Precision medicine in type 2 diabetes: targeting SGLT2 inhibitor treatment for kidney protection

作者：Thijs T Jansz, Katherine Young, Rhian Hopkins, Andrew McGovern, Beverley M. Shields, Andrew T. Hattersley, Angus G. Jones, Ewan R. Pearson, Coralie Bingham, Richard A. Oram, John Dennis · 发表于：Diabetologia · 年份：2025 · DOI：10.1007/s00125-025-06577-2 · 被引用次数：4 · 研究领域：Diabetes Treatment and Management、Chronic Kidney Disease and Diabetes、Renal Transplantation Outcomes and Treatments

AIMS/HYPOTHESIS: Current guidelines recommend use of sodium-glucose cotransporter-2 inhibitors (SGLT2 inhibitors) for kidney protection in people with type 2 diabetes and early-stage chronic kidney disease (CKD) based on a urinary albumin/creatinine ratio (uACR) of ≥3 mg/mmol. However, individuals with a normal uACR or low-level albuminuria were not represented in kidney outcome trials, leaving uncertainty about absolute treatment benefit in this group. To address this gap and support treatment decisions in clinical practice, we developed and validated a model to predict individual-level kidney protection benefit through the use of SGLT2 inhibitors. METHODS: and uACR <30 mg/mmol, without heart failure or atherosclerotic vascular disease, who were starting treatment with either SGLT2 inhibitors or the comparator drugs dipeptidyl peptidase-4 (DPP4) inhibitors/sulfonylureas. First, we confirmed the real-world applicability of the relative treatment effect from a previous SGLT2 inhibitor trial meta-analysis, using overlap-weighted Cox proportional hazards models. Second, we assessed calibration of the CKD-PC risk score for kidney disease progression (≥50% eGFR decline, end-stage kidney disease or kidney-related death). Third, we integrated the relative treatment effect with the risk score to predict 3 year individual-level absolute risk reductions for SGLT2 inhibitors, and validated the accuracy of predictions vs overlap-weighted estimates based on observed data. Finally, we comp...