Derivation and independent validation of kidneyintelX.dkd: A prognostic test for the assessment of diabetic kidney disease progression.

Autor: Nadkarni GN; Barbara T Murphy Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.; Division of Digital and Data Driven Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.; The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA., Stapleton S; Renalytix AI, PLC, New York, New York, USA., Takale D; Persistent Systems, Pune, India., Edwards K; Renalytix AI, PLC, New York, New York, USA., Moran K; Renalytix AI, PLC, New York, New York, USA., Mosoyan G; Barbara T Murphy Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, USA., Hansen MK; Janssen Research & Development, LLC, Spring House, Pennsylvania, USA., Donovan MJ; Renalytix AI, PLC, New York, New York, USA., Heerspink HJL; Department of Clinical Pharmacy and Pharmacology, University of Groningen, Groningen, The Netherlands., Fleming F; Renalytix AI, PLC, New York, New York, USA., Coca SG; Barbara T Murphy Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Jazyk: angličtina
Zdroj: Diabetes, obesity & metabolism [Diabetes Obes Metab] 2023 Dec; Vol. 25 (12), pp. 3779-3787. Date of Electronic Publication: 2023 Sep 18.
DOI: 10.1111/dom.15273
Abstrakt: Aims: To develop and validate an updated version of KidneyIntelX (kidneyintelX.dkd) to stratify patients for risk of progression of diabetic kidney disease (DKD) stages 1 to 3, to simplify the test for clinical adoption and support an application to the US Food and Drug Administration regulatory pathway.
Methods: We used plasma biomarkers and clinical data from the Penn Medicine Biobank (PMBB) for training, and independent cohorts (BioMe and CANVAS) for validation. The primary outcome was progressive decline in kidney function (PDKF), defined by a ≥40% sustained decline in estimated glomerular filtration rate or end-stage kidney disease within 5 years of follow-up.
Results: In 573 PMBB participants with DKD, 15.4% experienced PDKF over a median of 3.7 years. We trained a random forest model using biomarkers and clinical variables. Among 657 BioMe participants and 1197 CANVAS participants, 11.7% and 7.5%, respectively, experienced PDKF. Based on training cut-offs, 57%, 35% and 8% of BioMe participants, and 56%, 38% and 6% of CANVAS participants were classified as having low-, moderate- and high-risk levels, respectively. The cumulative incidence at these risk levels was 5.9%, 21.2% and 66.9% in BioMe and 6.7%, 13.1% and 59.6% in CANVAS. After clinical risk factor adjustment, the adjusted hazard ratios were 7.7 (95% confidence interval [CI] 3.0-19.6) and 3.7 (95% CI 2.0-6.8) in BioMe, and 5.4 (95% CI 2.5-11.9) and 2.3 (95% CI 1.4-3.9) in CANVAS, for high- versus low-risk and moderate- versus low-risk levels, respectively.
Conclusions: Using two independent cohorts and a clinical trial population, we validated an updated KidneyIntelX test (named kidneyintelX.dkd), which significantly enhanced risk stratification in patients with DKD for PDKF, independently from known risk factors for progression.
(© 2023 John Wiley & Sons Ltd.)
Databáze: MEDLINE
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