plotCIF {Epi}

Plotting Aalen-Johansen curves for competing events

Description

Function plotCIF plots, for one or more groups, the cumulative incidence curves for a selected event out of two or more competing events. Function stackedCIF plots, for one group or population, the cumulative incidence curves for two or more competing events such that the cumulative incidences are stacked upon each other. The CIFs are are estimated by the Aalen-Johansen method.

Usage

## S3 method for class 'survfit'
 plotCIF( x, event = 1,
              xlab = "Time",
              ylab = "Cumulative incidence",
              ylim = c(0, 1),
               lty = 1,
               col = "black", ... )

## S3 method for class 'survfit'
stackedCIF( x, group = 1,
                 col = "black",
                fill = "white",
                ylim = c(0,1),
                xlab = "Time",
                ylab = "Cumulative incidence", ... )

Arguments

x

An object of class survfit, the type of event in Surv() being "mstate"; the first level of the event factor represents censoring and the remaining ones the alternative competing events.

event

Determines the event for which the cumulative incidence curve is plotted by plotCIF.

group

An integer showing the selected level of a possible grouping factor appearing in the model formula in survfit when plotting by stackedCIF

col

A vector specifying the plotting color(s) of the curve(s) for the different groups in plotCIF– default: all "black".

fill

A vector indicating the colours to be used for shading the areas pertinent to the separate outcomes in stackedCIF - default: all "white".

xlab

Label for the $x$-axis.

ylab

Label for the $y$-axis.

ylim

Limits of the $y$-axis.

lty

A vector specifying the line type(s) of the curve(s) for the different groups - default: all 1 (=solid).

...

Further graphical parameters to be passed.

Details

The order in which the curves with stackedCIF are piled upon each other is the same as the ordering of the values or levels of the competing events in the pertinent event variable. The ordering can be changed by permuting the levels as desired using function Relevel, after which survfit is called with the relevelled event variable in Surv()

Value

No value is returned but a plot is produced as a side-effect.

Note

Aalen-Johansen curves for competing events in several groups can also be plotted by function plot.survfit of the survival library as well as by some functions in other packages covering analysis of time-to-event data.

Author(s)

Esa Laara, [e-mail]

References

Putter, H., Fiocco, M., Geskus, R.B. (2007). Tutorial in biostatistics: competing risks and multi-state models. Statistics in Medicine, 26: 2389–2430.

See Also

survfit, plot, plot.survfit.

Examples

library(survival)   #  requires version 2.39-4 or later
head(mgus1)
#  Aalen-Johansen estimates of CIF are plotted by sex for two 
#  competing events: (1) progression (pcm), and (2) death, in 
#  a cohort of patients with monoclonal gammopathy.

#  The data are actually covering transitions from pcm to death, too,
#  for those entering the state of pcm. Such patients have two rows
#  in the data frame, and in their 2nd row the 'start' time is 
#  the time to pcm (in days). 

#  In our analysis we shall only include those time intervals with value 0
#  for variable 'start'. Thus, the relevant follow-up time is represented 
#  by variable 'stop' (days). For convenience, days are converted to years.

fitCI <- survfit(Surv(stop/365.25, event, type="mstate") ~ sex,
              data= subset(mgus1, start==0) )
par(mfrow=c(1,2))
plotCIF(fitCI, event = 1, col = c("red", "blue"),
  main = "Progression", xlab="Time (years)" )
text( 38, 0.15, "Men", pos = 2)
text( 38, 0.4, "Women", pos = 2)
plotCIF(fitCI, event = 2, col = c("red", "blue"), 
  main = "Death", xlab="Time (years)" )
text( 38, 0.8, "Men", pos = 2)
text( 38, 0.5, "Women", pos = 2)

par(mfrow=c(1,2))
stackedCIF(fitCI, group = 1, fill = c("gray80", "gray90"),
  main = "Women", xlab="Time (years)" )	
text( 36, 0.15, "PCM", pos = 2)
text( 36, 0.6, "Death", pos = 2)
stackedCIF(fitCI, group = 2, fill = c("gray80", "gray90"), 
  main = "Men", xlab="Time (years)" )
text( 39, 0.10, "PCM", pos = 2)
text( 39, 0.6, "Death", pos = 2)