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Consensus recommendations on the management of toxicity associated with CD3×CD20 bispecific antibody therapy.

Authors :
Crombie JL
Graff T
Falchi L
Karimi YH
Bannerji R
Nastoupil L
Thieblemont C
Ursu R
Bartlett N
Nachar V
Weiss J
Osterson J
Patel K
Brody J
Abramson JS
Lunning M
Shah NN
Ayed A
Kamdar M
Parsons B
Caimi P
Flinn I
Herrera A
Sharman J
McKenna M
Armand P
Kahl B
Smith S
Zelenetz A
Budde LE
Hutchings M
Phillips T
Dickinson M
Source :
Blood [Blood] 2024 Apr 18; Vol. 143 (16), pp. 1565-1575.
Publication Year :
2024

Abstract

Abstract: Bispecific antibodies (BsAb) that target CD3 and CD20 represent a new milestone in the treatment of patients with B-cell non-Hodgkin lymphoma. These drugs have demonstrated remarkable single-agent activity in patients with heavily pretreated disease, and 3 drugs have so far received regulatory approvals in various countries. However, BsAbs can potentially lead to severe toxicity associated with T-cell activation, particularly cytokine release syndrome (CRS). The anticipated widespread use of these off-the-shelf products poses challenges for implementation and highlights the need for guidance in anticipating, mitigating, and managing adverse events. In clinical trials, guidance for the evaluation and treatment of CRS and neurotoxicity associated with BsAb therapy has been modeled after algorithms originally created for chimeric antigen receptor (CAR) T-cell therapies and other immune effector therapies, yet notable differences in timing, quality, and severity exist between the toxicities of BsAbs and CAR T-cell therapies. We therefore convened an international panel of academic and community practice physicians, advanced practitioners, registered nurses, and pharmacists with experience using CD3×CD20 BsAbs in clinical trial and off-trial settings to provide comprehensive, consensus-based recommendations specific to the assessment and management of CD3×CD20 BsAb-related toxicities.<br /> (© 2024 American Society of Hematology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.)

Details

Language :
English
ISSN :
1528-0020
Volume :
143
Issue :
16
Database :
MEDLINE
Journal :
Blood
Publication Type :
Academic Journal
Accession number :
38252906
Full Text :
https://doi.org/10.1182/blood.2023022432