# secMalASCT survival calculation
#
# License: GPL version 3
# Jens Mathis Sauer (c) 2020

library(survival)
secmal <- read.csv2("current.csv", header=TRUE)

# Setup survival object
surv_dx <- Surv(time = secmal$event_time_dx, event = secmal$event_status)
surv_asct <- Surv(time = secmal$event_time_asct, event = secmal$event_status)

# plot survival after diagnosis
# scaled to years
png(filename = "survival_dx.png", width = 3000, height = 3000, res = 300)
plot(survfit(surv_dx ~ 1), mark.time = TRUE, xscale = 12, xlab = "Years", ylab = "Survival")
title("Kaplan-Meier estimate for\nsecMalASCT study", "Survival after diagnosis")
dev.off()

# One graph per sex
png(filename = "survival_dx_sex.png", width = 3000, height = 3000, res = 300)
plot(survfit(surv_dx ~ sex, data = secmal), mark.time = TRUE, xscale = 12, 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)
dev.off()

# plot survival after diagnosis
# scaled to years
png(file = "survival_asct.png", width = 3000, height = 3000, res = 300)
plot(survfit(surv_asct ~ 1), mark.time = TRUE, xscale = 12, xlab = "Years", ylab = "Survival")
title("Kaplan-Meier estimate for\nsecMalASCT study", "Survival after transplantation")
dev.off()

# One graph per sex
png(filename = "survival_asct_sex.png", width = 3000, height = 3000, res = 300)
plot(survfit(surv_asct ~ sex, data = secmal), mark.time = TRUE, xscale = 12, 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)
dev.off()