Individual-level surrogacy of MRI lesions for disease severity in RRMS: Methods to quantify predictive power and their application to longitudinal data from recent trials.

ABSTRACT:

Background

Individual-level surrogacy (ILS) assesses how well a surrogate endpoint predicts treatment effect at the individual level. The paper discusses mutual information (MI) and the likelihood reduction factor (LRF) as ways to quantify ILS. It also reassesses ILS statements for people with relapsing-remitting multiple sclerosis (RRMS) by using T2 MRI lesions (T2L) as surrogates for disability and disease activity. ILS is often reported using inadequate concepts, e.g. subgroup analysis, correlation, odds ratios, sensitivity/specificity, or metrics based on Prentice's criteria.

Methods

LRF assesses ILS quality by determining prediction quality through shared information (MI) between surrogate(s) and clinical endpoint(s). A simulation study validates LRF as a measure of ILS

SUBMITTER: Buchka S 

PROVIDER: S-EPMC12742783 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature