Cumulative incidence of competing events

The probability of each event type over follow-up, in the presence of competing events. When a patient can experience one of several mutually exclusive events, a Kaplan-Meier estimate of any single one is biased upward, because patients who had a competing event are still counted as being at risk of the event of interest. The cumulative incidence function accounts for them.

Usage

plot_cumulative_incidence(
  time,
  status,
  group = NULL,
  event = NULL,
  conf_int = FALSE,
  palette = "house",
  xlab = "Follow up",
  ylab = "Cumulative incidence",
  title = NULL,
  legend_title = NULL,
  font = "Arial"
)

Arguments

time

Follow-up times.

status

Event type per patient. The first level is the event of interest, 0 is censoring, and any further levels are competing events. A factor with a 0 level, a numeric code vector, or a character vector are all accepted.

group

Optional grouping vector, giving one panel per group.

event

Optional event type to plot. By default every event type is drawn.

conf_int

Draw pointwise confidence bands.

palette

Palette name passed to get_color().

xlab, ylab, title

Axis and plot labels.

legend_title

Legend title.

font

Font family used in the plot.

Value

A ggplot object.

See also

plot_KMCurve() for a single event where no competing risk applies.

Examples

set.seed(1)
time <- rexp(200)
status <- sample(c(0, 1, 2), 200, replace = TRUE, prob = c(0.4, 0.4, 0.2))
p <- plot_cumulative_incidence(time, status, group = rep(c("A", "B"), 100))