OC 24.2 - VALIDATION OF A TREATMENT DECISION ALGORITHM FOR THE USE OF ANDEXANET ALFA IN ACUTE LIFE-THREATENING BLEEDING FROM DIRCT FACTOR Xa INHIBITORS

Sunday, July 10, 2022

3:00 PM – 3:15 PM

Location: ExCel Center, ICC Capital Suite Room 14-16

Presentation Format: In-Person

Presenting Author(s)

Jan Beyer-Westendorf, MD,PhD

Head of thrombosis research unit
University Hospital “Carl Gustav Carus”, Technische Universität Dresden, Division of Hematology and Hemostasis, Department of Medicine I Thrombosis Research, Dresden, Saxony, Germany
Dresden, Sachsen, Germany

Co-Author(s)

JK

Jürgen Koscielny

Leiter mit KV-Sitz (AGZ) und Oberarzt (ZTB)
Charité – Universitätsmedizin Berlin
Berlin, Berlin, Germany

Background: Andexanet alfa (AA) is approved for reversing direct factor Xa inhibitors (DXI) in life-threatening bleeding. However, AA label only provides dosing recommendations but does not specify in whom AA reversal is indicated or not. Under-treatment (continuous bleeding) and over-treatment (thrombotic risk) are clinical concerns. Anti-Xa activity tests are often not available to guide treatment decisions. A clinical decision pathway reducing the risk or over- and under-treatment is urgently needed.

Aims: To validate an AA treatment decision algorithm derived from an interdisciplinary
German expert consensus group (Figure 1).

Methods: The algorithm was retrospectively applied to 100 cases (acute life threatening DXI bleeding and documented anti-Xa activity levels), identified in charts from Dresden University Hospital, Germany and Charitè Berlin, Germany. The algorithm performance was compared against a label-conform decision to “reverse all”. Correctness of treatment indication was judged against three commonly used clinical AA treatment thresholds for anti-Xa activities: < 35 ng/ml; < 50 ng/ml and < 75 ng/ml.

Results: Of the 100 patients, 7% had aXa activities < 35 ng/ml; 11% < 50 ng/ml and 21% < 75 ng/ml but all would normally have received AA reversal. Application of a cut-off “last intake > 18 hours” (as applied in AA trials and used in clinical routine) would have excluded 12% from AA therapy, of whom 4 (33%) had aXa activities > 75 ng/ml. Table 1 indicates that, without an algorithm, the risk of over-treatment increases with increasing treatment indication thresholds. Application of the algorithm resulted in “correct indications” in 67-73% without delay from aXa activity test, which increased to 89-95% if 22% of cases would receive testing. The algorithm reduced risk of over-treatment considerably without increasing the risk of under-treatment.

Conclusion(s): The proposed algorithm can improve AA treatment decisions and reduces the risk of over-treatment. Further validation is currently ongoing.