Kaplan-Meier plots are the most popular graphical displays of time-to-event (survival) data, because they give an intuitive and concise overview of survival over time.
In this tutorial we run through a short example using the survminer package to obtain a well annotated Kaplan-Meier plot, which includes:
- a legend with proper group labels
- the log rank test p-value for testing differences in survival between the treatment groups
- the at-risk table indicating the number of patients in each group at different time points.
Check below the video for an easy option to download this R code, which will save you a lot of time!
The output will look like this:
Check out this quick and easy video for a step-by-step guide on how to produce this graphic in R:
Note: If you are looking for more details on how to use ggsurvplot() from the survminer package check out these helpful vignettes maintained by the package author:
https://cran.r-project.org/web/packages/survminer/vignettes/Informative_Survival_Plots.html
https://cran.r-project.org/web/packages/survminer/vignettes/Playing_with_fonts_and_texts.html