AI-Enabled KidneyIntelX Monitors SGLT2 Inhibitor Response, Disease Progression in Diabetic Kidney Disease


Using banked samples from the CANVAS trial, investigators demonstrate the ability of KidneyIntelX to monitor therapeutic response to SGLT2 inhibitors and predict disease progression in patients with type 2 diabetes and chronic kidney disease.

Marina Basina, MD, Stanford

Marina Basina, MD

Research from the American Diabetes Association’s 81st Scientific Sessions (ADA 2021) suggests an AI-enabled diagnostic could allow clinicians to monitor patient response to SGLT2 inhibitor therapy and better predict risk of kidney disease progression in patients with type 2 diabetes.

Examined in a cohort of more than 1000 patients from a major clinical trial, the KidneyIntelX demonstrated the ability to more accurately assess patient response to SGLT2 inhibitor therapy and monitor improvements in kidney health over time.

“Until now, primary care physicians have not had an optimal way to assess risk for kidney disease progression in their type 2 diabetes patients,” said Marina Basina, MD, Clinical Professor of Endocrinology, Gerontology, and Metabolism at Stanford University School of Medicine, in a statement. “KidneyIntelX provides early risk stratification which allows us to optimize and target patients in early stages of kidney disease with new medications such as SGLT2 inhibitors, and moreover, these data support how KidneyIntelX can help monitor these patients and their response to treatment. It helps address an unmet need and gives the PCP a better call to action in the monitoring and effective pharmacy management of patients.”

Produced by Renalytix plc, KidneyIntelX was designed with the intent of improving assessments of therapeutic response to help guide optimal management of patients with diabetes and kidney disease. KidneyIntelX is a composite risk score incorporating biomarkers, including sTNFR-1, sTNFR-2, and KIM-1, and clinical data for predicting processing of diabetic kidney disease.

The ADA 2021 study was created to provide further information related to the abilities of KidneyIntelX for use in real-world settings. With this in mind, investigators designed the study as an assessment of samples from patients within the CANVAS trial who had plasma samples at baseline and 1 year with an eGFR of less than 60 ml/min/1.73m2 or UACR of 30 mg/g or greater.

Using this data, investigators planned to assess the effect of canagliflozin on KidneyIntelX scores and how changes from baseline to year 1 were associated with progression of chronic kidney disease in these patients. For the purpose of analysis, kidney disease progression was defined as a composite of eGFR decline 5 ml/min/year or more, a 40% or greater sustained decline in eGFR, or kidney failure.

A total of 1016 participants from CANVAS were identified for inclusion in the final sample—this cohort had a median age of 64 years and 30% were female. At baseline, this group had a median eGFR of 66 ml/min and a median UACR of 55 mg/g. After the first year, 6.7% (n=68) of participants experienced a composite outcome event during a follow-up period lasting a median of 4.9 years.

Upon analysis, canagliflozin reduced the KidneyIntelX risk by 5.1% (95% CI, -6.6 to -3.6) at year 1 compared to an increase of 5.8% (95% CI, 3.4 to 8.1) in the placebo arm (P <.001). Further analysis indicated each percent reduction in KidneyIntelX score at 1 year was associated with a 2% (OR, 0.98; 95% CI, 0.97 to 0.99; P <.001) reduction in risk of the study’s composite outcome after adjustment for baseline score and treatment arm. Investigators pointed out the association observed between change in score and outcome were consistent in both arms of CANVAS (P for interaction=.63).

This study, “Longitudinal Changes in KidneyIntelX and Association with Progressive Decline in Kidney Function in the CANVAS Trial,” was presented at ADA 2021.

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