glioma {coin}R Documentation

Malignant Glioma Pilot Study

Description

A non-randomized pilot study on malignant glioma patients with pretargeted adjuvant radioimmunotherapy using Yttrium-90-biotin.

Usage

data("glioma")

Format

A data frame with 37 observations on the following 7 variables.

no.
patient number.
age
patients ages in years.
sex
a factor with levels F(emale) and M(ale).
histology
a factor with levels GBM (grade IV) and Grade3 (grade III)
time
survival times in month.
event
censoring indicator: FALSE censored and TRUE dead.
group
a factor with levels Control and RIT.

Details

The primary endpoint of this small pilot study is survival. Survival times are tied, the usual asymptotic log-rank test may be inadequate in this setup. Therefore, a permutation test (via Monte-Carlo sampling) was conducted in the original paper. The data are taken from Tables 1 and 2 of Grana et al. (2002).

Source

C. Grana, M. Chinol, C. Robertson, C. Mazzetta, M. Bartolomei, C. De Cicco, M. Fiorenza, M. Gatti, P. Caliceti & G. Paganelli (2002), Pretargeted adjuvant radioimmunotherapy with Yttrium-90-biotin in malignant glioma patients: A pilot study. British Journal of Cancer 86(2), 207–212.

Examples


data("glioma", package = "coin")

par(mfrow=c(1,2))

### Grade III glioma
g3 <- subset(glioma, histology == "Grade3")

### Plot Kaplan-Meier curves
plot(survfit(Surv(time, event) ~ group, data=g3), 
     main="Grade III Glioma", lty=c(2,1), 
     legend.text=c("Control", "Treated"),
     legend.bty=1, ylab="Probability", 
     xlab="Survival Time in Month")

### logrank test
surv_test(Surv(time, event) ~ group, data = g3, 
             distribution = "exact")

### Grade IV glioma
gbm <- subset(glioma, histology == "GBM")

### Plot Kaplan-Meier curves
plot(survfit(Surv(time, event) ~ group, data=gbm), 
     main="Grade IV Glioma", lty=c(2,1), 
     legend.text=c("Control", "Treated"),
     legend.bty=1, legend.pos=1, ylab="Probability", 
     xlab="Survival Time in Month")
   
### logrank test
surv_test(Surv(time, event) ~ group, data = gbm, 
             distribution = "exact")

### stratified logrank test
surv_test(Surv(time, event) ~ group | histology, data = glioma,
             distribution = approximate(B = 10000))


[Package coin version 0.4-6 Index]