The tidycmprsk package provides an intuitive interface for working with the competing risk endpoints. The package wraps the cmprsk package, and exports functions for univariate cumulative incidence estimates with cuminc() and competing risk regression with crr().

The package also includes broom-style tidiers: tidy(), augment(), and glance().

Installation

You can install {tidycmprsk} with the following code.

install.packages("tidycmprsk")

Install the development version of {tidycmprsk} with:

# install.packages("devtools")
devtools::install_github("MSKCC-Epi-Bio/tidycmprsk")

Competing Risk Regression

Fit a Fine and Gray competing risks regression model using the the example data, trial.

library(tidycmprsk)

crr_mod <- crr(Surv(ttdeath, death_cr) ~ age + trt, trial)
#> 11 cases omitted due to missing values
crr_mod
#> 
#> ── crr() ───────────────────────────────────────────────────────────────────────
#> • Call Surv(ttdeath, death_cr) ~ age + trt
#> • Failure type of interest "death from cancer"
#> 
#> Variable    Coef    SE      HR     95% CI       p-value    
#> age         0.006   0.010   1.01   0.99, 1.03   0.56       
#> trtDrug B   0.417   0.279   1.52   0.88, 2.62   0.13

The tidycmprsk plays well with other packages, such as gtsummary.

tbl <- 
  crr_mod %>%
  gtsummary::tbl_regression(exponentiate = TRUE) %>%
  add_n(location = "level")

gtsummary::inline_text(tbl, variable = age)
#> [1] "1.01 (95% CI 0.99, 1.03; p=0.6)"

Cumulative Incidence

cuminc(Surv(ttdeath, death_cr) ~ 1, trial)
#> 
#> ── cuminc() ────────────────────────────────────────────────────────────────────
#> • Failure type "death from cancer"
#> time   n.risk   estimate   std.error   95% CI          
#> 5.00   199      0.000      0.000       NA, NA          
#> 10.0   189      0.030      0.012       0.012, 0.061    
#> 15.0   158      0.120      0.023       0.079, 0.169    
#> 20.0   116      0.215      0.029       0.161, 0.274
#> • Failure type "death other causes"
#> time   n.risk   estimate   std.error   95% CI          
#> 5.00   199      0.005      0.005       0.000, 0.026    
#> 10.0   189      0.025      0.011       0.009, 0.054    
#> 15.0   158      0.090      0.020       0.055, 0.135    
#> 20.0   116      0.205      0.029       0.152, 0.264

Plot risks using using the {ggsurvfit} package.

library(ggsurvfit)
#> Loading required package: ggplot2

cuminc(Surv(ttdeath, death_cr) ~ trt, trial) %>%
  ggcuminc() +
  add_confidence_interval() +
  add_risktable()
#> Plotting outcome "death from cancer".

Summary table

tbl <- 
  cuminc(Surv(ttdeath, death_cr) ~ trt, trial) %>%
  tbl_cuminc(times = c(12, 24), label_header = "**Month {time}**") %>%
  add_p() %>%
  add_n()

Contributing

Please note that the {tidycmprsk} project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms. Thank you to all contributors!
@ddsjoberg, @erikvona, @karissawhiting, @m-freitag, and @tengfei-emory

Limitations

The tidycmprsk package implements most features (and more) available in cmprsk. However, the time interaction features available in cmprsk::crr() have not yet been made available in tidycmprsk.