Abstract

De novo donor-specific antibody (dnDSA) is associated with a higher risk of kidney graft failure. However, it is unknown whether preemptive treatment of subclinical dnDSA is beneficial. Here, we assessed the efficacy of high-dose intravenous immunoglobulin (IVIG) and rituximab combination therapy for subclinical dnDSA. An open-label randomized controlled clinical trial was conducted at two Korean institutions. Adult (aged ≥ 19 years) kidney transplant patients with subclinical class II dnDSA (mean fluorescence intensity ≥ 1000) were enrolled. Eligible participants were randomly assigned to receive rituximab or rituximab with IVIG at a 1:1 ratio. The primary endpoint was the change in dnDSA titer at 3 and 12 months after treatment. A total of 46 patients (24 for rituximab and 22 for rituximab with IVIG) were included in the analysis. The mean baseline estimated glomerular filtration rate was 66.7 ± 16.3 mL/min/1.73 m2. The titer decline of immune-dominant dnDSA at 12 months in both the preemptive groups was significant. However, there was no difference between the two groups at 12 months. Either kidney allograft function or proteinuria did not differ between the two groups. No antibody-mediated rejection occurred in either group. Preemptive treatment with high-dose IVIG combined with rituximab did not show a better dnDSA reduction compared with rituximab alone.

Trial registration: IVIG/Rituximab versus Rituximab in Kidney Transplant With de Novo Donor-specific Antibodies (ClinicalTrials.gov Identifier: NCT04033276, first trial registration (26/07/2019).

Details

Title
Comparison of high-dose IVIG and rituximab versus rituximab as a preemptive therapy for de novo donor-specific antibodies in kidney transplant patients
Author
Kim, Hyung Woo 1 ; Lee, Juhan 2 ; Heo, Seok-Jae 3 ; Kim, Beom Seok 1 ; Huh, Kyu Ha 2   VIAFID ORCID Logo  ; Yang, Jaeseok 1   VIAFID ORCID Logo 

 Yonsei University College of Medicine, Department of Internal Medicine, Seoul, Korea (GRID:grid.15444.30) (ISNI:0000 0004 0470 5454) 
 Yonsei University College of Medicine, Department of Surgery, Seoul, Korea (GRID:grid.15444.30) (ISNI:0000 0004 0470 5454) 
 Yonsei University College of Medicine, Division of Biostatistics, Department of Biomedical Systems Informatics, Seoul, Korea (GRID:grid.15444.30) (ISNI:0000 0004 0470 5454) 
Pages
7682
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2812332464
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.