1. Estimating the efficacy of felzartamab to treat antibody-mediated rejection using the iBox prognostication system.
- Author
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Lombardi Y, Raynaud M, Schatzl M, Mayer KA, Diebold M, Patel UD, Schrezenmeier E, Akifova A, Budde K, Loupy A, and Böhmig GA
- Abstract
Competing Interests: Declaration of competing interest The authors of this manuscript have conflicts of interest to disclose as described by the American Journal of Transplantation. Y. Lombardi received a grant from Assistance Publique-Hôpitaux de Paris and Sorbonne Center for Artificial Intelligence (“Poste d’accueil 2023-2025”). K. Budde has received honoraria, research grants, and/or travel support from Aicuris, Alexion, Astellas, AstraZeneca, Biohope, Carealytics, CareDx, Chiesi, CSL Behring, DTB GmbH, Eledon, Hi-Bio, MSD, Natera, Neovii, Oncocyte, Oska, Otsuka, Paladin, Pfizer, Pirche, Sanofi, Smart Care Solutions, Stada, Takeda, Veloxis, Vifor, and Xenothera. A. Loupy is a minor shareholder of Predict4Health, a software company. G.A. Böhmig is a member of the steering committee for a planned phase 3 trial evaluating felzartamab in antibody-mediated rejection (Human Immunology Biosciences) and has received honoraria, research grants, and/or travel support from Argenx, AstraZeneca, OneLambda, and Takeda.
- Published
- 2024
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