Evidence map›Paper›PMID 32506496›Full record

ArticleBiometrics2021

Evaluation of longitudinal surrogate markers.

Denis Agniel, Layla Parast

Abstract read
In one paragraph

Article in Biometrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Robust evaluation of longitudinal surrogate markers with censored data.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2025
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Denis AgnielRAND Corporation.ORCID 0000-0003-1483-2724
Layla ParastRAND Corporation.ORCID 0000-0002-7288-1009

Funding

Increasing Activity in Peripheral Arterial DiseaseR01HL088589 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI MCDERMOTT, MARY MCGRAE · 2008 to 2011
$2.9M
Robust Statistical Methods to Identify and Use Surrogate Markers in DiabetesR01DK118354 · NIDDK · UNIVERSITY OF TEXAS AT AUSTIN · PI PARAST, LAYLA · 2018 to 2025
$2.0M
The Role of Interleukin 23 In Colitis Associated CancerR00DK088589 · NIDDK · RESEARCH INST OF FOX CHASE CAN CTR · PI GRIVENNIKOV, SERGEI I · 2013 to 2015
$728k
The Role of Interleukin 23 In Colitis Associated CancerK99DK088589 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GRIVENNIKOV, SERGEI I · 2011 to 2012
$178k
NHLBI NIH HHS R01 HL088589NIDDK NIH HHS R01 DK118354
6 · The paper itself

Abstract

The use of surrogate markers to examine the effectiveness of a treatment has the potential to decrease study length and identify effective treatments more quickly. Most available methods to investigate the usefulness of a surrogate marker involve restrictive parametric assumptions and tend to focus on settings where the surrogate is measured at a single point in time. However, in many clinical settings, the potential surrogate marker is often measured repeatedly over time, and thus, the surrogate marker information is a trajectory of measurements. In addition, it is often difficult in practice to correctly specify the relationship between a treatment, primary outcome, and surrogate marker trajectory. In this paper, we propose a model-free definition for the proportion of the treatment effect on the primary outcome that is explained by the treatment effect on the longitudinal surrogate markers. We propose three novel flexible methods to estimate this proportion, develop the asymptotic properties of our estimators, and investigate the robustness of the estimators under multiple settings via a simulation study. We apply our proposed procedures to an AIDS clinical trial dataset to examine a trajectory of CD4 counts as a potential surrogate.

Indexed as

BiomarkersComputer SimulationTreatment OutcomeBiomarkersfunctional datakernel smoothinglongitudinal datanonparametric analysissurrogate markers

Identifiers

PMID32506496
PMCPMC8015060

What OpenQuestion holds

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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.