4.7 Article

Improved clinical trial enrollment criterion to identify patients with diabetes at risk of end-stage renal disease

期刊

KIDNEY INTERNATIONAL
卷 92, 期 1, 页码 258-266

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.kint.2017.02.010

关键词

acute kidney injury; chronic kidney disease; diabetes

资金

  1. JDRF [3-SRA-2015-106-Q-R, 5-CDA-2015-89-A-B]
  2. National Institutes of Health [DK-041526, DK-072381]
  3. Novo Nordisk Foundation (PROTON) [NNF14OC0013659]
  4. NIH DRC [P30 DK03683]
  5. Lilly Inc.
  6. Pfizer Inc.
  7. Novo Nordisk Fonden [NNF14OC0013659] Funding Source: researchfish

向作者/读者索取更多资源

Design of Phase III trials for diabetic nephropathy currently requires patients at a high risk of progression defined as within three years of a hard end point (end-stage renal disease, 40% loss of estimated glomerular filtration rate, or death). To improve the design of these trials, we used natural history data from the Joslin Kidney Studies of chronic kidney disease in patients with diabetes to develop an improved criterion to identify such patients. This included a training cohort of 279 patients with type 1 diabetes and 134 end points within three years, and a validation cohort of 221 patients with type 2 diabetes and 88 end points. Previous trials selected patients using clinical criteria for baseline urinary albumin-to-creatinine ratio and estimated glomerular filtration rate. Application of these criteria to our cohort data yielded sensitivities ( detection of patients at risk) of 70-80% and prognostic values of only 52-63%. We applied classification and regression trees analysis to select from among all clinical characteristics and markers the optimal prognostic criterion that divided patients with type 1 diabetes according to risk. The optimal criterion was a serum tumor necrosis factor receptor 1 level over 4.3 ng/ml alone or 2.9-4.3 ng/ml with an albumin-to-creatinine ratio over 1900 mg/g. Remarkably, this criterion produced similar results in both type 1 and type 2 diabetic patients. Overall, sensitivity and prognostic value were high (72% and 81%, respectively). Thus, application of this criterion to enrollment in future clinical trials could reduce the sample size required to achieve adequate statistical power for detection of treatment benefits.

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