Issues Related to Statistical Validation of Minimal Residual Disease as a Surrogate Endpoint for Clinical Trials and Drug Approvals in AML

• Activity Number: 95 - Statistical Validation of Surrogate Endpoints
• Type: Invited
• Date/Time: Monday, July 31, 2017 : 8:30 AM to 10:20 AM
• Sponsor: Pharmaceutical Research and Manufacturers of America
• Author(s): Liang Xiu* and Rianka Bhattacharya and Jianan Hui and Hong Tian
• Companies: Janssen Research and Development and Janssen Research and Development and University of California, Riverside and Janssen Research and Development
• Keywords: Meta-analytical approach ; weighted least square regression ; Surrogate Endpoint ; MRD ; AML

Abstract

Various methodologies have been proposed for statistical validation of surrogate endpoint; the evaluation of performance of those methods is needed for practitioners to apply these methods effectively. Acute myeloid leukemia (AML) is a heterogeneous disease associated with poor clinical outcomes. Now sensitive molecular biology tests become available to measure minimal levels of cancer cells in bone marrow samples (i.e., minimal residual disease), which is a potential surrogate endpoint for OS. For establishing surrogacy, it is important to quantify 2 types of correlations: individual-level and trial-level correlation. Establishing trial-level correlation is usually more challenging. A simple and initiative approach is weighted least square regression using aggregated data; alternatively, a sophisticated statistical modeling approach proposed by Burzykowski(2004) can be applied using subject level data. In this work, we evaluate these two approaches using simulated data under scenarios which are practical in AML settings. . In addition, we also recommend statistical criteria for surrogacy based on simulation results.