Statistical Validation of Surrogate Endpoints in Chronic Kidney Disease

• Activity Number: 49
• Type: Invited
• Date/Time: Sunday, August 3, 2014 : 4:00 PM to 5:50 PM
• Sponsor: ENAR
• Author(s): Tom Greene*+
• Companies: University of Utah
• Keywords: Surrogate endpoint ; chronic kidney disease ; Bayesian analysis ; multi-level model

Abstract

The definitive clinical outcome in clinical trials of chronic kidney disease (CKD) is the occurrence of end stage kidney disease (ESKD), at which point the patient requires dialysis or kidney transplantation to survive. However, because CKD often takes more than 10 years to progress to ESKD, there is a great interest in validation of surrogate endpoints, including change in proteinuria or estimated glomerular filtration rate (eGFR), which may be used to characterize the rate of progression of CKD over a shorter time frame. I will examine the application of Bayesian multi-level models to evaluate the validity of surrogate endpoints based on joint analyses of previous CKD clinical trials based on alternative frameworks of individual-level association, the Prentice-Friedman criteria, as well as trial-level analyses which assess the association of treatment effects on the putative surrogate endpoint with treatment effects on the clinical outcome. In the case of eGFR I will also examine the use of statistical simulation to characterize Type 1 error and statistical power of the surrogate endpoint relative to the treatment effect on the clinical outcome of ESKD.