fit <- survfit(Surv(time, status) ~ sex, data=lung)
p1 <- ggsurvplot(fit)
p2 <- ggsurvplot(fit, data = lung,
surv.median.line = "hv", #添加中位生存曲线
palette=c("red", "blue"), #更改线的颜色
legend.labs=c("Sex1","Sex2"), #标签
legend.title="Treatment",
title="Overall survival", #标题
ylab="Cumulative survival (percentage)",xlab = " Time (Days)", #更改横纵坐标
censor.shape = 124,censor.size = 2,conf.int = FALSE, #删失点的形状和大小
break.x.by = 100#横坐标间隔
)
p3 <- ggsurvplot(fit, data = lung,
surv.median.line = "hv", #添加中位生存曲线
palette=c("red", "blue"),
legend.labs=c("Sex1","Sex2"), #标签
legend.title="Treatment",
title="Overall survival",
ylab="Cumulative survival (percentage)",xlab = " Time (Days)", #更改横纵坐标
censor.shape = 124,censor.size = 2,conf.int = FALSE,
break.x.by = 100,
risk.table = TRUE,tables.height = 0.2,
tables.theme = theme_cleantable(),
ggtheme = theme_bw())
P4 <- ggsurvplot(fit, data = lung,
pval = TRUE,#添加P值
pval.coord = c(0, 0.03), #调节Pval的位置
surv.median.line = "hv", #添加中位生存曲线
palette=c("red", "blue"),
legend.labs=c("Sex1","Sex2"), #标签
legend.title="Treatment",
title="Overall survival",
ylab="Cumulative survival (percentage)",xlab = " Time (Days)", #更改横纵坐标
censor.shape = 124,censor.size = 2,conf.int = FALSE,
break.x.by = 100,
risk.table = TRUE,tables.height = 0.2,
tables.theme = theme_cleantable(),
ggtheme = theme_bw())
###添加COX回归hazard ratio值相关信息
res_cox<-coxph(Surv(time, status) ~sex, data=lung)
p3$plot = p3$plot + ggplot2::annotate("text",x = 50, y = 0.15,
label = paste("HR :",round(summary(res_cox)$conf.int[1],2))) + ggplot2::annotate("text",x = 50, y = 0.10,
label = paste("(","95%CI:",round(summary(res_cox)$conf.int[3],2),"-",round(summary(res_cox)$conf.int[4],2),")",sep = ""))+
ggplot2::annotate("text",x = 50, y = 0.05,
label = paste("P:",round(summary(res_cox)$coef[5],4)))
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