Example of the use of the kaplan-Meier survival analysis model

kaplan-meier.R

library(tidyverse)
library(finalfit)
library(survival)

melanoma <- boot::melanoma 

melanoma <- melanoma |>
  mutate(
    status_os = if_else(status == 2, 0,
      1
    ),
    status_dss = if_else(status == 2, 0,
      if_else(status == 1, 1,
        0
      )
    ),
    status_crr = if_else(status == 2, 0,
      if_else(status == 1, 1,
        2
      )
    ),
    age = ff_label(age, "Age (years)"),
    thickness = ff_label(thickness, "Tumour thickness (mm)"),
    sex = factor(sex) |>
      fct_recode(
        "Male" = "1",
        "Female" = "0"
      ) |>
      ff_label("Sex"),
    ulcer = factor(ulcer) |>
      fct_recode(
        "No" = "0",
        "Yes" = "1"
      ) |>
      ff_label("Ulcerated tumour")
  )


# Kaplan Meier

survival_object <- melanoma %$%
  Surv(time, status_os)

survival_object <- melanoma %$%
  Surv(time / 365, status_os)

my_survfit <- survfit(survival_object ~ 1, data = melanoma)

summary(my_survfit, times = c(0, 1, 2, 3, 4, 5))

# Plot
dependent_os <- "Surv(time/365, status_os)"
explanatory <- c("ulcer")

melanoma |> 
  surv_plot(dependent_os, explanatory, pval = TRUE)