Kaplan-Meier Plot

Source: R/gg_km.R

This set of functions facilitates the creation of Kaplan-Meier survival plots using ggplot2. Use process_survfit() to prepare the survival data from a fitted survfit object, and then gg_km() to generate the Kaplan-Meier plot with various customization options. Additional functions like annot_surv_med(), annot_cox_ph(), and annotate_riskdf() allow for adding summary tables and annotations to the plot.

process_survfit(fit_km, strata_levels = "All", max_time = NULL)

gg_km(
  surv_plot_data,
  lty = NULL,
  lwd = 0.5,
  censor_show = TRUE,
  size = 2,
  max_time = NULL,
  xticks = NULL,
  yval = c("Survival", "Failure"),
  ylim = NULL,
  font_size = 10,
  legend_pos = NULL
)

Arguments

fit_km

A fitted Kaplan-Meier object of class survfit.

strata_levels

(string)
A single character string used as the strata level if the input fit_km object has no strata (e.g., "All").

max_time

(numeric)
A single numeric value defining the maximum time point to display on the x-axis.

surv_plot_data

(data.frame)
A data frame containing the pre-processed survival data, ready for plotting. This data should be equivalent to the output of process_survfit.

lty

(numeric or NULL)
A numeric vector of line types (e.g., 1 for solid, 2 for dashed) for the survival curves, or NULL for ggplot2 defaults. The length should match the number of arms/groups.

lwd

(numeric)
A single numeric value specifying the line width for the survival curves.

censor_show

(logical)
A single logical value indicating whether to display censoring marks on the plot. Defaults to TRUE.

size

(numeric)
A single numeric value specifying the size of the censoring marks.

xticks

(numeric or NULL)
A numeric vector of explicit x-axis tick positions, or a single numeric value representing the interval between ticks, or NULL for automatic ggplot2 scaling.

yval

(character)
A single character string, either "Survival" or "Failure" to plot the corresponding probability.

ylim

(numeric)
A numeric vector of length 2 defining the lower and upper limits of the y-axis (e.g., c(0, 1)).

font_size

(numeric)
A single numeric value specifying the base font size for the plot theme elements.

legend_pos

(numeric or NULL)
A numeric vector of length 2 defining the legend position as (x, y) coordinates relative to the plot area (ranging from 0 to 1), or NULL for automatic placement.

Value

The function process_survfit returns a data frame containing the survival curve steps, confidence intervals, and censoring info.

The function gg_km returns a ggplot2 object of the KM plot.

Details

Data setup assumes "time" is event time, "status" is event indicator (1 represents an event), while "arm" is the treatment group.

Functions

  • process_survfit(): takes a fitted survival::survfit object and processes it into a data frame suitable for plotting a Kaplan-Meier curve with ggplot2. Time zero is also added to the data.

  • gg_km(): creates a Kaplan-Meier survival curve, with support for various customizations like censoring marks, Confidence Intervals (CIs), and axis control.

Examples

# Data preparation for KM plot
use_lung <- survival::lung
use_lung$arm <- factor(sample(c("A", "B", "C"), nrow(use_lung), replace = TRUE))
use_lung$status <- use_lung$status - 1 # Convert status to 0/1
use_lung <- na.omit(use_lung)

# Fit Kaplan-Meier model
formula <- survival::Surv(time, status) ~ arm
fit_kmg01 <- survival::survfit(formula, use_lung)

# Process survfit data for plotting
surv_plot_data <- process_survfit(fit_kmg01)
head(surv_plot_data)
#> # A tibble: 6 × 10
#>    time n.risk n.event n.censor estimate std.error conf.high conf.low strata
#>   <dbl>  <dbl>   <dbl>    <dbl>    <dbl>     <dbl>     <dbl>    <dbl> <fct> 
#> 1     0     58       0        0    1        0          1        1     A     
#> 2     5     57       1        0    0.982    0.0177     1        0.949 A     
#> 3    15     56       1        0    0.965    0.0253     1        0.918 A     
#> 4    31     55       1        0    0.947    0.0312     1        0.891 A     
#> 5    54     54       1        0    0.930    0.0364     0.999    0.866 A     
#> 6    59     53       1        0    0.912    0.0411     0.989    0.842 A     
#> # ℹ 1 more variable: censor <dbl>

# Example of making the KM plot
plt_kmg01 <- gg_km(surv_plot_data)

# Confidence Interval as Ribbon
plt_kmg01 +
  ggplot2::geom_ribbon(alpha = 0.3, lty = 0, na.rm = TRUE)


# Adding Title and Footnotes
plt_kmg01 +
  ggplot2::labs(title = "title", caption = "footnotes")


# Changing xlab and ylab
plt_kmg01 +
  ggplot2::xlab("Another Day") +
  ggplot2::ylab("THE Survival Probability")