German Breast Cancer Study Group 2

A data frame containing the observations from the GBSG2 study.

Usage

data("GBSG2")

Format

This data frame contains the observations of 686 women:

horTh: hormonal therapy, a factor at two levels no and yes.
age: of the patients in years.
menostat: menopausal status, a factor at two levels pre (premenopausal) and post (postmenopausal).
tsize: tumor size (in mm).
tgrade: tumor grade, a ordered factor at levels I < II < III.
pnodes: number of positive nodes.
progrec: progesterone receptor (in fmol).
estrec: estrogen receptor (in fmol).
time: recurrence free survival time (in days).
cens: censoring indicator (0- censored, 1- event).

Source

W. Sauerbrei and P. Royston (1999). Building multivariable prognostic and diagnostic models: transformation of the predictors by using fractional polynomials. Journal of the Royal Statistics Society Series A, Volume 162(1), 71–94.

References

M. Schumacher, G. Basert, H. Bojar, K. Huebner, M. Olschewski, W. Sauerbrei, C. Schmoor, C. Beyerle, R.L.A. Neumann and H.F. Rauschecker for the German Breast Cancer Study Group (1994), Randomized \(2\times2\) trial evaluating hormonal treatment and the duration of chemotherapy in node-positive breast cancer patients. Journal of Clinical Oncology, 12, 2086–2093.

Examples

data(GBSG2)

thsum <- function(x) {
  ret <- c(median(x), quantile(x, 0.25), quantile(x,0.75))
  names(ret)[1] <- "Median"
  ret
}

t(apply(GBSG2[,c("age", "tsize", "pnodes", 
                 "progrec", "estrec")], 2, thsum))
#>         Median 25%    75%
#> age       53.0  46  61.00
#> tsize     25.0  20  35.00
#> pnodes     3.0   1   7.00
#> progrec   32.5   7 131.75
#> estrec    36.0   8 114.00

table(GBSG2$menostat)
#> 
#>  Pre Post 
#>  290  396 
table(GBSG2$tgrade)
#> 
#>   I  II III 
#>  81 444 161 
table(GBSG2$horTh)
#> 
#>  no yes 
#> 440 246