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


  layout(matrix(1:2, ncol = 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 1.0-24 Index]