surv_group: Generate Kaplan-Meier Survival Plots for Categorical Groups

In IOBR: Immune Oncology Biological Research

Generate Kaplan-Meier Survival Plots for Categorical Groups

Description

Creates Kaplan-Meier survival plots for data grouped by a categorical variable. Handles both binary and multi-level categorical groups with customizable plot aesthetics.

Usage

surv_group(
  input_pdata,
  target_group,
  ID = "ID",
  levels = c("High", "Low"),
  reference_group = NULL,
  project = NULL,
  time = "time",
  status = "status",
  time_type = "month",
  break_month = "auto",
  cols = NULL,
  palette = "jama",
  mini_sig = "score",
  save_path = NULL,
  fig.type = "pdf",
  index = 1,
  width = 6,
  height = 6.5,
  font.size.table = 3
)

Arguments

input_pdata	Data frame containing survival data and grouping variables.
target_group	Name of column containing the grouping variable.
ID	Name of column with unique identifiers. Default is "ID".
levels	Names for levels of target_group (for binary groups). Default is c("High", "Low").
reference_group	Reference level for binary comparison. Default is NULL.
project	Optional title for plot. Default is NULL.
time	Name of column with follow-up times. Default is "time".
status	Name of column with event indicators. Default is "status".
time_type	Units: "month" or "day". Default is "month".
break_month	X-axis break interval. If "auto", calculated automatically. Default is "auto".
cols	Color vector for plot lines. Default is NULL.
palette	Color palette name. Default is "jama".
mini_sig	Prefix label for variables. Default is "score".
save_path	Directory for saving plot. Default is NULL.
fig.type	File format: "pdf" or "png". Default is "pdf".
index	Identifier for file naming. Default is 1.
width	Plot width. Default is 6.
height	Plot height. Default is 6.5.
font.size.table	Font size for risk table. Default is 3.

Value

Kaplan-Meier plot object.

Author(s)

Dongqiang Zeng

Examples

# Simulate data
set.seed(123)
sim_pdata <- data.frame(
  ID = paste0("Sample", 1:100),
  Lauren = sample(c("Intestinal", "Diffuse"), 100, replace = TRUE),
  time = runif(100, 1, 60),
  OS_status = sample(0:1, 100, replace = TRUE)
)
# Run survival analysis (survival and survminer are imported packages)
result <- surv_group(
  input_pdata = sim_pdata,
  target_group = "Lauren",
  time = "time",
  status = "OS_status",
  save_path = NULL
)
if (!is.null(result)) print(result)

IOBR documentation built on May 30, 2026, 5:07 p.m.