ArticleStatistics in medicine2025
A General Framework to Assess Complex Heterogeneity in the Strength of a Surrogate Marker.
Article in Statistics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Assessing surrogate heterogeneity in real world data using meta-learners.Journal of causal inference · 2026Article
- Efficient Testing Using Surrogate Information.Biometrical journal. Biometrische Zeitschrift · 2025Article
- RISE: Two-Stage Rank-Based Identification of High-Dimensional Surrogate Markers Applied to Vaccinology.Statistics in medicine · 2025Article
- Surrogate Marker Evaluation: A Tutorial Using R.Statistics in medicine · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
A surrogate marker is a biological measurement in a clinical trial that aims to replace the primary outcome in evaluating the treatment effect, and can be measured earlier, with less cost, or with less patient burden. In theory, once a surrogate is validated, future studies can evaluate treatment efficacy using only the surrogate. While there are many methods to evaluate a surrogate, these methods rarely account for heterogeneity in surrogacy, that is, when a surrogate is valid for only certain people. We propose a general framework for the assessment of complex heterogeneity in the strength of a surrogate marker, as well as corresponding parametric and semiparametric estimation procedures. Our framework defines the proportion of the treatment effect on the primary outcome that is explained by the treatment effect on the surrogate, as a function of multiple baseline covariates,
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Registered trials
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