Kidney Failure Risk Equation (KFRE, 2- and 5-year risk)

Compute 2- and 5-year risk of end-stage kidney disease using the original 4-variable KFRE (Tangri et al., 2011) with optional data-quality diagnostics, and verbose progress reporting.

Usage

kidney_failure_risk(
  data,
  col_map = list(age = "age", sex = "sex", eGFR = "eGFR", UACR = "UACR"),
  na_action = c("keep", "error", "omit", "warn"),
  na_warn_prop = 0.2,
  verbose = TRUE
)

Arguments

data

A data.frame or tibble containing at least the columns mapped in col_map.

col_map

Named list mapping:

• age -> age in years

• sex -> sex code (1 = male, 2 = female)

• eGFR -> estimated GFR (mL/min/1.73 m^2)

• UACR -> urine albumin-to-creatinine ratio (mg/g)

na_action

One of c("keep","error","omit","warn"). Default "keep" to preserve previous behavior:

• "keep": propagate NA/NaN through logs and outputs.

• "error": abort if any required input contains missing values.

• "omit": drop rows with NA in required inputs before computation.

• "warn": like "keep" but emits high-missingness warnings.

na_warn_prop

Numeric in \([0,1]\); per-variable threshold for high-missingness warnings. Default 0.2.

verbose

Logical; if TRUE, prints stepwise messages and a completion summary. Default TRUE.

Value

A tibble with:

• KFRE_2yr risk (0-1) at 2 years

• KFRE_5yr risk (0-1) at 5 years

Details

This function preserves prior behavior by default:

• Inputs are taken as-is; NA values propagate to outputs (na_action = "keep").

• No capping or out-of-range checks are applied.

Units (no automatic conversion):

• age: years; sex: 1 = male, 2 = female

• eGFR: mL/min/1.73 m^2

• UACR: mg/g (albumin-to-creatinine ratio)

Details

• Prognostic index: PI = 0.220 x log(age) + (-0.556) x log(eGFR) + 0.451 x log(UACR) + 0.391 x (male) where male = 1 if sex == 1, else 0.

• Baseline survival: S0(2y) = 0.934, S0(5y) = 0.881 (Tangri 2011).

• Risks: KFRE_t = 1 - (S0_t ^ exp(PI)).

• The 2016 JAMA study provides a large, multinational validation of the KFRE in humans.

• This implementation computes the original 4-variable linear predictor and does not apply recalibration or alternative coefficient sets.

References

Tangri N, Stevens LA, Griffith J, others (2011). “A predictive model for progression of chronic kidney disease to kidney failure.” JAMA, 305(15), 1553–1559. doi:10.1001/jama.2011.451 . Tangri N, Grams ME, Levey AS, others (2016). “Multinational assessment of accuracy of equations for predicting risk of kidney failure: a meta-analysis.” JAMA, 315(2), 164–174. doi:10.1001/jama.2015.18202 .

See also

inflammatory_markers(), iAge(), impute_missing()

Examples

library(tibble)
df <- tibble(
  age  = c(65, 72),
  sex  = c(1, 2),          # 1 = male, 2 = female
  eGFR = c(45, 22),        # mL/min/1.73 m^2
  UACR = c(300, 1200)      # mg/g
)
# Default behavior (NA propagate, no extreme checks)
kidney_failure_risk(
  data = df,
  col_map = list(age = "age", sex = "sex", eGFR = "eGFR", UACR = "UACR")
)
#> kidney_failure_risk(): reading input 'df' — 2 rows × 4 variables
#> kidney_failure_risk(): col_map: age -> 'age', sex -> 'sex', eGFR -> 'eGFR', UACR -> 'UACR'
#> kidney_failure_risk(): computing markers:
#>   KFRE_2yr  [age, sex, eGFR, UACR -- 2-year kidney failure risk]
#>   KFRE_5yr  [age, sex, eGFR, UACR -- 5-year kidney failure risk]
#> kidney_failure_risk(): results: KFRE_2yr 2/2, KFRE_5yr 2/2
#> # A tibble: 2 × 2
#>   KFRE_2yr KFRE_5yr
#>      <dbl>    <dbl>
#> 1    0.329    0.523
#> 2    0.536    0.759

# With verbose output
# \donttest{
kidney_failure_risk(
  data = df,
  col_map = list(age = "age", sex = "sex", eGFR = "eGFR", UACR = "UACR"),
  verbose = TRUE
)
#> kidney_failure_risk(): reading input 'df' — 2 rows × 4 variables
#> kidney_failure_risk(): col_map: age -> 'age', sex -> 'sex', eGFR -> 'eGFR', UACR -> 'UACR'
#> kidney_failure_risk(): computing markers:
#>   KFRE_2yr  [age, sex, eGFR, UACR -- 2-year kidney failure risk]
#>   KFRE_5yr  [age, sex, eGFR, UACR -- 5-year kidney failure risk]
#> kidney_failure_risk(): results: KFRE_2yr 2/2, KFRE_5yr 2/2
#> # A tibble: 2 × 2
#>   KFRE_2yr KFRE_5yr
#>      <dbl>    <dbl>
#> 1    0.329    0.523
#> 2    0.536    0.759
# }