ARD Survival Estimates — ard_survival

Analysis results data for survival quantiles and x-year survival estimates, extracted from a survival::survfit() model.

Usage

ard_survival_survfit(x, times = NULL, probs = NULL, type = NULL)

Arguments

x

(survival::survfit())
a survival::survfit() object. See below for details.

times

(numeric)
a vector of times for which to return survival probabilities.

probs

(numeric)
a vector of probabilities with values in (0,1) specifying the survival quantiles to return.

type

(string or NULL)
type of statistic to report. Available for Kaplan-Meier time estimates only, otherwise type is ignored. Default is NULL. Must be one of the following:

type	transformation
`"survival"`	`x`
`"risk"`	`1 - x`
`"cumhaz"`	`-log(x)`

Value

an ARD data frame of class 'card'

Details

Only one of either the times or probs parameters can be specified.
Times should be provided using the same scale as the time variable used to fit the provided survival fit model.

Examples

library(survival)
library(ggsurvfit)

survfit(Surv_CNSR(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>
  ard_survival_survfit(times = c(60, 180))
#> {cards} data frame: 30 x 11
#>    group1 group1_level variable variable_level stat_name stat_label  stat
#> 1    TRTA      Placebo     time             60    n.risk  Number o…    59
#> 2    TRTA      Placebo     time             60  estimate  Survival… 0.768
#> 3    TRTA      Placebo     time             60 std.error  Standard… 0.047
#> 4    TRTA      Placebo     time             60 conf.high  CI Upper… 0.866
#> 5    TRTA      Placebo     time             60  conf.low  CI Lower… 0.682
#> 6    TRTA      Placebo     time            180    n.risk  Number o…    35
#> 7    TRTA      Placebo     time            180  estimate  Survival… 0.626
#> 8    TRTA      Placebo     time            180 std.error  Standard… 0.056
#> 9    TRTA      Placebo     time            180 conf.high  CI Upper… 0.746
#> 10   TRTA      Placebo     time            180  conf.low  CI Lower… 0.526
#> ℹ 20 more rows
#> ℹ Use `print(n = ...)` to see more rows
#> ℹ 4 more variables: context, fmt_fn, warning, error

survfit(Surv_CNSR(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>
  ard_survival_survfit(probs = c(0.25, 0.5, 0.75))
#> {cards} data frame: 27 x 11
#>    group1 group1_level variable variable_level stat_name stat_label stat
#> 1    TRTA      Placebo     prob           0.25  estimate  Survival…   70
#> 2    TRTA      Placebo     prob           0.25 conf.high  CI Upper…  177
#> 3    TRTA      Placebo     prob           0.25  conf.low  CI Lower…   35
#> 4    TRTA      Placebo     prob            0.5  estimate  Survival…   NA
#> 5    TRTA      Placebo     prob            0.5 conf.high  CI Upper…   NA
#> 6    TRTA      Placebo     prob            0.5  conf.low  CI Lower…   NA
#> 7    TRTA      Placebo     prob           0.75  estimate  Survival…   NA
#> 8    TRTA      Placebo     prob           0.75 conf.high  CI Upper…   NA
#> 9    TRTA      Placebo     prob           0.75  conf.low  CI Lower…   NA
#> 10   TRTA    Xanomeli…     prob           0.25  estimate  Survival…   14
#> ℹ 17 more rows
#> ℹ Use `print(n = ...)` to see more rows
#> ℹ 4 more variables: context, fmt_fn, warning, error

# Competing Risks Example ---------------------------
set.seed(1)
ADTTE_MS <- cards::ADTTE %>%
  dplyr::mutate(
    CNSR = dplyr::case_when(
      CNSR == 0 ~ "censor",
      runif(dplyr::n()) < 0.5 ~ "death from cancer",
      TRUE ~ "death other causes"
    ) %>% factor()
  )

survfit(Surv(AVAL, CNSR) ~ TRTA, data = ADTTE_MS) %>%
  ard_survival_survfit(times = c(60, 180))
#> Multi-state model detected. Showing probabilities into state 'death from
#> cancer'.
#> {cards} data frame: 30 x 11
#>    group1 group1_level variable variable_level stat_name stat_label  stat
#> 1    TRTA      Placebo     time             60    n.risk  Number o…    59
#> 2    TRTA      Placebo     time             60  estimate  Survival… 0.054
#> 3    TRTA      Placebo     time             60 std.error  Standard… 0.026
#> 4    TRTA      Placebo     time             60 conf.high  CI Upper…  0.14
#> 5    TRTA      Placebo     time             60  conf.low  CI Lower… 0.021
#> 6    TRTA      Placebo     time            180    n.risk  Number o…    35
#> 7    TRTA      Placebo     time            180  estimate  Survival… 0.226
#> 8    TRTA      Placebo     time            180 std.error  Standard… 0.054
#> 9    TRTA      Placebo     time            180 conf.high  CI Upper… 0.361
#> 10   TRTA      Placebo     time            180  conf.low  CI Lower… 0.142
#> ℹ 20 more rows
#> ℹ Use `print(n = ...)` to see more rows
#> ℹ 4 more variables: context, fmt_fn, warning, error