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().
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")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 0.13The tidycmprsk plays well with other packages, such as
gtsummary.
tbl <-
crr_mod %>%
gtsummary::tbl_regression(exponentiate = TRUE) %>%
gtsummary::add_global_p() %>%
add_n(location = "level")
gtsummary::inline_text(tbl, variable = age)
#> [1] "1.01 (95% CI 0.99, 1.03; p=0.6)"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, 0.264Plot 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() +
scale_ggsurvfit(x_scales = list(breaks = seq(0, 24, by = 6)))
#> 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()
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!
@abduazizR, @ABohynDOE, @ddsjoberg, @dublinQAQ, @erikvona, @fdehrich, @gustavomodelli, @hadley, @karissawhiting, @Lamenace23, @m-freitag, @mjtjmjtj, @nettam, @Nickrou10, @pteridin, @ramashka328, @SoumyaRo, @t-vinn, and @tengfei-emory
The tidycmprsk package implements most features (and
more) available in cmprsk. However, the time interaction
features available in cmprsk::crr() is not available in
tidycmprsk.