用ggplot2绘制R中的生存曲线

Question

我一直在寻找使用ggplot2绘制生存曲线的解决方案.我发现了一些不错的例子,但它们并没有遵循整个ggplot2美学(主要是关于阴影置信区间等).所以最后我写了自己的函数:

ggsurvplot<-function(s, conf.int=T, events=T, shape="|", xlab="Time", 
                  ylab="Survival probability", zeroy=F, col=T, linetype=F){

#s: a survfit object.
#conf.int: TRUE or FALSE to plot confidence intervals.
#events: TRUE or FALSE to draw points when censoring events occur
#shape: the shape of these points
#zeroy: Force the y axis to reach 0
#col: TRUE, FALSE or a vector with colours. Colour or B/W
#linetype: TRUE, FALSE or a vector with line types.

require(ggplot2)
require(survival)

if(class(s)!="survfit") stop("Survfit object required")

#Build a data frame with all the data
sdata<-data.frame(time=s$time, surv=s$surv, lower=s$lower, upper=s$upper)
sdata$strata<-rep(names(s$strata), s$strata)

#Create a blank canvas
kmplot<-ggplot(sdata, aes(x=time, y=surv))+
    geom_blank()+
    xlab(xlab)+
    ylab(ylab)+
    theme_bw()

#Set color palette
if(is.logical(col)) ifelse(col,
                         kmplot<-kmplot+scale_colour_brewer(type="qual", palette=6)+scale_fill_brewer(type="qual", palette=6),
                         kmplot<-kmplot+scale_colour_manual(values=rep("black",length(s$strata)))+scale_fill_manual(values=rep("black",length(s$strata)))
                        )
else kmplot<-kmplot+scale_fill_manual(values=col)+scale_colour_manual(values=col)

#Set line types
if(is.logical(linetype)) ifelse(linetype,
                              kmplot<-kmplot+scale_linetype_manual(values=1:length(s$strata)),
                              kmplot<-kmplot+scale_linetype_manual(values=rep(1,  length(s$strata)))
                              )
else kmplot<-kmplot+scale_linetype_manual(values=linetype)

#Force y axis to zero
if(zeroy) {
    kmplot<-kmplot+ylim(0,1)
}

#Confidence intervals
if(conf.int) {  

    #Create a data frame with stepped lines
    n <- nrow(sdata)
    ys <- rep(1:n, each = 2)[-2*n] #duplicate row numbers and remove the last one
    xs <- c(1, rep(2:n, each=2))   #first row 1, and then duplicate row numbers
    scurve.step<-data.frame(time=sdata$time[xs], lower=sdata$lower[ys], upper=sdata$upper[ys],  surv=sdata$surv[ys], strata=sdata$strata[ys])

    kmplot<-kmplot+
      geom_ribbon(data=scurve.step, aes(x=time,ymin=lower, ymax=upper, fill=strata), alpha=0.2)
}

#Events
if(events) {
    kmplot<-kmplot+
      geom_point(aes(x=time, y=surv, col=strata), shape=shape)
}

#Survival stepped line
kmplot<-kmplot+geom_step(data=sdata, aes(x=time, y=surv, col=strata, linetype=strata))

#Return the ggplot2 object
kmplot
}

我为每个阶层编写了一个使用for循环的先前版本,但速度较慢.因为我不是程序员,所以我会寻求改进功能的建议.可能会为患有风险的患者添加数据表,或者在ggplot2框架中更好地集成.

谢谢

Answer 1

对于CI之间带阴影区域的内容,您可以尝试以下操作:

(我在这里使用的是开发版本,因为alpha生产版本中的参数存在缺陷(对于非默认值,没有正确地遮盖上部矩形).否则函数是相同的).

library(devtools)
dev_mode(TRUE) # in case you don't want a permanent install
install_github("survMisc", "dardisco")
library("survMisc", lib.loc="C:/Users/c/R-dev") # or wherever you/devtools has put it
data(kidney, package="KMsurv")
p1 <- autoplot(survfit(Surv(time, delta) ~ type, data=kidney),
               type="fill", survSize=2, palette="Pastel1",
               fillLineSize=0.1, alpha=0.4)$plot
p1 + theme_classic()
dev_mode(FALSE)

赠送:

而对于经典情节和表格:

autoplot(autoplot(survfit(Surv(time, delta) ~ type, data=kidney),
                  type="CI"))

见?survMisc::autoplot.survfit和?survMisc::autoplot.tableAndPlot更多的选择.