Evaluating a surrogate endpoint at three levels, with application to vaccine development.

Publication Type:

Journal Article

Source:

Statistics in medicine, Volume 27, Issue 23, p.4758-78 (2008)

Keywords:

2008, AIDS Vaccines, Algorithms, Biological Markers, Center-Authored Paper, Clinical Trials as Topic, Humans, Immunotherapy, Active, Influenza Vaccines, Meta-Analysis as Topic, Public Health Sciences Division, Research Design, Treatment Outcome, Vaccine and Infectious Disease Institute

Abstract:

Identification of an immune response to vaccination that reliably predicts protection from clinically significant infection, i.e. an immunological surrogate endpoint, is a primary goal of vaccine research. Using this problem of evaluating an immunological surrogate as an illustration, we describe a hierarchy of three criteria for a valid surrogate endpoint and statistical analysis frameworks for evaluating them. Based on a placebo-controlled vaccine efficacy trial, the first level entails assessing the correlation of an immune response with a study endpoint in the study groups, and the second level entails evaluating an immune response as a surrogate for the study endpoint that can be used for predicting vaccine efficacy for a setting similar to that of the vaccine trial. We show that baseline covariates, innovative study design, and a potential outcomes formulation can be helpful for this assessment. The third level entails validation of a surrogate endpoint via meta-analysis, where the goal is to evaluate how well the immune response can be used to predict vaccine efficacy for new settings (building bridges). A simulated vaccine trial and two example vaccine trials are presented, one supporting that certain anti-influenza antibody levels are an excellent surrogate for influenza illness and another supporting that certain anti-HIV antibody levels are not useful as a surrogate for HIV infection.