Abstract

There is tremendous interest in evaluating surrogate markers given their potential to decrease study time, costs, and patient burden.The purpose of this statistical workshop article is to describe and illustrate how to evaluate a surrogate marker of interest using the proportion of treatment effect (PTE) explained as a measure of the quality of the surrogate marker for (1) a setting with a general fully observed primary outcome (eg, biopsy score) and (2) a setting with a time-to-event primary outcome which may be censored due to study termination or early drop out (eg, time to diabetes).The methods are motivated by 2 randomized trials, one among children with nonalcoholic fatty liver disease where the primary outcome was a change in biopsy score (general outcome) and another study among adults at high risk for Type 2 diabetes where the primary outcome was time to diabetes (time-to-event outcome). The methods are illustrated using the Rsurrogate package with a detailed R code provided.In the biopsy score outcome setting, the estimated PTE of the examined surrogate marker was 0.182 (95% confidence interval [CI]: 0.121, 0.240), that is, the surrogate explained only 18.2% of the treatment effect on the biopsy score. In the diabetes setting, the estimated PTE of the surrogate marker was 0.596 (95% CI: 0.404, 0.760), that is, the surrogate explained 59.6% of the treatment effect on diabetes incidence.This statistical workshop provides tools that will support future researchers in the evaluation of surrogate markers.

View details for DOI 10.1097/MLR.0000000000001956

View details for PubMedID 38079232