summary.survfit {survival} R Documentation

## Summary of a Survival Curve

### Description

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

### Usage

  ## 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.

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