How to overlay survival plot - r

Question

I would to overlay two different survival curves on same plot, for example OS et PFS (here false results).
N pt. OS. OS_Time_(years). PFS. PFS_Time_(years).
__________________________________________________________________
1. 1 12 0 12
2. 0 10 1 8
3. 0 14 0 14
4. 0 10 0 10
5. 1 11 1 8
6. 1 16 1 6
7. 0 11 1 4
8. 0 12 1 10
9. 1 9 0 9
10 1 10 1 9
__________________________________________________________
First, I import my dataset:
library(readxl)
testR <- read_excel("~/test.xlsx")
View(testR)
Then, I created survfit for both OS and PFS:
OS<-survfit(Surv(OS_t,OS)~1, data=test)
PFS<-survfit(Surv(PFS_t,PFS)~1, data=test)
And finally, I can plot each one thanks to:
plot(OS)
plot(PFS)
for example (or ggplot2...).
Here my question, if I want to overlay the 2 ones on same graph, how can I do?
I tried multipleplot or
ggplot(testR, aes(x)) + # basic graphical object
geom_line(aes(y=y1), colour="red") + # first layer
geom_line(aes(y=y2), colour="green") # second layer
But it didn't work (but I'm not sure to use it correctly).
Can someone help me, please ?
Thanks a lot
Here is my code for Data sample:
test <- structure(list(ID = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 2, 3, 4, 5, 6, 7, 8, 9),
Sex = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1),
Tabac = c(2, 0, 1, 1, 0, 0, 2, 0, 0, 0, 1, 1, 1, 0, 2, 0, 1, 1, 1),
Bmi = c(20, 37, 37, 25, 28, 38, 16, 27, 26, 28, 15, 36, 20, 17, 28, 37, 27, 26, 18),
Age = c(75, 56, 45, 65, 76, 34, 87, 43, 67, 90, 56, 37, 84, 45, 80, 87, 90, 65, 23), c(0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0),
OS_times = c(2, 4, 4, 2, 3, 5, 5, 3, 2, 2, 4, 1, 3, 2, 4, 3, 4, 3, 2),
OS = c(0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0),
PFS_time = c(1, 2, 1, 1, 3, 4, 3, 1, 2, 2, 4, 1, 2, 2, 2, 3, 4, 3, 2),
PFS = c(1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0)),
.Names = c("ID", "Sex", "Tabac", "Bmi", "Age", "LN", "OS_times", "OS", "PFS_time", "PFS"),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -19L))

Answer 1

You may use the ggsurv function from the GGally package in the following way. Combine both groups of variables in a data frame and add a "type" column. Later in the call to the plot, you refer to the type.
I used your data structure and named it "test". Afterwards, I transformed it to a data frame with the name "testdf".
library(GGally)
testdf <- data.frame(test)
OS_PFS1 <- data.frame(life = testdf$OS, life_times = testdf$OS_times, type= "OS")
OS_PFS2 <- data.frame(life = testdf$PFS, life_times = testdf$PFS_time, type= "PFS")
OS_PFS <- rbind(OS_PFS1, OS_PFS2)
sf.OS_PFS <- survfit(Surv(life_times, life) ~ type, data = OS_PFS)
ggsurv(sf.OS_PFS)
if you want the confidence intervals shown:
ggsurv(sf.OS_PFS, CI = TRUE)
Please let me know whether this is what you want.