# Load required libraries
library(ggplot2)
library(ggpubr)
library(survminer)
library(survival)

# Load data
data_1 <- read.csv(file = "XXX.csv", header = TRUE, sep = ",")

# Define variables, titles, and thresholds
predictors <- c("SII1424.8", "NLR2.8", "MLR0.2", "PLR184.4")
titles <- c("SII", "NLR", "MLR", "PLR")
thresholds <- c(1424.8, 2.8, 0.2, 184.4)

# Create a list to store survival curve plots
plots <- list()

# Iterate through each variable, fit survival curves, and create plots
for (i in 1:4) {
  predictor <- predictors[i]
  title <- titles[i]
  threshold <- thresholds[i]
  
  # Fit survival curve
  fit <- survfit(as.formula(paste("Surv(OSM, CENSOR) ~", predictor)), data = data_1)
  
  # Calculate sample sizes for legend labels
  n0 <- sum(data_1[[predictor]] == 0)
  n1 <- sum(data_1[[predictor]] == 1)
  legend.labs <- c(paste0(title, " ≤ ", threshold, " (n=", n0, ")"),
                   paste0(title, " > ", threshold, " (n=", n1, ")"))
  
  # Create survival curve plot
  p <- ggsurvplot(fit, data = data_1,
                  title = title,                    # Set title (SII, NLR, MLR, PLR)
                  pval = TRUE, pval.method = FALSE, # Display p-value, hide method
                  legend.title = paste0(title, " Level"), # Legend title
                  legend.labs = legend.labs,        # Legend labels, including sample sizes
                  palette = c("dodgerblue3", "firebrick2"), # Color scheme
                  risk.table = TRUE,                # Include risk table
                  cumevents = TRUE,                 # Include cumulative events table
                  tables.height = 0.15,             # Table height
                  tables.theme = theme_cleantable(),# Clean table theme
                  tables.y.text = FALSE,            # Remove y-axis text in tables
                  xlab = "Survival (Months)",       # x-axis label
                  break.time.by = 15)               # x-axis time interval
  
  # Store the plot in the list
  plots[[i]] <- p
}

# Arrange the four plots into a 2x2 grid
arrange_ggsurvplots(plots, print = TRUE, ncol = 2, nrow = 2)