diff --git a/ehrapy/plot/_survival_analysis.py b/ehrapy/plot/_survival_analysis.py
index c135d582..0eb7a55e 100644
--- a/ehrapy/plot/_survival_analysis.py
+++ b/ehrapy/plot/_survival_analysis.py
@@ -183,6 +183,8 @@ def kmf(
 
 def kaplan_meier(
     kmfs: Sequence[KaplanMeierFitter],
+    *,
+    diplay_table: bool = False,
     ci_alpha: list[float] | None = None,
     ci_force_lines: list[Boolean] | None = None,
     ci_show: list[Boolean] | None = None,
@@ -204,6 +206,7 @@ def kaplan_meier(
 
     Args:
         kmfs: Iterables of fitted KaplanMeierFitter objects.
+        diplay_table: Display the survival probabilities in a table, below the plot.
         ci_alpha: The transparency level of the confidence interval. If more than one kmfs, this should be a list.
         ci_force_lines: Force the confidence intervals to be line plots (versus default shaded areas).
                         If more than one kmfs, this should be a list.
@@ -297,37 +300,38 @@ def kaplan_meier(
         ax.set_title(title)
 
     # Prepare data for the table
-    xticks = [x for x in ax.get_xticks() if x >= 0]
-    xticks_space = xticks[1] - xticks[0]
-    if xlabel is None:
-        xlabel = "Time"
-
-    yticks = np.arange(len(kmfs))
-
-    ax_table = plt.subplot(spec[1, 0])
-    ax_table.set_xticks(xticks)
-    ax_table.set_xlim(-xticks_space / 2, xticks[-1] + xticks_space / 2)
-    ax_table.set_ylim(-1, len(kmfs))
-    ax_table.set_yticks(yticks)
-    ax_table.set_yticklabels([kmf.label if kmf.label else f"Group {i + 1}" for i, kmf in enumerate(kmfs[::-1])])
-
-    for i, kmf in enumerate(kmfs[::-1]):
-        survival_probs = kmf.survival_function_at_times(xticks).values
-        for j, prob in enumerate(survival_probs):
-            ax_table.text(
-                xticks[j],  # x position
-                yticks[i],  # y position
-                f"{prob:.2f}",  # formatted survival probability
-                ha="center",
-                va="center",
-                bbox={"boxstyle": "round,pad=0.2", "edgecolor": "none", "facecolor": "lightgrey"},
-            )
-
-    ax_table.grid(grid)
-    ax_table.spines["top"].set_visible(False)
-    ax_table.spines["right"].set_visible(False)
-    ax_table.spines["bottom"].set_visible(False)
-    ax_table.spines["left"].set_visible(False)
+    if diplay_table:
+        xticks = [x for x in ax.get_xticks() if x >= 0]
+        xticks_space = xticks[1] - xticks[0]
+        if xlabel is None:
+            xlabel = "Time"
+
+        yticks = np.arange(len(kmfs))
+
+        ax_table = plt.subplot(spec[1, 0])
+        ax_table.set_xticks(xticks)
+        ax_table.set_xlim(-xticks_space / 2, xticks[-1] + xticks_space / 2)
+        ax_table.set_ylim(-1, len(kmfs))
+        ax_table.set_yticks(yticks)
+        ax_table.set_yticklabels([kmf.label if kmf.label else f"Group {i + 1}" for i, kmf in enumerate(kmfs[::-1])])
+
+        for i, kmf in enumerate(kmfs[::-1]):
+            survival_probs = kmf.survival_function_at_times(xticks).values
+            for j, prob in enumerate(survival_probs):
+                ax_table.text(
+                    xticks[j],  # x position
+                    yticks[i],  # y position
+                    f"{prob:.2f}",  # formatted survival probability
+                    ha="center",
+                    va="center",
+                    bbox={"boxstyle": "round,pad=0.2", "edgecolor": "none", "facecolor": "lightgrey"},
+                )
+
+        ax_table.grid(grid)
+        ax_table.spines["top"].set_visible(False)
+        ax_table.spines["right"].set_visible(False)
+        ax_table.spines["bottom"].set_visible(False)
+        ax_table.spines["left"].set_visible(False)
 
     if not show:
         return ax