Bayesian Estimation of Agreement of Biomarkers in Early Drug Development

Abstract

The need for assessment of agreement of biomarkers is ubiquitous in drug development. In this study, we focus on scaled agreement indices including within-subject coefficient of variation, intraclass correlation coefficient, and concordance correlation coefficient. We illustrate, by both simulated and real life datasets, the usage and added value of Bayesian estimation of agreement of biomarkers in early drug development. We discuss the solutions to small sample size, outliers, and nonnormally distributed data problems. Furthermore, we present how to address, coherently within the Bayesian framework, other practically relevant issues such as accommodation of covariates and model diagnostics.

Keywords:

• Agreement
• Bayesian
• Concordance correlation coefficient
• Intraclass correlation coefficient
• Within-subject coefficient of variation