jsauer/secmalasct
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

survival: Change plot function to ggsurvplot

Browse Source 
This will create the plot using the ggsurvplot from "survminer" package.
survminer user ggplot for plotting and comes with some powerful and nice
looking features.
This commit is contained in:
Jens Sauer 2020-11-16 23:22:45 +01:00
parent b5634b7f8f
commit 12ffcd4e38
3 changed files with 26 additions and 21 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
README.md
View File

@ -4,3 +4,4 @@ secMalASCT statistical analysis
R packages used
---------------
* tidyverse
* survminer

37
survival.R
View File

@ -4,6 +4,7 @@
# Jens Mathis Sauer (c) 2020
library(survival)
library(survminer)
source("utils.R")
secmal <- sma_load_data("current.csv")
@ -14,38 +15,34 @@ surv_asct <- Surv(time = secmal$event_time_asct, event = secmal$event_status)
# plot survival after diagnosis
sma_plot_surv_dx <- function() {
plot(survfit(surv_dx ~ 1), mark.time = TRUE, xscale = 365.25,
xlab = "Years", ylab = "Survival")
title("Kaplan-Meier estimate for\nsecMalASCT study",
"Survival after diagnosis")
ggsurvplot(survfit(surv_dx ~ 1), data = secmal, xscale = "d_y",
title = "Survival after diagnosis",
break.time.by = 5 * 365.25)
}
# plot survival after diagnosis per sex
sma_plot_surv_dx_sex <- function() {
plot(survfit(surv_dx ~ sex, data = secmal), mark.time = TRUE,
xscale = 365.25, xlab = "Years", ylab = "Survival",
lty = 2:3)
title("Kaplan-Meier estimate for\nsecMalASCT study",
"Survival after diagnosis")
legend(100, .9, c("Female", "Male"), lty = 2:3)
ggsurvplot(survfit(surv_dx ~ sex, data = secmal), data = secmal,
xscale = "d_y", title = "Survival after diagnosis",
legend.labs = c("Female", "Male"),
break.time.by = 5 * 365.25,
pval = TRUE)
}
# plot survival after transplantation
sma_plot_surv_asct <- function() {
plot(survfit(surv_asct ~ 1), mark.time = TRUE, xscale = 365.25,
xlab = "Years", ylab = "Survival")
title("Kaplan-Meier estimate for\nsecMalASCT study",
"Survival after transplantation")
ggsurvplot(survfit(surv_asct ~ 1), data = secmal, xscale = "d_y",
title = "Survival after transplantation",
break.time.by = 5 * 365.25)
}
# plot survival after transplantation per sex
sma_plot_surv_asct_sex <- function() {
plot(survfit(surv_asct ~ sex, data = secmal), mark.time = TRUE,
xscale = 365.25, xlab = "Years", ylab = "Survival",
lty = 2:3)
title("Kaplan-Meier estimate for\nsecMalASCT study",
"Survival after transplantation")
legend(100, .9, c("Female", "Male"), lty = 2:3)
ggsurvplot(survfit(surv_asct ~ sex, data = secmal), data = secmal,
xscale = "d_y", title = "Survival after transplantation",
legend.labs = c("Female", "Male"),
break.time.by = 5 * 365.25,
pval = TRUE)
}
#

9
utils.R
View File

@ -17,7 +17,14 @@ sma_plot_file <- function(fname, ftype, fun) {
# Open file for writing
ftype(filename = fname, width = 3000, height = 3000, res = 300)
fun()
#
# Write plot into variable, then printing it manually. This is
# needed to save plots from package "survminer" at the moment.
#
# See: https://github.com/kassambara/survminer/issues/152
#
p <- fun()
print(p)
# hide "null device 1" in garbage
garbage <- dev.off()