Assessing the Surrogate Value of a Biomarker: An Approach Combining Matching and Sensitivity Analysis

• Activity Number: 6
• Type: Invited
• Date/Time: Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Julian Wolfson*+
• Companies: University of Minnesota
• Keywords: surrogate endpoint ; Prentice criteria ; sensitivity analysis ; infectious diseases ; matching

Abstract

Statisticians have developed a number of frameworks which can be used to assess the surrogate value of a biomarker, i.e. establish whether it can be used in place of a clinical endpoint for quantifying the effect of a treatment. The most commonly applied of these frameworks is due to Prentice (1989), who proposed a set of criteria which a surrogate marker should satisfy. However, verifying these criteria using observed data can be challenging due to the presence of unmeasured simultaneous predictors (i.e. confounders) which influence both the potential surrogate and the outcome. In this work, we adapt a technique proposed by Rosenbaum (2002) for observational studies, in which observations are matched and the odds of treatment within each matched pair is bounded. This yields a straightforward and interpretable sensitivity analysis which can be performed particularly efficiently for certain types of test statistics. We discuss the details of this technique, and illustrate with an example drawn from the infectious disease literature.