diff --git a/pySEQTarget/expansion/_binder.py b/pySEQTarget/expansion/_binder.py
index 727e0e6..bba0e45 100644
--- a/pySEQTarget/expansion/_binder.py
+++ b/pySEQTarget/expansion/_binder.py
@@ -95,4 +95,15 @@ def _binder(self, kept_cols):
         .drop([f"{self.eligible_col}{self.indicator_baseline}", self.eligible_col])
     )
 
+    # Truncate each (id, trial) at the first outcome event so that subjects who
+    # experience the outcome early are not carried forward with subsequent rows.
+    DT = DT.filter(
+        pl.col(self.outcome_col)
+        .fill_null(0)
+        .cum_max()
+        .shift(1, fill_value=0)
+        .over([self.id_col, "trial"])
+        == 0
+    )
+
     return DT
diff --git a/pyproject.toml b/pyproject.toml
index 1e7dac8..3c97a2c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "pySEQTarget"
-version = "0.12.8"
+version = "0.12.9"
 description = "Sequentially Nested Target Trial Emulation"
 readme = "README.md"
 license = {text = "MIT"}
@@ -25,7 +25,7 @@ authors = [
     {name = "Ryan O'Dea", email = "ryan.odea@psi.ch"},
     {name = "Alejandro Szmulewicz", email = "aszmulewicz@hsph.harvard.edu"},
     {name = "Tom Palmer", email = "tom.palmer@bristol.ac.uk"},
-    {name = "Miguel Hernan", email = "mhernan@hsph.harvard.edu"},
+    {name = "Miguel Hernán", email = "mhernan@hsph.harvard.edu"},
 ]
 
 maintainers = [
diff --git a/tests/test_expansion.py b/tests/test_expansion.py
new file mode 100644
index 0000000..e9e81cb
--- /dev/null
+++ b/tests/test_expansion.py
@@ -0,0 +1,92 @@
+import polars as pl
+
+from pySEQTarget import SEQuential
+
+
+def _make_model(data):
+    return SEQuential(
+        data,
+        id_col="ID",
+        time_col="time",
+        eligible_col="eligible",
+        treatment_col="treatment",
+        outcome_col="outcome",
+        time_varying_cols=[],
+        fixed_cols=[],
+    )
+
+
+def test_expansion_truncates_at_first_outcome():
+    """Expansion should truncate each (id, trial) at and including the first
+    outcome=1 row. Rows from later periods must not appear."""
+    data = pl.DataFrame(
+        {
+            "ID": [1, 1, 1, 1, 1],
+            "time": [0, 1, 2, 3, 4],
+            "eligible": [1, 0, 0, 0, 0],
+            # Both treatment values required by default treatment_level=[0,1]
+            "treatment": [0, 1, 0, 1, 0],
+            # outcome=1 at time=2, but original data continues with outcome=0
+            "outcome": [0, 0, 1, 0, 0],
+        }
+    )
+
+    model = _make_model(data)
+    model.expand()
+
+    # Only trial 0 exists (eligible only at time=0).
+    # Should have followup 0, 1, 2 — the outcome=1 row is included but not beyond.
+    followups = sorted(model.DT["followup"].to_list())
+    assert followups == [0, 1, 2]
+
+    # The outcome=1 row must be present
+    outcome_row = model.DT.filter(pl.col("outcome") == 1)
+    assert len(outcome_row) == 1
+    assert int(outcome_row["followup"][0]) == 2
+
+
+def test_expansion_does_not_truncate_without_outcome():
+    """Subjects who never experience the outcome should retain all expanded rows."""
+    data = pl.DataFrame(
+        {
+            "ID": [1, 1, 1, 1, 1],
+            "time": [0, 1, 2, 3, 4],
+            "eligible": [1, 0, 0, 0, 0],
+            "treatment": [0, 1, 0, 1, 0],
+            "outcome": [0, 0, 0, 0, 0],
+        }
+    )
+
+    model = _make_model(data)
+    model.expand()
+
+    # All 5 followup periods should be present
+    followups = sorted(model.DT["followup"].to_list())
+    assert followups == [0, 1, 2, 3, 4]
+
+
+def test_expansion_truncates_each_trial_independently():
+    """Truncation must apply per (id, trial), not globally. A subject enrolled in
+    multiple trials should have each trial truncated at its own first outcome."""
+    data = pl.DataFrame(
+        {
+            "ID": [1, 1, 1, 1, 1],
+            "time": [0, 1, 2, 3, 4],
+            "eligible": [1, 1, 0, 0, 0],
+            "treatment": [0, 1, 0, 1, 0],
+            # outcome=1 at time=3: trial 0 sees it at followup=3, trial 1 at followup=2
+            "outcome": [0, 0, 0, 1, 0],
+        }
+    )
+
+    model = _make_model(data)
+    model.expand()
+
+    trial_0 = model.DT.filter(pl.col("trial") == 0)
+    trial_1 = model.DT.filter(pl.col("trial") == 1)
+
+    # Trial 0 starts at time=0, outcome at time=3 → followup 0,1,2,3
+    assert sorted(trial_0["followup"].to_list()) == [0, 1, 2, 3]
+
+    # Trial 1 starts at time=1, outcome at time=3 → followup 0,1,2
+    assert sorted(trial_1["followup"].to_list()) == [0, 1, 2]