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Kaplan-Meier survival probability table

Source: R/survival_prob.R
survival_prob.Rd

Estimate Kaplan-Meier survival probabilities at user-specified follow-up times, such as 30-day, 6-month, or 1-year survival.

Usage

survival_prob(
  data,
  time,
  event,
  by = NULL,
  times,
  digits = 1,
  extend = TRUE,
  format = c("flextable", "gt", "tibble"),
  theme = c("minimal")
)

Arguments

data

A data.frame containing survival time and event status.

time

Survival follow-up time. Quoted and bare names are accepted.

event

Event indicator. Quoted and bare names are accepted. Numeric 0/1, numeric 1/2, logical, character, and factor variables are accepted. For two-level character or factor variables, the second level is treated as the event.

by

Optional grouping variable for separate Kaplan-Meier survival probabilities. Quoted and bare names are accepted.

times

Numeric vector of follow-up times at which survival probability should be estimated.

digits

Number of digits for percentages and survival probabilities.

extend

Logical. If TRUE, requested times beyond the observed follow-up range are retained using the last available Kaplan-Meier estimate.

format

Output format. One of "flextable" (default), "gt", or "tibble".

theme

Table styling preset.

Value

A list of class c("gtregression","survival_prob", ...) with elements:

table

A flextable, gt_tbl, or NULL when format = "tibble".

table_body

Tibble with Kaplan-Meier survival probabilities.

table_display

Display data frame used to render the table.

fit

Fitted survfit object.

time,event,by,times,format,source

Metadata fields.

Details

Survival probabilities are estimated from survival::survfit() at the requested follow-up times. Events and censored counts are interval counts up to each requested time point as returned by summary.survfit().

Examples

lung_data <- data_lungcancer
lung_data$trt <- factor(lung_data$trt, levels = c(1, 2),
                        labels = c("Standard", "Test"))

survival_prob(
  data = lung_data,
  time = time,
  event = status,
  by = trt,
  times = c(90, 180, 365)
)

survival_prob(
  data = lung_data,
  time = "time",
  event = "status",
  times = c(90, 180),
  format = tibble
)
#> # A tibble: 2 × 8
#>   Group    Time N.risk Events Censored Survival.probability CI.lower CI.upper
#>   <chr>   <dbl>  <dbl>  <dbl>    <dbl>                <dbl>    <dbl>    <dbl>
#> 1 Overall    90     62     73        3                0.464    0.387    0.556
#> 2 Overall   180     27     30        4                0.222    0.161    0.308