summary.survfit: Summary of a Survival Curve

Description Usage Arguments Value Details See Also Examples

View source: R/survfitms.R

Description

Returns a list containing the survival curve, confidence limits for the curve, and other information.

Usage

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  ## S3 method for class 'survfit'
summary(object, times, censored=FALSE, scale=1,
  extend=FALSE, rmean=getOption('survfit.rmean'), ...)
  

Arguments

object

the result of a call to the survfit function.

times

vector of times; the returned matrix will contain 1 row for each time. The vector will be sorted into increasing order; missing values are not allowed. If censored=T, the default times vector contains all the unique times in fit, otherwise the default times vector uses only the event (death) times.

censored

logical value: should the censoring times be included in the output? This is ignored if the times argument is present.

scale

numeric value to rescale the survival time, e.g., if the input data to survfit were in days, scale = 365.25 would scale the output to years.

extend

logical value: if TRUE, prints information for all specified times, even if there are no subjects left at the end of the specified times. This is only used if the times argument is present.

rmean

Show restricted mean: see print.survfit for details

...

for future methods

Value

a list with the following components:

surv

the estimate of survival at time t+0.

time

the timepoints on the curve.

n.risk

the number of subjects at risk at time t-0 (but see the comments on weights in the survfit help file).

n.event

if the times argument is missing, then this column is the number of events that occurred at time t. Otherwise, it is the cumulative number of events that have occurred since the last time listed until time t+0.

n.entered

This is present only for counting process survival data. If the times argument is missing, this column is the number of subjects that entered at time t. Otherwise, it is the cumulative number of subjects that have entered since the last time listed until time t.

n.exit.censored

if the times argument is missing, this column is the number of subjects that left without an event at time t. Otherwise, it is the cumulative number of subjects that have left without an event since the last time listed until time t+0. This is only present for counting process survival data.

std.err

the standard error of the survival value.

conf.int

level of confidence for the confidence intervals of survival.

lower

lower confidence limits for the curve.

upper

upper confidence limits for the curve.

strata

indicates stratification of curve estimation. If strata is not NULL, there are multiple curves in the result and the surv, time, n.risk, etc. vectors will contain multiple curves, pasted end to end. The levels of strata (a factor) are the labels for the curves.

call

the statement used to create the fit object.

na.action

same as for fit, if present.

table

table of information that is returned from print.survfit function.

type

type of data censoring. Passed through from the fit object.

Details

This routine has two uses: printing out a survival curve at specified time points (often yearly), or extracting the values at specified time points for further processing. In the first case we normally want extend=FALSE, i.e., don't print out data past the end of the curve. If the times option only contains values beyond the last point in the curve then there is nothing to print and an error message will result. For the second usage we almost always want extend=TRUE, so that the results will have a predictable length.

The survfit object itself will have a row of information at each censoring or event time, it does not save information on each unique entry time. For printout at two time points t1, t2, this function will give the the number at risk at the smallest event times that are >= t1 and >= t2, respectively, the survival curve at the largest recorded times <= t1 and <= t2, and the number of events and censorings in the interval t1 < t <= t2.

When the routine is called with counting process data many users are confused by counts that are too large. For example, Surv(c(0,0, 5, 5), c(2, 3, 8, 10), c(1, 0, 1, 0)) followed by a request for the values at time 4. The survfit object has entries only at times 2, 3, 8, and 10; there are 2 subjects at risk at time 8, so that is what will be printed.

See Also

survfit, print.summary.survfit

Examples

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summary( survfit( Surv(futime, fustat)~1, data=ovarian))
summary( survfit( Surv(futime, fustat)~rx, data=ovarian))

Example output

Call: survfit(formula = Surv(futime, fustat) ~ 1, data = ovarian)

 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   59     26       1    0.962  0.0377        0.890        1.000
  115     25       1    0.923  0.0523        0.826        1.000
  156     24       1    0.885  0.0627        0.770        1.000
  268     23       1    0.846  0.0708        0.718        0.997
  329     22       1    0.808  0.0773        0.670        0.974
  353     21       1    0.769  0.0826        0.623        0.949
  365     20       1    0.731  0.0870        0.579        0.923
  431     17       1    0.688  0.0919        0.529        0.894
  464     15       1    0.642  0.0965        0.478        0.862
  475     14       1    0.596  0.0999        0.429        0.828
  563     12       1    0.546  0.1032        0.377        0.791
  638     11       1    0.497  0.1051        0.328        0.752
Call: survfit(formula = Surv(futime, fustat) ~ rx, data = ovarian)

                rx=1 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   59     13       1    0.923  0.0739        0.789        1.000
  115     12       1    0.846  0.1001        0.671        1.000
  156     11       1    0.769  0.1169        0.571        1.000
  268     10       1    0.692  0.1280        0.482        0.995
  329      9       1    0.615  0.1349        0.400        0.946
  431      8       1    0.538  0.1383        0.326        0.891
  638      5       1    0.431  0.1467        0.221        0.840

                rx=2 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
  353     13       1    0.923  0.0739        0.789        1.000
  365     12       1    0.846  0.1001        0.671        1.000
  464      9       1    0.752  0.1256        0.542        1.000
  475      8       1    0.658  0.1407        0.433        1.000
  563      7       1    0.564  0.1488        0.336        0.946

survival documentation built on April 26, 2021, 9:06 a.m.