lines.survfit: Add Lines or Points to a Survival Plot

Description

Often used to add the expected survival curve(s) to a Kaplan-Meier plot generated with plot.survfit.

Usage

## S3 method for class 'survfit':
lines(x, type="s", mark=3, col=1, lty=1,
lwd=1, mark.time=TRUE , xscale=1,  firstx=0, firsty=1, xmax, fun, conf.int=FALSE,  ...)
## S3 method for class 'survfit':
points(x, ...)

Arguments

a survival object, generated from the survfit or survexp functions.

type

the line type, as described in lines. The default is a step function for survfit objects, and a connected line for survexp objects.

mark

vectors giving the mark symbol, color, line type and line width for the added curves.

mark.time

controls the labeling of the curves. If FALSE, no labeling is done. If TRUE, then curves are marked at each censoring time. If mark.time is a numeric vector, then curves are marked at the specified time points

xscale

a number used to divide the x values. If time was originally in days, a value of 365.24 would give a plotted scale in years.

firstx,firsty

the starting point for the survival curves. If either of these is set to NA or the plot will start at the first time point of the curve.

col,lty,lwd,...

passed to lines

xmax

the maximum horizontal plot coordinate. This shortens the curve before plotting it, so unlike using the xlim graphical parameter, warning messages about out of bounds points are not generated.

fun

an arbitrary function defining a transformation of the survival curve. For example fun=log is an alternative way to draw a log-survival curve (but with the axis labeled with log(S) values). Four often used transformations can be specified wit

conf.int

if TRUE, confidence bands for the curves are also plotted. If set to "only", then only the CI bands are plotted, and the curve itself is left off. This can be useful for fine control over the colors or line types of a plot.

Value

a list with components x and y, containing the coordinates of the last point on each of the curves (but not of the confidence limits). This may be useful for labeling.

Side Effects

one or more curves are added to the current plot.

Examples

Run this code

fit <- survfit(Surv(time, status) ~ sex, pbc,subset=1:312)
plot(fit, mark.time=FALSE, xscale=365.24,
	xlab='Years', ylab='Survival')
lines(fit[1], lwd=2, xscale=365.24)    #darken the first curve and add marks


# add expected survival curves for the two groups,
#   based on the US census data
tdata <- data.frame(age=pbc$age*365.24, sex=pbc$sex +1,
		    year= rep(mdy.date(1,1,1976), nrow(pbc)))
tdata<-tdata[1:312,] ## only the randomised people, with no missing data

efit <- survexp(~ sex+ratetable(sex=sex,age=age,year=year), data=tdata, ratetable=survexp.us, times=(0:24)*182)
temp <- lines(efit, lty=2, xscale=365.24, lwd=2:1)
text(temp, c("Male", "Female"), adj= -.1) #labels just past the ends
title(main="Primary Biliary Cirrhosis, Observed and Expected")

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