Background and objectives: Clinical trials in nephrology are enriched for patients with micro- or macroalbuminuria to enroll patients at risk of kidney failure. However, patients with normoalbuminuria can also progress to kidney failure. Tumor Necrosis Factor Receptor (TNFR)-1, TNFR-2 and Kidney Injury Marker (KIM)-1 are known to be associated with kidney disease progression in patients with micro- or macroalbuminuria. We assessed the value of TNFR-1, TNFR-2 and KIM-1 as prognostic biomarkers for CKD progression in patients with type 2 diabetes and normoalbuminuria.
Design, setting, participants and measurements: TNFR-1, TNFR-2, and KIM-1 were measured using immunoassays in plasma samples from patients with type 2 diabetes at high cardiovascular risk participating in the CANVAS trial. We used multivariable adjusted Cox proportional hazards analyses to estimate hazard ratios per doubling of each biomarker for the kidney outcome and stratified the population by the 4th quartile of each biomarker distribution and assessed the number of events and event rates.
Results: In patients with normoalbuminuria (N=2,553), 51 kidney outcomes were recorded during a median follow-up of 6.1 (IQR 5.8 to 6.4) years (event rate 3.5 [95%CI 2.6-4.6] per 1,000-patient-years). Each doubling of baseline TNFR-1 (HR 4.16; 95%CI 1.80-9.61) and TNFR-2 (HR 2.35; 95%CI 1.51-3.63) was associated with a higher risk for the kidney outcome. Baseline KIM-1, UACR and eGFR were not associated with kidney outcomes. The event rates in the highest quartile of the TNFR-1 (≥2,992 ng/ml) or TNFR-2 (≥11,394 ng/ml) were 5.6 and 7.0 events per 1000-patient-years compared to 2.4 and 2.8 in the lower three quartiles.
Conclusion: TNFR-1 and TNFR-2 are associated with kidney outcomes in patients with type 2 diabetes and normoalbuminuria.
|Number of pages||9|
|Journal||Clinical Journal of the American Society of Nephrology|
|Early online date||7-Dec-2021|
|Publication status||Published - 1-Feb-2022|
- clinical trial design
- hepatitis a virus cellular receptor 1
- kidney outcomes
- risk prediction