[KM plot] Plotting a KM survival plot #km #plot #survival

plot_km_survival.R

library("tidyverse")
library("survival")
library("survminer")


# Fit model on survival data:
fit01 <- survfit(Surv(time=Time_survival, 
                      event=Status_survival) ~ as.factor(group), 
                 data = clin_dat)
fit01_cph <- coxph(Surv(time=Time_survival, 
                      event=Status_survival) ~ as.factor(group),
                   data =  clin_dat)

# Extract HR, p-value:
fit01_hr <- summary(fit01_cph)$conf.int[1] %>% 
  as.numeric() %>% 
  round(3)
fit01_hr_ci_lower <- summary(fit01_cph)$conf.int[3] %>% 
  as.numeric() %>% 
  round(3)
fit01_hr_ci_upper <- summary(fit01_cph)$conf.int[4] %>% 
  as.numeric() %>% 
  round(3)
fit01_p <- summary(fit01_cph)$logtest[3] %>% 
  as.numeric() %>% 
  round(3)

# Annotation text:
annot <- paste0("HR=", fit01_hr, " (95% CI=", fit01_hr_ci_lower, "-",
                fit01_hr_ci_upper, ")\n",
                "p=", fit01_p)

# Create plot object:
plot <- ggsurvplot(
  fit01,                     # survfit object with calculated statistics.
  pval = F,             # show p-value of log-rank test.
  conf.int = TRUE,         # show confidence intervals for 
  title="Disease-specific survival",                       
  conf.int.style = "step",  # customize style of confidence intervals
  xlab = "Time in days",   # customize X axis label.
  break.time.by = 200,     # break X axis in time intervals by 200.
  ggtheme = theme_light(), # customize plot and risk table with a theme.
  risk.table =T,  # absolute number and percentage at risk.
  risk.table.y.text.col = T,# colour risk table text annotations.
  risk.table.y.text = T,                     # in legend of risk table.
  ncensor.plot = F,      # plot the number of censored subjects at time t
  surv.median.line = "hv",#,  # add the median survival pointer.
  legend.labs = c("MPS1", "MPS2"),    # change legend labels.
  palette = c("#E7B800", "#2E9FDF"))

# Add annotation text:
plot$plot <- plot$plot +
  ggplot2::annotate(
    "text",
    x = Inf, y = Inf,
    vjust = 1, hjust = 1,
    label = annot,
    size = 5
  )

# Plot:
plot