ArticleBiometrics2019
Using a surrogate marker for early testing of a treatment effect.
Article in Biometrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Flexible evaluation of surrogate markers with Bayesian model averaging.Statistics in medicine · 2024Trial
- Doubly robust evaluation of high-dimensional surrogate markers.Biostatistics (Oxford, England) · 2023Trial
- Efficient Testing Using Surrogate Information.Biometrical journal. Biometrische Zeitschrift · 2025Article
- Model-Free Approach to Evaluate a Censored Intermediate Outcome as a Surrogate for Overall Survival.Statistics in medicine · 2025Article
- Surrogate Marker Evaluation: A Tutorial Using R.Statistics in medicine · 2025Article
- Article
- Assessing heterogeneity in surrogacy using censored data.Statistics in medicine · 2024Article
- Article
- Higher Levels of Cerebrospinal Fluid and Plasma Neurofilament Light in Human Immunodeficiency Virus-Associated Distal Sensory Polyneuropathy.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Using a surrogate with heterogeneous utility to test for a treatment effect.Statistics in medicine · 2023Article
- Estimation of the proportion of treatment effect explained by a high-dimensional surrogate.Statistics in medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The development of methods to identify, validate, and use surrogate markers to test for a treatment effect has been an area of intense research interest given the potential for valid surrogate markers to reduce the required costs and follow-up times of future studies. Several quantities and procedures have been proposed to assess the utility of a surrogate marker. However, few methods have been proposed to address how one might use the surrogate marker information to test for a treatment effect at an earlier time point, especially in settings where the primary outcome and the surrogate marker are subject to censoring. In this paper, we propose a novel test statistic to test for a treatment effect using surrogate marker information measured prior to the end of the study in a time-to-event outcome setting. We propose a robust nonparametric estimation procedure and propose inference procedures. In addition, we evaluate the power for the design of a future study based on surrogate marker information. We illustrate the proposed procedure and relative power of the proposed test compared to a test performed at the end of the study using simulation studies and an application to data from the Diabetes Prevention Program.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.