern="AUC = 0.896", ## 展示AUC的格式
auc.polygon.border='darkred',
print.auc.x=0.48, ## AUC值的X位置
print.auc.y=0.13, ## AUC值的Y位置
print.auc.cex=1.2, ## AUC值的放大倍数
print.auc.col='black', ## ACU值的颜色
auc.polygon=TRUE, ## 是否将ROC下面积上色
auc.polygon.col='skyblue',
max.auc.polygon=TRUE,
max.auc.polygon.col='WhiteSmoke',
max.auc.polygon.lty=1
)
dev.off()
}
# -------------------------------------------------------------------------
# -------------------------------------------------------------------------
library(plyr)
ggdata <- table(x$gg,x$RR)%>%as.data.frame()
ggdata2 <- ddply(ggdata,'Var1',transform,percent_Freq=Freq/sum(Freq)*100)
ggdata2 <- ddply(ggdata2,'Var1',transform,lable=cumsum(percent_Freq)-0.5*percent_Freq)
ggdata2$ll <- paste0(round(ggdata2$percent_Freq/100,2)*100,'%')
ggdata2$Var2 <- factor(ifelse(ggdata2$Var2==0,'NR','R'),levels = c('R','NR'))
ggplot(ggdata2,aes(Var1,percent_Freq,fill=Var2))+
geom_bar(stat = 'identity',width = 0.85)+
xlab(NULL)+ylab('Fraction (%)')+
geom_text(aes(label=ll),size=3.8,
position = position_stack(vjust = 0.5),
color='white')+
scale_fill_manual(values = pal_npg(alpha = 0.9)(2)[1:2])+
theme_classic()+
scale_x_discrete(expand = c(0.3,0.2))+
scale_y_continuous(expand = c(0.01,0.0))+
ggtitle('****')+
theme(legend.position = 'right',
plot.title = element_text(hjust=0.5,face = 'plain'),
axis.title = element_text(size=13),
axis.text.y = element_text(size=10),
axis.text.x = element_text(size=12))+
labs(fill=NULL)
ggsave(filename = 'IC-bar.pdf',height = 4,width = 3.2)
chisq.test(table(x$gg,x$RR))
# -------------------------------------------------------------------------
ggplot(x2,aes(reorder(ID,RS),RS,fill=Res))+
geom_bar(stat = 'identity',width = 0.7,color='grey30',position = position_dodge2(width = 0.9))+
scale_fill_nejm()+labs(y='IRLS score')+
theme_classic(base_rect_size = 2)+
theme(axis.line.x = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_blank(),
axis.title.x = element_blank(),
legend.title = element_blank(),
axis.text.y = element_text(size=12),
axis.title.y = element_text(size=13),
legend.text = element_text(size=12),
legend.position = c(0.01,1),
legend.justification = c(0,1))
# -------------------------------------------------------------------------
library(compareC)
tt <- my
dd <- data.frame()
for (i in colnames(my)[5:13]) {
fit <- summary(coxph(Surv(OS.time,OS)~get(i),tt))
CC <- fit$concordance[1]%>%as.numeric()
se <- fit$concordance[2]%>%as.numeric()
p <- compareC(tt$OS.time,tt$OS,tt$RS,tt[,i])$pval
dd <- rbind(dd,data.frame(ID=i,C=CC,SE=se,P=p))
}
ggplot(dd,aes(ID,C,fill=ID))+
geom_bar(stat='identity',position=position_dodge(0.8),width=0.6)+
geom_errorbar(aes(ymax=C+1.5*SE,ymin=C-1.5*SE),
width=0.1,position = position_dodge(0.8),size=0.6)+
theme_bw(base_rect_size = 1.5)+
ggtitle('C-index (Compared with IRLS)')+
theme(axis.title = element_blank(),
axis.text = element_text(size=12),
legend.position = 'none',
panel.grid = element_blank(),
plot.title = element_text(hjust = 0.5,size=14),
strip.text = element_text(size=12),
axis.ticks.x = element_blank())+
scale_fill_npg()+
scale_y_continuous(expand = c(0,0.01),limits = c(0,0.85))+
geom_text(aes(y=0.80,label=ll),size=5)