A meta-analysis of GFR slope as a surrogate endpoint for kidney failure
the CKD-EPI Clinical Trials Consortium
(2023) Nature Medicine, volume 29, issue 7, pp. 1867 - 1876
(Article)
Abstract
Glomerular filtration rate (GFR) decline is causally associated with kidney failure and is a candidate surrogate endpoint for clinical trials of chronic kidney disease (CKD) progression. Analyses across a diverse spectrum of interventions and populations is required for acceptance of GFR decline as an endpoint. In an analysis of individual
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participant data, for each of 66 studies (total of 186,312 participants), we estimated treatment effects on the total GFR slope, computed from baseline to 3 years, and chronic slope, starting at 3 months after randomization, and on the clinical endpoint (doubling of serum creatinine, GFR < 15 ml min−1 per 1.73 m2 or kidney failure with replacement therapy). We used a Bayesian mixed-effects meta-regression model to relate treatment effects on GFR slope with those on the clinical endpoint across all studies and by disease groups (diabetes, glomerular diseases, CKD or cardiovascular diseases). Treatment effects on the clinical endpoint were strongly associated with treatment effects on total slope (median coefficient of determination (R2) = 0.97 (95% Bayesian credible interval (BCI) 0.82–1.00)) and moderately associated with those on chronic slope (R2 = 0.55 (95% BCI 0.25–0.77)). There was no evidence of heterogeneity across disease. Our results support the use of total slope as a primary endpoint for clinical trials of CKD progression.
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Keywords: General Biochemistry,Genetics and Molecular Biology
ISSN: 1078-8956
Publisher: Nature Publishing Group
Note: Funding Information: We thank the National Kidney Foundation (NKF) and its sponsors for funding this research. The NKF received consortium support from the following companies: AstraZeneca, Bayer, Boehringer Ingelheim, Cerium Pharma, Chinook, CSL Behring, Janssen, Novartis, NovoNordisk, ProKidney and Travere. This work also received support from the Utah Study Design and Biostatistics Center, with funding in part from the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR002538. The support and resources from the Center for High Performance Computing at the University of Utah are also gratefully acknowledged. We thank all investigators, study teams and participants of the studies included in the meta-analysis (). This analysis includes SPRINT and TOPCAT research materials obtained from the National Heart, Lung and Blood Institute (NHLBI) Biologic Specimen and Data Repository Information Coordinating Center and does not necessarily reflect the opinions or views of SPRINT or TOPCAT or the NHLBI. The FSGS/FONT trial, HALT-PKD Study A and HALT-PKD Study B were conducted by the investigators of the respective studies and were supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The data from these studies reported here were supplied by the NIDDK Central Repository. This paper does not necessarily reflect the opinions or views of these studies, the NIDDK Central Repository or the NIDDK. We are grateful for data from AstraZeneca, Bayer AG, Boehringer Ingelheim, GlaxoSmithKline (made available through Vivli, Inc.), Novartis (made available through a clinical study data request (CSDR)), Novo Nordisk A/S and Takeda (made available through Vivli, Inc.). Vivli and CSDR have not contributed to or approved, and are not in any way responsible for, the contents of this publication. Publisher Copyright: © 2023, The Author(s), under exclusive licence to Springer Nature America, Inc.
(Peer reviewed)