Description Usage Format References Examples
The dataset is extracted from a published Kaplan Meier image by ScanIt software. Locoreginal control events
were studied in 424 head and neck cancer patients: 213 in Radiotherapy treatment group and 211 in the Radiotherapy plus cetuximab group.
There are 145 pairs of coordinates extracted from the radiation treatment arm, and 136 pairs of coordinates are extracted from the radiation
plus arm. For both datasets, the first columns are the times, and the second columns are the survival rates at those time points(in percentage).
For each group, there are six patients numbers at risk reported at the months of 0, 10, 20, 30, 40, and 50. Three vectors (i.e., trisk, nrisk.radio and
nrisk.radioplus) record those numbers.
1 |
List of two dataframes (radio and radioplus) and three vectors
Bonner JA, Harari PM, Giralt J, Azarnia N, Shin DM, Cohen RB, Jones CU, Sur R, Raben D, Jassem J, Ove R, Kies MS, Baselga J, Youssoufian H, Amellal N, Rowinsky EK, Ang KK: Radiotherapy plus Cetuximab for Squamous-Cell Carcinoma of the Head and Neck. N Engl J Med. 2006, 354: 567-78. 10.1056/NEJMoa053422.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | radio <- Radiationdata$radio
radioplus <- Radiationdata$radioplus
trisk <- Radiationdata$trisk
nrisk_radio <- Radiationdata$nrisk.radio
nrisk_radioplus <- Radiationdata$nrisk.radioplus
plot(radio,xlab="time",ylab="survival rates",type="l",
lty=2,col="cyan4",xlim=c(1,70),main="Curves extracted by ScanIt software")
lines(radioplus,type="l",col="red4",lty=1)
legend("topright", c("Radiotherapy", "Radiotherapy plus cetuximab"),
col = c("cyan4","red4"),lty=c(2,1),text.col = "green4")
text(40,80,"Reported Hazard Ratio with 95% CI: 0.69 (0.52,0.89)")
pre_radio <- preprocess(dat=radio, trisk=trisk,nrisk=nrisk_radio,maxy=100)
est_radio <- getIPD(prep=pre_radio,armind=0,tot.events=NULL)
pre_radio_plus <- preprocess(dat=radioplus, trisk=trisk,nrisk=nrisk_radioplus,maxy=100)
est_radio_plus <- getIPD(prep=pre_radio_plus,armind=1,tot.events=NULL)
library(survival)
library(survminer)
mixdat <- rbind(est_radio$IPD,est_radio_plus$IPD)
coxfit <- coxph(Surv(time,status)~treat,data=mixdat)
fit <- survfit(Surv(time, status) ~ treat,data = mixdat)
ggsurvplot(fit, data = mixdat, risk.table = TRUE)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.