rotterdam Breast cancer data set used in Royston and Altman (2013)

Description

The rotterdam data set includes 2982 primary breast cancers patients whose data whose records were included in the Rotterdam tumor bank.

Usage

rotterdam
data(cancer, package="survival")

Format

A data frame with 2982 observations on the following 15 variables.

pid

patient identifier

year

year of surgery

age

age at surgery

meno

menopausal status (0= premenopausal, 1= postmenopausal)

size

tumor size, a factor with levels <=20 20-50 >50

grade

differentiation grade

nodes

number of positive lymph nodes

pgr

progesterone receptors (fmol/l)

er

estrogen receptors (fmol/l)

hormon

hormonal treatment (0=no, 1=yes)

chemo

chemotherapy

rtime

days to relapse or last follow-up

recur

0= no relapse, 1= relapse

dtime

days to death or last follow-up

death

0= alive, 1= dead

Details

These data sets are used in the paper by Royston and Altman. The Rotterdam data is used to create a fitted model, and the GBSG data for validation of the model. The paper gives references for the data source.

References

Patrick Royston and Douglas Altman, External validation of a Cox prognostic model: principles and methods. BMC Medical Research Methodology 2013, 13:33

See Also

gbsg

Examples

rfstime <- pmin(rotterdam$rtime, rotterdam$dtime)
status  <- pmax(rotterdam$recur, rotterdam$death)
fit1 <- coxph(Surv(rfstime, status) ~ pspline(age) + meno + size + 
        pspline(nodes) + er,
     data=rotterdam, subset = (nodes > 0))
# Royston and Altman used fractional polynomials for the nonlinear terms