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

rotterdam {survival} | R Documentation

## 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

    data("rotterdam")

### Format

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

`pid`

  patient identifier

`year`

  year of cancer incidence

`age`

  age

`meno`

  menopausal status (0= premenopausal, 1= postmenopausal)

`size`

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

`grade`

  tumor 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 recurrence or last follow-up

`recur`

  0= no recurrence, 1= recurrence

`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

[Package survival version 3.2-7 Index]