diff --git a/README.md b/README.md
index 4e984b1..ceeb332 100644
--- a/README.md
+++ b/README.md
@@ -4,3 +4,4 @@ secMalASCT statistical analysis
 R packages used
 ---------------
 * tidyverse
+* survminer
diff --git a/survival.R b/survival.R
index 3d275c4..49535fc 100644
--- a/survival.R
+++ b/survival.R
@@ -4,6 +4,7 @@
 # Jens Mathis Sauer (c) 2020
 
 library(survival)
+library(survminer)
 source("utils.R")
 
 secmal <- sma_load_data("current.csv")
@@ -14,38 +15,46 @@ 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,
+		   surv.median.line = "hv",
+		   risk.table = "abs_pct",
+		   ggtheme = theme_bw())
 }
 
 # 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,
+		   surv.median.line = "hv",
+		   risk.table = "abs_pct",
+		   ggtheme = theme_bw(),
+		   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,
+		   surv.median.line = "hv",
+		   risk.table = "abs_pct",
+		   ggtheme = theme_bw())
 }
 
 # 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,
+		   surv.median.line = "hv",
+		   risk.table = "abs_pct",
+		   ggtheme = theme_bw(),
+		   pval = TRUE)
 }
 
 #
diff --git a/utils.R b/utils.R
index 2972992..9ca0719 100644
--- a/utils.R
+++ b/utils.R
@@ -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()