Univariate versus multivariate surrogates in the single-trial setting

<p>In spite of medical and methodological advances, the identification of good surrogate endpoints has remained a challenging endeavour. This may, at least partially, be attributable to the fact that most researchers have only focused on univariate surrogates endpoints. In the present work, we argue in favour of using multivariate surrogates and introduce two new complementary metrics to assess their validity. The first one, the so-called Individual Causal Association, quantifies the association between the individual causal treatment effects on the multivariate surrogate and true endpoints, while the second one quantifies the treatment-corrected association between the multivariate surrogate and the true endpoint outcomes. The newly proposed methodology is implemented in the R package <i>Surrogate</i> and a Web Appendix, detailing how the analysis can be conducted in practice, is provided.</p>