ggsurvplot and ggplot lattice ?! Plotting kaplan-meier curve with cumulative incidence function

I would like to plot a kaplan meier curve (KM) and cumulative events or cumulative incidence function (CIF) in one plot as a lattice.

I have switched recently from SAS to R, and in SAS you can do it all in one step using a macro (See this image), but I couldn't find something similar in R yet.

enter image description here

Currently, I run a code for two separate graphs. The first plots survfit object using ggsurvplot which results in a KM curve, While the second plots a cuminc object after a number of transformations using ggplot. ggcompetingrisks was not very optimizable, so I don't use it. Also I am interested in plotting one certain competing risk for example death from cancer, and not all competing risks.

Here is an example of my current code using the BMT data-frame from the survminer package.

library(survminer)
library(cmprsk)
data(BMT)

# I'll add the variable Death to plot overall survival.
BMT <- mutate(BMT, death = ifelse (status == 1, 1, 0))

# KM plot:
figKM <- ggsurvplot(survfit(Surv(ftime, death) ~ dis, BMT))
figKM

# CIF plot:
cif <- cuminc(ftime = BMT$ftime, fstatus = BMT$status, group = BMT$dis, cencode = 0)
cifDT <- cif %>% 
  list_modify("Tests" = NULL) %>% 
  map_df(`[`, c("time", "est"), .id = "id")  %>% 
  filter(id %in% c("0 1","1 1")) # to keep the incident I want

figCIF <- ggplot (cifDT, aes(x = time, y = est, color = id)) + geom_step(lwd = 1.2)
figCIF

is there a way to put figKM and figCIF together in a lattice plot? May by plotting them differently?

Solution

If you look at the contents of your figKM object with class and str you see that the first item in that list is a "plot", so this seems to do what you asked for in your comment:

 library(cowplot)
 plot_grid(figKM[[1]], figKM[[1]], nrow = 2)

I'm not a tidyverse-user so the map_df is perhaps some clone of the base function Reduce or Map but I don't have enough experience to a) know which package to load, or b) have the ability to figure out what is being done with your piped expressions. Commented code might have been more understandable. I am quite experienced with the survival package.