How to change the y axis scale of ggsurvplot with very few events-CodePudding

## KAPLAN MEIER
fit.obj<-survfit(Surv(duree_suivi,k_oesogastr) ~ baria_t, data = pts_raw_matched)
library(survminer)

I am comparing two curves. But the number of events is so low that you can't see the curves very well. I want to truncate the y-axis (between 0.9 and 1 for example) to see the evolution of the two curves.

                    n events median 0.95LCL 0.95UCL
baria_t=Sleeve 114221     61     NA      NA      NA
baria_t=Bypass 114221     58     NA      NA      NA

ggsurvplot(fit.obj,
           conf.int = T,
           risk.table ="absolute",
           tables.theme = theme_cleantable())

Here are the survival curves:

CodePudding user response：

If we use some simulated data we can replicate your problem:

set.seed(1)

pts_raw_matched <- data.frame(
  duree_suivi = c(runif(114221, 0, 25000),runif(114221, 0, 26000)),
  baria_t = rep(c('Sleeve', 'Bypass'), each = 114221)
)
pts_raw_matched$k_oesogastr <- as.numeric(pts_raw_matched$duree_suivi < 15)
pts_raw_matched$duree_suivi[pts_raw_matched$duree_suivi > 15] <- 15

Now we should have a data set with the same names and approximately the same characteristics as your own data.

We start by creating the plot using your own code, but storing the result:

fit.obj <- survfit(Surv(duree_suivi,k_oesogastr) ~ baria_t, 
                   data = pts_raw_matched)

ggs <- ggsurvplot(fit.obj,
           conf.int = T,
           risk.table ="absolute",
           tables.theme = theme_cleantable()) 

ggs

In order to change the y axis, we need to set the ylim of the plot component of the ggs object. In this case, we need to set the limits between 0.999 and 1 to be able to properly compare the curves:

ggs$plot <- ggs$plot   ylim(c(0.999, 1))

ggs

CodePudding user response：

you can add argument ylim=c(0.999, 1) directly in the call to ggsurvplot:

ggsurvplot(fit.obj,
           conf.int = T,
           risk.table ="absolute",
           tables.theme = theme_cleantable(),
           ylim=c(0.999, 1))

You can do the same for xlim