Using surrogate failure time data to increase cost effectiveness in clinical trials

Abstract

SUMMARY In clinical trials with failure time, outcomes, the cost of follow-up for the endpoint of primary interest is sometimes expensive. In many of these settings, one or more secondary or surrogate failure time outcomes are also available which either occur much earlier or are much less expensive to follow than the primary outcome. This paper presents a method for using these secondary outcomes to increase the power of detecting a treatment effect on the primary outcome only, without introducing bias. The proposed method requires that patients be randomized to either extended or limited follow-up. A test statistic is constructed by forming a minimum variance linear combination of a linear rank statistic based on the primary outcome and a mean zero weighted sum of linear rank statistics based on secondary outcomes from both follow-up arms. Large-sample distribution theory for this statistic is developed while moderate sample behaviour is explored through a simulation study.