ggsurvfit: Plot Survival Probability

In ggsurvfit: Flexible Time-to-Event Figures

Plot Survival Probability

Description

Plot survival probabilities (and other transformations) using the results from survfit2() or survival::survfit(); although, the former is recommend to have the best experience with the ggsurvfit package.

Usage

ggsurvfit(
  x,
  type = "survival",
  linetype_aes = FALSE,
  theme = theme_ggsurvfit_default(),
  ...
)

Arguments

x	a 'survfit' object created with survfit2()
type	type of statistic to report. Available for Kaplan-Meier estimates only. Default is "survival". Must be one of the following: type transformation "survival" x "risk" 1 - x "cumhaz" -log(x)
linetype_aes	logical indicating whether to add ggplot2::aes(linetype = strata) to the ggplot2::geom_step() call. When strata are present, the resulting figure will be a mix a various line types for each stratum.
theme	a survfit theme. Default is theme_ggsurvfit_default()
...	arguments passed to ggplot2::geom_step(...), e.g. size = 2

Value

a ggplot2 figure

Details

This function creates a ggplot figure from the 'survfit' object. To better understand how to modify the figure, review the simplified code used internally:

survfit2(Surv(time, status) ~ sex, data = df_lung) %>%
  tidy_survfit() %>%
  ggplot(aes(x = time, y = estimate,
             min = conf.low, ymax = conf.low,
             color = strata, fill = strata)) +
  geom_step()

See Also

Visit the gallery for examples modifying the default figures

Examples

# Default publication ready plot
survfit2(Surv(time, status) ~ sex, data = df_lung) %>%
  ggsurvfit() +
  scale_ggsurvfit(x_scales = list(breaks = seq(0, 30, by = 6)))

# Changing statistic type
survfit2(Surv(time, status) ~ sex, data = df_lung) %>%
  ggsurvfit(type = "cumhaz")

# Configuring KM line type to vary by strata
survfit2(Surv(time, status) ~ sex, data = df_lung) %>%
  ggsurvfit(linetype_aes = TRUE) +
  scale_ggsurvfit()

# Customizing the plot to your needs
survfit2(Surv(time, status) ~ 1, data = df_lung) %>%
  ggsurvfit() +
  add_censor_mark() +
  add_confidence_interval() +
  add_quantile() +
  add_risktable() +
  scale_ggsurvfit()

ggsurvfit documentation built on Nov. 2, 2023, 5:33 p.m.