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Restricted mean survival time table

Source: R/rmst_table.R
rmst_table.Rd

Estimate restricted mean survival time (RMST) up to a user-specified follow-up time. RMST is the average survival time observed within a fixed time window, such as 365 days.

Usage

rmst_table(
  data,
  time,
  event,
  by = NULL,
  tau,
  digits = 1,
  conf.level = 0.95,
  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 RMST estimates. Quoted and bare names are accepted.

tau

Restriction time for RMST. For example, tau = 365 reports mean survival time restricted to the first 365 days of follow-up.

digits

Number of digits for displayed survival time summaries.

conf.level

Confidence level for RMST confidence intervals.

format

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

theme

Table styling preset.

Value

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

table

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

table_body

Tibble with numeric RMST summaries.

table_display

Display data frame used to render the table.

fit

Fitted survfit object.

time,event,by,tau,format,source

Metadata fields.

Details

RMST is estimated from survival::survfit() using Kaplan-Meier methods and summary.survfit(rmean = tau). When by has exactly two groups, the table includes the RMST difference as the second group minus the first group, with a Wald confidence interval and p-value based on the reported RMST standard errors.

Examples

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

rmst_table(
  data = lung_data,
  time = time,
  event = status,
  by = trt,
  tau = 365
)

rmst_table(
  data = lung_data,
  time = "time",
  event = "status",
  tau = 180,
  format = tibble
)
#> # A tibble: 1 × 14
#>   Type  Group     Tau     N Events  RMST    SE CI.lower CI.upper Difference
#>   <chr> <chr>   <dbl> <dbl>  <dbl> <dbl> <dbl>    <dbl>    <dbl>      <dbl>
#> 1 Group Overall   180   137    128  88.5  5.64     77.5     99.6         NA
#> # ℹ 4 more variables: Difference.SE <dbl>, Difference.CI.lower <dbl>,
#> #   Difference.CI.upper <dbl>, p.value <dbl>