在调整生存模型后用ggplot2绘制变量的所有时间风险

Question

我正在使用生存分析和smoothHR包，在建模之后我想绘制相对风险与变量之间的关系，这很容易用

plot(dataset, predictor)

但是我想使用ggplot包来做。知道怎么做？

#the library
library(smoothHR)

#the artificial dataset
surv.days<- runif(n = 200, min = 100, max = 500)
censor<- sample(c(0,1), 200, replace=TRUE)
surv.var<- surv.days/10 + rnorm(200, mean = 0, sd = 3)
surv.var[which(surv.days>250)]<- surv.days[which(surv.days>250)]/5 + rnorm(length(which(surv.days>250)), mean = 0, sd = 10)

survdata<- data.frame(surv.days, censor, surv.var)

rm(censor, surv.days, surv.var)

#using smoothHR package to adjust a model
variabledf<-dfmacox (time = "surv.days", status = "censor",
                    nl.predictor = c ("surv.var"),
                    smoother = "ns",
                    method = "AIC",
                    data = survdata)

coxmodel<- coxph(Surv(surv.days, censor) ~ ns(surv.var, variabledf$df[1]), data = survdata, x = TRUE)

c.smoothhr<-smoothHR (data = survdata, coxfit = coxmodel)

之后，我可以将风险绘制为生存变量的函数

plot (c.smoothhr, predictor = "surv.var", conf.level = 0.95, ref.label = "", main = "", xlab = "surv.var")

我想使用ggplot2包生成这个图，用于存储和定制目的;但我对如何继续下去一无所知。