I am new to survival analysis in R. I saw that my collegues managed to find drug retention rates at specific time intervals (6 month, 12 month, 24 month) with 95% CI. How would I do this?
Here is a reproducible example:
library(survival)
library(survminer)
gender <- as.factor(c("Female", "Male", "Female", "Male", "Male", "Male", "Female", "Female", "Female", "Male"))
country <- as.factor(c("US", "US", "GB", "GB", "GB", "US", "GB", "US", "GB", "US"))
time <- c(5, 10, 12, 15, 20, 9, 14, 18, 24, 20)
event <- c(1, 1, 1, 1, 1, 0, 0, 1, 0, 1)
df <- data.frame(gender, country, time, event)
km.model <- survfit(Surv(time = df$time, event = df$event) ~ gender, data = df)
km.model
ggsurvplot (km.model, data = df, conf.int = TRUE, risk.table = "abs_pct", xlab = "Time in months")
Thanks in advance!
You could use summary with the needed time intervals:
this will give the needed CI's.
summary(km.model, times = seq(0, 24, 6))
output:
gender=Female
time n.risk n.event survival std.err lower 95% CI upper 95% CI
0 5 0 1.0 0.000 1.0000 1
6 4 1 0.8 0.179 0.5161 1
12 4 1 0.6 0.219 0.2933 1
18 2 1 0.3 0.239 0.0631 1
24 1 0 0.3 0.239 0.0631 1
gender=Male
time n.risk n.event survival std.err lower 95% CI upper 95% CI
0 5 0 1.00 0.000 1.000 1
6 5 0 1.00 0.000 1.000 1
12 3 1 0.75 0.217 0.426 1
18 2 1 0.50 0.250 0.188 1