library(here)
library(forestplot)
library(stringr)
library(dplyr)

save.image(file = 'forest_plot_20260410.RData')
load(file = 'forest_plot_20260410.RData')

# -------------------- DATA Input --------------------
path <- here("COPD10_mace_corrected_results_table_Main_Analysis.csv")
raw_data <- read.csv(path)

# -------------------- DATA Clean --------------------
# for select the data which needed to be presentation
raw_data <- raw_data %>% 
  dplyr::filter(!Outcome %in% c("ARF", "ICU", "HF*", "Pneumonia"))

# below is a standard pipeline
clean_data <- str_match(raw_data$aHR..95..CI., "([0-9\\.]+) \\(([0-9\\.]+), ([0-9\\.]+)\\)")

plot_data <- data.frame(
  mean = as.numeric(clean_data[,2]),
  lower = as.numeric(clean_data[,3]),
  upper = as.numeric(clean_data[,4])
)

table_text <- cbind(
  c("Outcome", raw_data$Outcome),
  c("aHR (95% CI)", raw_data$aHR..95..CI.)
)

forestplot(
  labeltext = table_text,
  mean = c(NA, plot_data$mean),   # First row is title -> NA
  lower = c(NA, plot_data$lower),
  upper = c(NA, plot_data$upper),
  zero = 1,                       # HR baseline = 1
  clip = c(0.4, 1.0), 
  xticks = c(0.4, 0.6, 0.8, 1.0),
  is.summary = c(TRUE, rep(FALSE, nrow(raw_data))), # bold title
  boxsize = 0.2,
  vertices = TRUE,
  col = fpColors(box = "royalblue", line = "darkblue", zero = "gray50"),
  xlab = "Adjusted Hazard Ratio",
  txt_gp = fpTxtGp(label = gpar(cex = 0.9), ticks = gpar(cex = 0.8))
)
2026年4月10日 研究日志¶

2026年4月10日研究日志¶
