A Surrogate Measure for Time-Varying Biomarkers in Randomized Clinical Trials

Clinical trials with rare or distant outcomes are usually designed to be large in size and long term. The resource-demand and time-consuming characteristics limit the feasibility and efficiency of the studies. There are motivations to replace rare or distal clinical endpoints by reliable surrogate m...

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Bibliographic Details
Published in:Mathematics (Basel) 2022-02, Vol.10 (4), p.584
Main Authors: Zhuang, Rui, Xia, Fan, Wang, Yixin, Chen, Ying-Qing
Format: Article
Language:English
Subjects:
Biomarkers
Clinical trials
Disease prevention
HIV
Human immunodeficiency virus
Hypotheses
Infections
Mathematics
Monte Carlo simulation
surrogate measure
survival settings
Time measurement
time-varying internal markers
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Summary:Clinical trials with rare or distant outcomes are usually designed to be large in size and long term. The resource-demand and time-consuming characteristics limit the feasibility and efficiency of the studies. There are motivations to replace rare or distal clinical endpoints by reliable surrogate markers, which could be earlier and easier to collect. However, statistical challenges still exist to evaluate and rank potential surrogate markers. In this paper, we define a generalized proportion of treatment effect for survival settings. The measure's definition and estimation do not rely on any model assumption. It is equipped with a consistent and asymptotically normal non-parametric estimator. Under proper conditions, the measure reflects the proportion of average treatment effect mediated by the surrogate marker among the group that would survive to mark the measurement time under both intervention and control arms.
ISSN:2227-7390
2227-7390
DOI:10.3390/math10040584