Reading the tree leaves – how to enrich clinical trials of diabetic kidney disease - Looker, Helen C. (Kidney Int, 2017)
Diabetic kidney disease typically develops over decades, but only outcomes associated with late disease stages are currently approved for clinical trials. Participants at greatest risk for these outcomes are currently selected using various combinations of traditional risk factors, including blood pressure, urine albumin excretion, and estimated glomerular filtration rate. Nevertheless, most clinical trial participants still do not reach the endpoints of interest, requiring very large trials or prolonged follow-up to achieve adequate statistical power. In this issue, Yamanouchi et al. used a Classification and Regression Trees analysis to further enrich enrollment criterion for patients at high risk for approved clinical trial outcomes. Selection criteria included novel biomarkers of diabetic kidney disease, which greatly enhanced the prognostic value of criterion based solely on traditional risk factors. These findings suggest a greater role for newly identified biomarkers of diabetic kidney disease in the selection of participants for clinical trials.