diff --git a/pandas/core/construction.py b/pandas/core/construction.py
index 8df4f7e3e08f9..baf2e63918829 100644
--- a/pandas/core/construction.py
+++ b/pandas/core/construction.py
@@ -509,15 +509,20 @@ def ensure_wrapped_if_datetimelike(arr):
 
 def sanitize_masked_array(data: ma.MaskedArray) -> np.ndarray:
     """
-    Convert numpy MaskedArray to ensure mask is softened.
+    Convert numpy MaskedArray to ensure mask is softened,
+
     """
     mask = ma.getmaskarray(data)
     if mask.any():
-        dtype, fill_value = maybe_promote(data.dtype, np.nan)
-        dtype = cast(np.dtype, dtype)
-        data = ma.asarray(data.astype(dtype, copy=True))
-        data.soften_mask()  # set hardmask False if it was True
-        data[mask] = fill_value
+        dtype = cast(np.dtype, data.dtype)
+        if isinstance(dtype, ExtensionDtype) and dtype.name.startswith("Masked"):
+            data = ma.asarray(data.astype(dtype, copy=True))
+            data.soften_mask()  # If the data is a Masked EA, directly soften the mask.
+        else:
+            dtype, fill_value = maybe_promote(data.dtype, np.nan)
+            data = ma.asarray(data.astype(dtype, copy=True))
+            data.soften_mask()  # set hardmask False if it was True
+            data[mask] = fill_value
     else:
         data = data.copy()
     return data
diff --git a/pandas/tests/dtypes/cast/test_construct_ndarray.py b/pandas/tests/dtypes/cast/test_construct_ndarray.py
index 6b9b2dfda6e8b..609123f1d4642 100644
--- a/pandas/tests/dtypes/cast/test_construct_ndarray.py
+++ b/pandas/tests/dtypes/cast/test_construct_ndarray.py
@@ -34,3 +34,38 @@ def test_construct_1d_ndarray_preserving_na_datetimelike(dtype):
 
     result = sanitize_array(arr, index=None, dtype=np.dtype(object))
     tm.assert_numpy_array_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "values, dtype, expected",
+    [
+        (
+            np.ma.masked_array([1, 2, 3], mask=[False, True, False]),
+            "int64",
+            np.array([1, 2, 3], dtype=np.int64),
+        ),
+        (
+            np.ma.masked_array([1, 2, 3], mask=[False, True, False]),
+            "float64",
+            np.array([1, 2, 3], dtype=np.float64),
+        ),
+        (
+            np.ma.masked_array([1, 2, 3], mask=[False, True, False]),
+            "UInt64",
+            np.array([1, 2, 3], dtype=np.uint64),
+        ),
+        (
+            np.ma.masked_array([1.0, 2.0, 3.0], mask=[False, True, False]),
+            "float64",
+            np.array([1.0, 2.0, 3.0], dtype=np.float64),
+        ),
+        (
+            np.ma.masked_array([1.0, 2.0, 3.0], mask=[False, True, False]),
+            "Int64",
+            np.array([1, 2, 3], dtype=np.int64),
+        ),
+    ],
+)
+def test_sanitize_masked_array_with_masked_ea(values, dtype, expected):
+    result = sanitize_array(values, index=None, dtype=dtype)
+    tm.assert_masked_array_equal(result, expected)