How to change the y-axis of the censoring table in ggsurvplot in R?-CodePudding

The ggsurvplot function from the package survminer allows users to draw Kaplen-Meier curves. It also allows us to create a table beneath the plot with the number of censored observations by configuring the ncensor.plot value. My question is: how does one change the y-axis of the censored table beneath the plot? The reason is I have a study termination at for example 52 weeks, and therefore the amount of censored observations is high, skewing the table completely. See the example below.

#Create a random dataset with gender, event, time
set.seed(100)
time <- rnorm(n = 100, mean = 52, sd = 20)
set.seed(150)
gender <- sample(x = c(0, 1), prob = c(.6, .4), size = 100, replace = TRUE)
set.seed(100)
event <- sample(x = c(0, 1), prob = c(.4, .6), size = 100, replace = TRUE)
dat <- data.frame(time, gender, event)

#Censor time after 52 weeks
dat <- dat %>% mutate(time_adjusted = if_else(time > 52, 52, time))

#KM-estimator
survObject <- Surv(time = dat$time_adjusted, event = dat$event)
km.model <- survfit(survObject ~ gender, data = dat)
summary(km.model)

Call: survfit(formula = survObject ~ gender, data = dat)

                gender=0 
     time n.risk n.event survival   std.err lower 95% CI upper 95% CI
  6.56149     61       1 0.983607 0.0162585     0.952251     1.000000
 14.42688     58       1 0.966648 0.0231936     0.922242     1.000000
 28.42634     56       1 0.949386 0.0284876     0.895162     1.000000
 28.84541     54       1 0.931805 0.0329415     0.869427     0.998658
 28.84858     53       1 0.914224 0.0367130     0.845027     0.989087
 33.72372     52       1 0.896643 0.0399957     0.821581     0.978562
 35.49481     51       1 0.879061 0.0429020     0.798871     0.967301
 35.71242     50       1 0.861480 0.0455040     0.776755     0.955446
 37.73950     48       1 0.843533 0.0479650     0.754572     0.942981
 41.95615     45       1 0.824787 0.0504291     0.731641     0.929793
 43.23820     44       1 0.806042 0.0526518     0.709180     0.916135
 44.22292     43       1 0.787297 0.0546624     0.687131     0.902065
 48.84190     40       1 0.767615 0.0567288     0.664106     0.887257
 49.24141     39       1 0.747932 0.0585893     0.641480     0.872050
 50.42166     36       1 0.727156 0.0605334     0.617686     0.856027
 50.60166     35       1 0.706380 0.0622672     0.594300     0.839599
 51.00008     34       1 0.685605 0.0638078     0.571287     0.822798
 52.00000     33      21 0.249311 0.0619235     0.153222     0.405659

                gender=1 
    time n.risk n.event survival   std.err lower 95% CI upper 95% CI
 10.5119     39       1 0.974359 0.0253102     0.925994     1.000000
 17.2280     37       1 0.948025 0.0357936     0.880404     1.000000
 24.0235     36       1 0.921691 0.0434190     0.840402     1.000000
 28.7516     35       1 0.895357 0.0495247     0.803367     0.997880
 30.7129     33       1 0.868225 0.0549558     0.766927     0.982903
 34.1409     32       1 0.841093 0.0595606     0.732095     0.966319
 35.2230     31       1 0.813961 0.0635192     0.698519     0.948482
 35.3501     30       1 0.786829 0.0669463     0.665973     0.929616
 43.0588     26       1 0.756566 0.0708822     0.629649     0.909066
 43.2310     25       1 0.726303 0.0742265     0.594466     0.887379
 44.8028     24       1 0.696041 0.0770563     0.560275     0.864706
 46.7601     23       1 0.665778 0.0794266     0.526965     0.841157
 47.9673     21       1 0.634074 0.0817272     0.492524     0.816307
 49.9674     20       1 0.602371 0.0835642     0.458966     0.790583
 50.1777     18       1 0.568906 0.0853600     0.423959     0.763408
 52.0000     15       8 0.265489 0.0834090     0.143425     0.491439

#KM-curves
ggsurvplot(km.model, data = dat, ggtheme = theme_bw(), conf.int = TRUE, risktable = "abs_pct", ncensor.plot = TRUE,
           xlab = "Time in weeks", ylab = "Survival", xlim = c(0,52), break.x.by = 13)

Output of the graph

CodePudding user response：

The object returned by ggsurvplot is a list which contains the main plot as an element called plot and the censored table plot as an element named ncensor.plot. Both of which are ggplot objects and can therefore be tweaked using default ggplot options. As an example in my code below I use scale_y_continuous to change the breaks of the y scale for the censored table plot:

library(survminer)
library(survival)
library(dplyr)

p <- ggsurvplot(km.model, data = dat, ggtheme = theme_bw(), conf.int = TRUE, risktable = "abs_pct", ncensor.plot = TRUE,
           xlab = "Time in weeks", ylab = "Survival", xlim = c(0,52), break.x.by = 13)

p$ncensor.plot <- p$ncensor.plot   scale_y_continuous(breaks = seq(12))
#> Scale for 'y' is already present. Adding another scale for 'y', which will
#> replace the existing scale.

p

EDIT The limits of the x axis could be set using the limits argument, where I also have set the breaks according to ones set by ggsurvplot by default, except for the 52 which I replaced by 51:

p$ncensor.plot <- p$ncensor.plot   
  scale_y_continuous(breaks = seq(12))   
  scale_x_continuous(breaks = c(0, 13, 26, 39, 51), limits = c(NA, 51))

p