Evidence map›Paper›PMID 29164641›Full record

ArticleStatistics in medicine2018

Five criteria for using a surrogate endpoint to predict treatment effect based on data from multiple previous trials.

Stuart G Baker

Erratum issuedAbstract read
In one paragraph

Article in Statistics in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Albuminuria Changes as a surrogate endpoint inmedRxiv : the preprint server for health sciences · 2026
    Article
  5. Impact of LEAP-012 and EMERALD-1 in the management of HCC.JHEP reports : innovation in hepatology · 2026
    Review
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  10. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Stuart G BakerDivision of Cancer Prevention, National Cancer Institute, 9609 Medical Center Dr, Room 5E606, MSC 9789, Bethesda, MD, 20892-9789, USA.ORCID 0000-0001-6759-2838

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

A surrogate endpoint in a randomized clinical trial is an endpoint that occurs after randomization and before the true, clinically meaningful, endpoint that yields conclusions about the effect of treatment on true endpoint. A surrogate endpoint can accelerate the evaluation of new treatments but at the risk of misleading conclusions. Therefore, criteria are needed for deciding whether to use a surrogate endpoint in a new trial. For the meta-analytic setting of multiple previous trials, each with the same pair of surrogate and true endpoints, this article formulates 5 criteria for using a surrogate endpoint in a new trial to predict the effect of treatment on the true endpoint in the new trial. The first 2 criteria, which are easily computed from a zero-intercept linear random effects model, involve statistical considerations: an acceptable sample size multiplier and an acceptable prediction separation score. The remaining 3 criteria involve clinical and biological considerations: similarity of biological mechanisms of treatments between the new trial and previous trials, similarity of secondary treatments following the surrogate endpoint between the new trial and previous trials, and a negligible risk of harmful side effects arising after the observation of the surrogate endpoint in the new trial. These 5 criteria constitute an appropriately high bar for using a surrogate endpoint to make a definitive treatment recommendation.

Indexed as

BiomarkersBiostatisticsComputer SimulationHumansLikelihood FunctionsLinear ModelsMeta-Analysis as TopicRandomized Controlled Trials as TopicSample SizeTreatment OutcomeBiomarkersmeta-analysisPrentice criterionrandomized trialsurrogate endpoint

Identifiers

PMID29164641
PMCPMC5771803

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.