diff --git a/R/derive_vars_transposed.R b/R/derive_vars_transposed.R
index d21322e73f..a0b67c1a1b 100644
--- a/R/derive_vars_transposed.R
+++ b/R/derive_vars_transposed.R
@@ -118,6 +118,8 @@ derive_vars_transposed <- function(dataset,
     optional = TRUE
   )
 
+  dataset_merge <- filter_if(dataset_merge, filter)
+
   # check for duplicates in dataset_merge as these will create list columns,
   # which is not acceptable for ADaM datasets
   signal_duplicate_records(
@@ -134,7 +136,6 @@ derive_vars_transposed <- function(dataset,
   )
 
   dataset_transposed <- dataset_merge %>%
-    filter_if(filter) %>%
     pivot_wider(
       names_from = !!key_var,
       values_from = !!value_var,
diff --git a/tests/testthat/test-derive_vars_transposed.R b/tests/testthat/test-derive_vars_transposed.R
index d2e1db5a8d..ee1b8d3cb3 100644
--- a/tests/testthat/test-derive_vars_transposed.R
+++ b/tests/testthat/test-derive_vars_transposed.R
@@ -40,6 +40,15 @@ test_that("derive_vars_transposed Test 2: filtering the merge dataset works", {
     "STUDY01", "P02",       31,    3,
     "STUDY01", "P03",       42,   NA
   )
+
+  dataset_merge <- tibble::tribble(
+    ~STUDYID,  ~USUBJID, ~TESTCD, ~VALUE,
+    "STUDY01", "P01",    "T01",       31,
+    "STUDY01", "P01",    "T02",        5,
+    "STUDY01", "P02",    "T01",        3,
+    "STUDY01", "P01",    "T02",        9
+  )
+
   actual_output <- derive_vars_transposed(
     dataset,
     dataset_merge,