survminer | Survival Analysis and Visualization | Data Visualization library

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.

I have got survival data, based on quartiles of delta_mon1_baselone_to_3d. Outcomes is mace.

Cox regression for each quartile are obtained with this code:

I am looking to customise my ggsurvplot title by making one word in it be in italics. I have tried the more 'classic' code that words in ggplots, but they don't appear to work in this.

Here is an example of what I am doing:

I have a dataset consisting in observations of the developmental time and survival of an insect.

Developmental time is the time in days between egg exclosure and adult emergence, while survival of adults is the time between adult emergence and death (or censoring).

In my analysis, I am plotting a Kaplan-Meier reversed survival curve (ggsurvplot(survfit_obj, fun = "event")) for developmental time, while for adult survival I am using a classical Kaplan-Meier curve.

Since I have these two time-to-event variables for every unique individual, I am wondering if there is the possibility to horizontally merge the two resulting Kaplan-Meier curves into a single comprehensive one, or eventually with a different estimator.

Actually, I am not even sure if it has a solid statistical meaning, it just graphically make sense (see last figure).

Keep in mind that the two time-to-events variables are substantially different, they are not representing a single recurrent event.

Below you can find my reproducible example.

Variable legend:

• treat -> treatment

• days2emerge -> days from egg to adult

• new.ad = 1 -> successful adult emergence

• days2event -> days from adult emergence to death/censoring

• days2event = 1 -> adult death

• days2event = 0 -> adult censoring

How to replace the default geom_ribbon with geom_errorbar in ggcompetingrisks from survminer package?

conf.int = T will put confidence interval as a ribbon layer.

my code:

To generate p-values for the differences between two survival curves, I need to perform a tedious series of steps, which need to be repeated with all combinations of two out of three values that are represented in one column of the starting data frame, say groups A, B and C:

I want to create a KM curve with 95%-CI with the x-axis zoomed in to show values between 0-60 months. This all works fine with ggsurvplot untill I use xlim.

Hello I am using the survival package and the survminer package to do some analysis. I am having trouble with pairwise_survdiff from the survminer package.

Here is some simulated data that mimics my own.

I am new to survival analysis in R. I saw that my collegues managed to find drug retention rates at specific time intervals (6 month, 12 month, 24 month) with 95% CI. How would I do this?

Here is a reproducible example: