Report statistics from survfit tables inline

Extracts and returns statistics from a tbl_survfit object for inline reporting in an R markdown document. Detailed examples in the inline_text vignette

# S3 method for class 'tbl_survfit'
inline_text(
  x,
  variable = NULL,
  level = NULL,
  pattern = NULL,
  time = NULL,
  prob = NULL,
  column = NULL,
  estimate_fun = x$inputs$estimate_fun,
  pvalue_fun = label_style_pvalue(prepend_p = TRUE),
  ...
)

Arguments

x

(tbl_survfit)
Object created from tbl_survfit()

variable

(tidy-select)
Variable name of statistic to present.

level

(string)
Level of the variable to display for categorical variables. Can also specify the 'Unknown' row. Default is NULL

pattern

(string)
String indicating the statistics to return.

time, prob

(numeric scalar)
time or probability for which to return result

column

(tidy-select)
column to print from x$table_body. Columns may be selected with time or prob arguments as well.

estimate_fun

(function)
Function to round and format estimate and confidence limits. Default is the same function used in tbl_survfit()

pvalue_fun

(function)
Function to round and format p-values. Default is label_style_pvalue(). The function must have a numeric vector input, and return a string that is the rounded/formatted p-value (e.g. pvalue_fun = label_style_pvalue(digits = 2)).

...

These dots are for future extensions and must be empty.

Value

A string reporting results from a gtsummary table

Author

Daniel D. Sjoberg

Examples

library(survival)

# fit survfit
fit1 <- survfit(Surv(ttdeath, death) ~ trt, trial)
fit2 <- survfit(Surv(ttdeath, death) ~ 1, trial)

# sumarize survfit objects
tbl1 <-
  tbl_survfit(
    fit1,
    times = c(12, 24),
    label = ~"Treatment",
    label_header = "**{time} Month**"
  ) %>%
  add_p()

tbl2 <-
  tbl_survfit(
    fit2,
    probs = 0.5,
    label_header = "**Median Survival**"
  )

# report results inline
inline_text(tbl1, time = 24, level = "Drug B")
#> [1] "41% (33%, 52%)"
inline_text(tbl1, time = 24, level = "Drug B",
            pattern = "{estimate} [95% CI {conf.low}, {conf.high}]")
#> 41% [95% CI 33%, 52%]
inline_text(tbl1, column = p.value)
#> [1] "p=0.2"
inline_text(tbl2, prob = 0.5)
#> [1] "22 (21, —)"