diff --git a/doc/source/whatsnew/v1.2.0.rst b/doc/source/whatsnew/v1.2.0.rst
index 8dbc6728dccfe..b166f0a360d26 100644
--- a/doc/source/whatsnew/v1.2.0.rst
+++ b/doc/source/whatsnew/v1.2.0.rst
@@ -771,6 +771,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrame.groupby` dropped ``nan`` groups from result with ``dropna=False`` when grouping over a single column (:issue:`35646`, :issue:`35542`)
 - Bug in :meth:`.DataFrameGroupBy.head`, :meth:`.DataFrameGroupBy.tail`, :meth:`SeriesGroupBy.head`, and :meth:`SeriesGroupBy.tail` would raise when used with ``axis=1`` (:issue:`9772`)
 - Bug in :meth:`.DataFrameGroupBy.transform` would raise when used with ``axis=1`` and a transformation kernel (e.g. "shift") (:issue:`36308`)
+- Bug in :meth:`.DataFrameGroupBy.apply` dropped values on ``nan`` group when returning the same axes with the original frame (:issue:`38227`)
 - Bug in :meth:`.DataFrameGroupBy.quantile` couldn't handle with arraylike ``q`` when grouping by columns (:issue:`33795`)
 - Bug in :meth:`DataFrameGroupBy.rank` with ``datetime64tz`` or period dtype incorrectly casting results to those dtypes instead of returning ``float64`` dtype (:issue:`38187`)
 
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 583fc6bf8ddb7..4b9e554aa8bc2 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1216,7 +1216,7 @@ def reset_identity(values):
 
         if not not_indexed_same:
             result = concat(values, axis=self.axis)
-            ax = self._selected_obj._get_axis(self.axis)
+            ax = self.filter(lambda x: True).axes[self.axis]
 
             # this is a very unfortunate situation
             # we can't use reindex to restore the original order
diff --git a/pandas/tests/groupby/test_apply.py b/pandas/tests/groupby/test_apply.py
index b2074dcb08c95..975cebe16dc55 100644
--- a/pandas/tests/groupby/test_apply.py
+++ b/pandas/tests/groupby/test_apply.py
@@ -1087,3 +1087,25 @@ def test_apply_by_cols_equals_apply_by_rows_transposed():
 
     tm.assert_frame_equal(by_cols, by_rows.T)
     tm.assert_frame_equal(by_cols, df)
+
+
+def test_apply_dropna_with_indexed_same():
+    # GH 38227
+
+    df = DataFrame(
+        {
+            "col": [1, 2, 3, 4, 5],
+            "group": ["a", np.nan, np.nan, "b", "b"],
+        },
+        index=list("xxyxz"),
+    )
+    result = df.groupby("group").apply(lambda x: x)
+    expected = DataFrame(
+        {
+            "col": [1, 4, 5],
+            "group": ["a", "b", "b"],
+        },
+        index=list("xxz"),
+    )
+
+    tm.assert_frame_equal(result, expected)