Cumulative Incidence Curves for Competing Risks

This function plots Cumulative Incidence Curves. For cuminc objects it's a ggplot2 version of plot.cuminc. For survfitms objects a different geometry is used, as suggested by @teigentler.

Usage

ggcompetingrisks(
  fit,
  gnames = NULL,
  gsep = " ",
  multiple_panels = TRUE,
  ggtheme = theme_survminer(),
  coef = 1.96,
  conf.int = FALSE,
  ...
)

Arguments

fit

an object of a class cmprsk::cuminc - created with cmprsk::cuminc function or survfitms created with survfit function.

gnames

a vector with group names. If not supplied then will be extracted from fit object (cuminc only).

gsep

a separator that extracts group names and event names from gnames object (cuminc only).

multiple_panels

if TRUE then groups will be plotted in different panels (cuminc only).

ggtheme

function, ggplot2 theme name. Default value is theme_survminer. Allowed values include ggplot2 official themes: see theme.

coef

see conf.int, scaling actor for the ribbon. The default value is 1.96.

conf.int

if TRUE then additional layer (geom_ribbon) is added around the point estimate. The ribon is plotted with boundries +- coef*standard deviation.

...

further arguments passed to the function ggpar for customizing the plot.

Value

Returns an object of class gg.

Author

Przemyslaw Biecek, przemyslaw.biecek@gmail.com

Examples

if (FALSE) { # \dontrun{
if(require("cmprsk")){

set.seed(2)
ss <- rexp(100)
gg <- factor(sample(1:3,100,replace=TRUE),1:3,c('BRCA','LUNG','OV'))
cc <- factor(sample(0:2,100,replace=TRUE),0:2,c('no event', 'death', 'progression'))
strt <- sample(1:2,100,replace=TRUE)

# handles cuminc objects
print(fit <- cmprsk::cuminc(ss,cc,gg,strt))
ggcompetingrisks(fit)
ggcompetingrisks(fit, multiple_panels = FALSE)
ggcompetingrisks(fit, conf.int = TRUE)
ggcompetingrisks(fit, multiple_panels = FALSE, conf.int = TRUE)

# handles survfitms objects
library(survival)
df <- data.frame(time = ss, group = gg, status = cc, strt)
fit2 <- survfit(Surv(time, status, type="mstate") ~ 1, data=df)
ggcompetingrisks(fit2)
fit3 <- survfit(Surv(time, status, type="mstate") ~ group, data=df)
ggcompetingrisks(fit3)
}

  library(ggsci)
  library(cowplot)
  ggcompetingrisks(fit3) + theme_cowplot() + scale_fill_jco()
} # }