install.packages("kfre")

# install.packages("remotes")
remotes::install_github("lshpaner/kfre_r")

toy <- data.frame(
  age = c(55, 72),
  sex_txt = c("male", "female"),
  eGFR = c(45, 28),
  uACR = c(120, 800),
  dm = c(1, 0),
  htn = c(1, 1),
  albumin = c(4.2, 3.4),
  phosphorous = c(3.3, 4.6),
  bicarbonate = c(24, 22),
  calcium = c(9.1, 9.8),
  stringsAsFactors = FALSE
)

cols <- list(
  age = "age",
  sex = "sex_txt",
  eGFR = "eGFR",
  uACR = "uACR",
  dm = "dm",
  htn = "htn",
  albumin = "albumin",
  phosphorous = "phosphorous",
  bicarbonate = "bicarbonate",
  calcium = "calcium"
)

rp <- RiskPredictor$new(df = toy, columns = cols)

# 4-variable KFRE (2-year), North America constants
p4_2y <- rp$predict_kfre(
  years = 2, is_north_american = TRUE,
  use_extra_vars = FALSE, num_vars = 4
)

# 6-variable KFRE (5-year)
p6_5y <- rp$predict_kfre(
  years = 5, is_north_american = TRUE,
  use_extra_vars = TRUE, num_vars = 6
)

# 8-variable KFRE (2-year)
p8_2y <- rp$predict_kfre(
  years = 2, is_north_american = TRUE,
  use_extra_vars = TRUE, num_vars = 8
)

p4_2y
p6_5y
p8_2y

# Male, 55yo, 2-year risk (4-var)
rp$kfre_person(
  age = 55, is_male = TRUE,
  eGFR = 45, uACR = 120,
  is_north_american = TRUE, years = 2
)

# Female, 72yo, 5-year risk (6-var)
rp$kfre_person(
  age = 72, is_male = FALSE,
  eGFR = 28, uACR = 800,
  is_north_american = TRUE, years = 5,
  dm = 0, htn = 1
)

# Female, 72yo, 2-year risk (8-var)
rp$kfre_person(
  age = 72, is_male = FALSE,
  eGFR = 28, uACR = 800,
  is_north_american = TRUE, years = 2,
  albumin = 3.4, phosphorous = 4.6, bicarbonate = 22, calcium = 9.8
)

toy_kfre <- add_kfre_risk_col(
  df = toy,
  age_col = "age",
  sex_col = "sex_txt",
  eGFR_col = "eGFR",
  uACR_col = "uACR",
  dm_col = "dm",
  htn_col = "htn",
  albumin_col = "albumin",
  phosphorous_col = "phosphorous",
  bicarbonate_col = "bicarbonate",
  calcium_col = "calcium",
  num_vars = c(4, 6, 8),
  years = c(2, 5),
  is_north_american = TRUE,
  copy = TRUE
)

names(toy_kfre)
head(toy_kfre)
# Adds:
# kfre_4var_2year, kfre_4var_5year,
# kfre_6var_2year, kfre_6var_5year,
# kfre_8var_2year, kfre_8var_5year

# ESRD outcome within 2 years (duration is in days → converted to years)
out <- data.frame(
  eGFR = c(95, 25),
  ESRD_flag = c(1, 1),
  followup_days = c(200, 1000)
)

out <- class_esrd_outcome(
  df = out,
  col = "ESRD_flag",
  years = 2,
  duration_col = "followup_days",
  prefix = "esrd",
  create_years_col = TRUE
)
# Adds: ESRD_duration_years and esrd_2_year_outcome

# CKD stage labels
out <- class_ckd_stages(
  df = out,
  egfr_col = "eGFR",
  stage_col = "stage",
  combined_stage_col = "stage_combined"
)

table(out$stage)
table(out$stage_combined)

df_pcr <- data.frame(
  sex = c("female","male","female"),
  dm  = c(1,0,1),
  htn = c(1,1,0),
  pcr = c(150, 600, 50)
)

acr <- upcr_uacr(
  df_pcr,
  sex_col = "sex",
  diabetes_col = "dm",
  hypertension_col = "htn",
  upcr_col = "pcr",
  female_str = "female"
)

acr

met <- eval_kfre_metrics(
  df = toy_kfre,                 # must contain truth + prediction columns
  n_var_list = c(4, 6, 8),
  outcome_years = c(2, 5),
  decimal_places = 4
)

met
# Rows: Metrics; Cols: "{2_year|5_year}_{4|6|8}_var_kfre"

# Basic: compute & plot both ROC and PR (no files written)
plot_kfre_metrics(
  df = toy_kfre,
  num_vars = c(4, 6, 8),
  plot_type = "all_plots",
  mode = "both",              # compute + plot
  show_years = c(2, 5)
)

# Save to disk (PNG/SVG)
plot_kfre_metrics(
  df = toy_kfre,
  num_vars = c(4, 6),
  plot_type = "auc_roc",
  mode = "both",
  show_years = c(2, 5),
  save_plots = TRUE,
  image_path_png = "plots",
  image_prefix = "kfre"
)

library(devtools)
devtools::load_all(".")
devtools::test()