lines.survfit {survival} | R Documentation

## 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

`x` | 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 <blank> 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 with a character argument instead: `"log"` is the same as using the `log=T` option, `"event"` plots cumulative events (f(y) =1-y), `"cumhaz"` plots the cumulative hazard function (f(y) = -log(y)) and `"cloglog"` creates a complementary log-log survival plot (f(y) = log(-log(y)) along with log scale for the x-axis).
`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.

### See Also

`lines`, `par`, `plot.survfit`, `survfit`, `survexp`.

### Examples

    data(pbc)
    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 expected
    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
    data(ratetables)
    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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