casebase (version 0.1.0)

ERSPC: Data on the men in the European Randomized Study of Prostate Cancer Screening

Description

This data set lists the individual observations for 159,893 men in the core age group between the ages of 55 and 69 years at entry.

Usage

ERSPC

Format

A data frame with 159,893 observations on the following 3 variables:

ScrArm

Whether in Screening Arm (1) or non-Screening arm (0) [numeric]

Follow.Up.Time

The time, measured in years from randomization, at which follow-up was terminated

DeadOfPrCa

Whether follow-up was terminated by Death from Prostate Cancer (1) or by death from other causes, or administratively (0)

Details

The men were recruited from seven European countries (centres). Each centre began recruitment at a different time, ranging from 1991 to 1998. The last entry was in December 2003. The uniform censoring date was December 31, 2006. The randomization ratio was 1:1 in six of the seven centres. In the seventh, Finland, the size of the screening group was fixed at 32,000 subjects. Because the whole birth cohort underwent randomization, this led to a ratio, for the screening group to the control group, of approximately 1 to 1.5, and to the non-screening arm being larger than the screening arm.

References

Liu Z, Rich B, Hanley JA. Recovering the raw data behind a non-parametric survival curve. Systematic Reviews 2014 Dec 30;3:151. doi: 10.1186/2046-4053-3-151.

Schroder FH, et al., for the ERSPC Investigators.Screening and Prostate-Cancer Mortality in a Randomized European Study. N Engl J Med 2009;360:1320-8.

Examples

# NOT RUN {
###  cumulative incidence plots
library(survival)
library(casebase)
data("ERSPC")
KM = survfit(Surv(Follow.Up.Time,DeadOfPrCa) ~ ScrArm, data = ERSPC)
str(KM)
par(mfrow=c(1,1),mar = c(5,5,0.1,0.1))
plot(KM$time[    1: 1501], 1-KM$surv[   1:1501], type="s", col="red" ,
     ylab = "Risk", xlab="Years since Randomization")
lines(KM$time[1502: 2923], 1-KM$surv[1502: 2923], type="s", col="green" )

###  PopulationTime plots
ds <- ERSPC
par(mfrow=c(1,1),mar = c(0.01,0.01,0.1,0.1))

plot(c(-0.5,15.75),c(-93000,80000), col="white" )
set.seed(7654321)

OFF = 2000


for(i in 0:1) {
    t=seq(0.01,14.9,0.01)
    S = function(x) sum(ds$Follow.Up.Time[ds$ScrArm==i] >= x)
    n = unlist(lapply(t,"S"))
    if(i==1) yy =  c(0,n,0) + OFF
    if(i==0) yy =  c(0,-n,0) - OFF
    polygon(c(0,t,14.9),yy,col="grey80",border=NA)

    t.d = ds$Follow.Up.Time[ds$ScrArm==i & ds$DeadOfPrCa==1]

    for( j in 1:length(t.d) ) {
        time.index =  ceiling(t.d[j]/0.01)
        nn   = n[ time.index ]
        if(i==1) h = runif(1,0.01*nn,0.99*nn)  + OFF
        if(i==0) h = runif(1,-0.99*nn,-0.01*nn) - OFF
        points(t.d[j],h, pch=19,cex=0.25,col="red")
    }
}

for (t in 1:15) text(t,0,toString(t), cex=0.75)
text(15.25,0,"Year", cex=0.75,adj=c(0,0.5))

for (n in seq(0,90000,10000)) {
    if(n> 0 & n < 80000) text(-0.1,n+OFF,format(n,big.mark=","), cex=0.75,adj=c(1,0.5))
    if(n> 0) text(-0.1,-n-OFF,format(n,big.mark=","), cex=0.75,adj=c(1,0.5))
    segments(-0.05,  n+OFF, 0, n+OFF , lwd=0.5)
    segments(-0.05, -n-OFF, 0, -n-OFF, lwd=0.5 )

}
text(4, 70000+OFF,"Screening Arm of ERSPC", cex=1,adj=c(0,0.5))
text(4,-85000-OFF,"No-Screening Arm", cex=1,adj=c(0,0.5))

text(-0.75,78000+OFF,"Number of
Men being Followed", cex=1,adj=c(0,0.5))
h = 50000+OFF
points(9.5,h, pch=19,cex=0.25,col="red")
text(9.6,h,"Death from Prostate Cancer", adj=c(0,0.5))

#The randomization of the Finnish cohorts were carried out on January 1 of
#each of the 4 years 1996 to 1999. This, coupled with the uniform December 31
#2006 censoring date, lead to large numbers of men with exactly 11, 10, 9 or 8
#years of follow-up.

#Tracked backwards in time (i.e. from right to left) , the PopulationTime
#plot shows the recruitment pattern from its beginning in 1991, and in
#particular the Jan 1 entries in successive years.

#Tracked forwards in time (i.e. from left to right), the plot for the first
#three years shows attrition due entirely to death (mainly from other causes).
#Since the Swedish and Belgian centres were the last to close their
#recruitment - in December 2003 - the minimum potential follow-up is three
#years. Tracked further forwards in time (i.e. after year 3) the attrition is
#a combination of deaths and staggered entries.
# }
# NOT RUN {

# }