Competing Risks Cumulative Incidence
# S3 method for class 'formula'
cuminc(formula, data, strata, rho = 0, conf.level = 0.95, ...)
cuminc(x, ...)
# Default S3 method
cuminc(x, ...)formula with Surv() on LHS and covariates on RHS.
The event status variable must be a factor, with the first level indicating
'censor' and subsequent levels the competing risks. The Surv(time2=)
argument cannot be used.
data frame
stratification variable. Has no effect on estimates. Tests will be stratified on this variable. (all data in 1 stratum, if missing)
Power of the weight function used in the tests.
confidence level. Default is 0.95.
passed to methods
input object
tidycuminc object
The confidence intervals for cumulative incidence estimates use the recommended method in Competing Risks: A Practical Perspective by Melania Pintilie.
$$x^{exp(±z * se / (x * log(x)))}$$
where \(x\) is the cumulative incidence estimate, \(se\) is the standard error estimate, and \(z\) is the z-score associated with the confidence level of the interval, e.g. \(z = 1.96\) for a 95% CI.
The p-values reported in cuminc(), glance.tidycuminc() and add_p.tbl_cuminc()
are Gray's test as described in
Gray RJ (1988) A class of K-sample tests for comparing the cumulative incidence of a competing risk, Annals of Statistics, 16:1141-1154.
Other cuminc() functions:
broom_methods_cuminc
# calculate risk for entire cohort -----------
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
# calculate risk by treatment group ----------
cuminc(Surv(ttdeath, death_cr) ~ trt, trial)
#>
#> ── cuminc() ────────────────────────────────────────────────────────────────────
#>
#> • Failure type "death from cancer"
#> strata time n.risk estimate std.error 95% CI
#> Drug A 5.00 97 0.000 0.000 NA, NA
#> Drug A 10.0 94 0.020 0.014 0.004, 0.065
#> Drug A 15.0 83 0.071 0.026 0.031, 0.134
#> Drug A 20.0 61 0.173 0.039 0.106, 0.255
#> Drug B 5.00 102 0.000 0.000 NA, NA
#> Drug B 10.0 95 0.039 0.019 0.013, 0.090
#> Drug B 15.0 75 0.167 0.037 0.102, 0.246
#> Drug B 20.0 55 0.255 0.043 0.175, 0.343
#>
#> • Failure type "death other causes"
#> strata time n.risk estimate std.error 95% CI
#> Drug A 5.00 97 0.010 0.010 0.001, 0.050
#> Drug A 10.0 94 0.020 0.014 0.004, 0.065
#> Drug A 15.0 83 0.082 0.028 0.038, 0.147
#> Drug A 20.0 61 0.204 0.041 0.131, 0.289
#> Drug B 5.00 102 0.000 0.000 NA, NA
#> Drug B 10.0 95 0.029 0.017 0.008, 0.077
#> Drug B 15.0 75 0.098 0.030 0.050, 0.165
#> Drug B 20.0 55 0.206 0.040 0.133, 0.289
#>
#> • Tests
#> outcome statistic df p.value
#> death from cancer 1.99 1.00 0.16
#> death other causes 0.089 1.00 0.77