Closes #2612 improve missing value handling in compute egfr (#2613)

* #2612 update to allow missing valeus for sex * Update NEWS * #2612 Test: add additional data for testing NA values for sex * Update R/compute_kidney.R Co-authored-by: Stefan Bundfuss <[email protected]> --------- Co-authored-by: Stefan Bundfuss <[email protected]>
pharmaverse · Dec 23, 2024 · 76b83e6 · 76b83e6
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diff --git a/NEWS.md b/NEWS.md
@@ -53,6 +53,8 @@ are not unique. (#2563)
 `derive_extreme_event()`, and `filter_joined()` were updated to reduce their
 memory consumption. (#2590)
 
+- The function `compute_egfr()` updated to allow missing values for sex which result in missing values for output. (#2612)
+
 ## Breaking Changes
 
 - The following function arguments are entering the next phase of the deprecation process: (#2487)

diff --git a/R/compute_kidney.R b/R/compute_kidney.R
@@ -139,7 +139,7 @@ compute_egfr <- function(creat, creatu = "SI", age, weight, sex, race = NULL, me
     optional = TRUE
   ))
   assert_numeric_vector(age)
-  assert_character_vector(sex, values = c("M", "F"))
+  assert_character_vector(sex, values = c("M", "F", NA_character_))
   assert_character_vector(race, optional = TRUE)
   assert_character_scalar(
     method,
@@ -159,9 +159,10 @@ compute_egfr <- function(creat, creatu = "SI", age, weight, sex, race = NULL, me
     egfr <- case_when(
       race == "BLACK OR AFRICAN AMERICAN" & sex == "F" ~ 175 * (scr^-1.154) *
         (age^-0.203) * 0.742 * 1.212,
-      race == "BLACK OR AFRICAN AMERICAN" ~ 175 * (scr^-1.154) * (age^-0.203) * 1.212,
+      race == "BLACK OR AFRICAN AMERICAN" & sex == "M" ~ 175 * (scr^-1.154) * (age^-0.203) * 1.212,
       sex == "F" ~ 175 * (scr^-1.154) * (age^-0.203) * 0.742,
-      sex == "M" ~ 175 * (scr^-1.154) * (age^-0.203)
+      sex == "M" ~ 175 * (scr^-1.154) * (age^-0.203),
+      TRUE ~ NA_real_
     )
   } else if (method == "CRCL") {
     assert_numeric_vector(weight)
@@ -172,7 +173,8 @@ compute_egfr <- function(creat, creatu = "SI", age, weight, sex, race = NULL, me
       tolower(creatu) %in% c("cv", "mg/dl") & sex == "M" ~
         ((140 - age) * weight) / (creat * 72),
       sex == "F" ~ ((140 - age) * weight * 1.04) / creat,
-      sex == "M" ~ ((140 - age) * weight * 1.23) / creat
+      sex == "M" ~ ((140 - age) * weight * 1.23) / creat,
+      TRUE ~ NA_real_
     )
   } else if (method == "CKD-EPI") {
     kappa <- case_when(
@@ -189,7 +191,8 @@ compute_egfr <- function(creat, creatu = "SI", age, weight, sex, race = NULL, me
 
     gender_coefficent <- case_when(
       sex == "F" ~ 1.012,
-      TRUE ~ 1
+      sex == "M" ~ 1,
+      TRUE ~ NA_real_
     )
 
     egfr <- 142 * pmin(scr / kappa, 1)^(alpha) *

diff --git a/tests/testthat/test-compute_kidney.R b/tests/testthat/test-compute_kidney.R
@@ -73,7 +73,9 @@ test_that("compute_egfr Test 7: CKD-EPI calculated on input data", {
     "P01", "P01-1001", 55, "M", "WHITE", 90.7, 96.3, "umol/L",
     "P01", "P01-1002", 52, "F", "BLACK OR AFRICAN AMERICAN", 68, 70, "umol/L",
     "P01", "P01-1003", 67, "M", "BLACK OR AFRICAN AMERICAN", 85, 77, "umol/L",
-    "P01", "P01-1004", 76, "F", "ASIAN", 60, 65, "umol/L"
+    "P01", "P01-1004", 76, "F", "ASIAN", 60, 65, "umol/L",
+    "P01", "P01-1005", 54, NA_character_, "AMERICAN INDIAN OR ALASKA NATIVE", 65, 68,
+    "umol/L",
   )
 
   expected_output <- tibble::tribble(
@@ -82,6 +84,8 @@ test_that("compute_egfr Test 7: CKD-EPI calculated on input data", {
     "P01", "P01-1002", 52, "F", "BLACK OR AFRICAN AMERICAN", 68, 70, "umol/L", 89.7175,
     "P01", "P01-1003", 67, "M", "BLACK OR AFRICAN AMERICAN", 85, 77, "umol/L", 94.5453,
     "P01", "P01-1004", 76, "F", "ASIAN", 60, 65, "umol/L", 84.4646,
+    "P01", "P01-1005", 54, NA_character_, "AMERICAN INDIAN OR ALASKA NATIVE", 65, 68,
+    "umol/L", NA_real_,
   )
 
   egfr <- input %>%