Evidence map›Paper›PMID 39030751›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2024

Statistical considerations when estimating time-saving treatment effects in Alzheimer's disease clinical trials.

Guoqiao Wang, Gary Cutter, Neil P Oxtoby, Guogen Shan, Whedy Wang, Brian Mangal, Yijie Liao, Jorge J Llibre-Guerra, Yan Li, Chengjie Xiong and 4 more

Abstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Letter to the Editor.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  6. Article
  7. Article
  8. Statistical considerations when estimating time-saving treatment effects in Alzheimer's disease clinical trials.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

14 authors.

Guoqiao WangDepartment of Neurology, Division of Biostatistics, School of Medicine, Washington University, St. Louis, Missouri, USA.ORCID 0000-0002-6808-8737
Gary CutterDepartment of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Neil P OxtobyDepartment of Computer Science, University College London, London, UK.
Guogen ShanDepartment of Biostatistics, University of Florida, Gainesville, Florida, USA.
Whedy WangTenaya Therapeutics, South San Francisco, California, USA.
Brian MangalSolara Consulting Corp., North Vancouver, British Columbia, Canada.
Yijie LiaoNeogene Therapeutics, Inc., Santa Monica, California, USA.
Jorge J Llibre-GuerraDepartment of Neurology, Division of Biostatistics, School of Medicine, Washington University, St. Louis, Missouri, USA.
Yan LiDepartment of Neurology, Division of Biostatistics, School of Medicine, Washington University, St. Louis, Missouri, USA.
Chengjie XiongDivision of Biostatistics, Washington University, School of Medicine, St. Louis, Missouri, USA.
Eric McDadeDepartment of Neurology, Division of Biostatistics, School of Medicine, Washington University, St. Louis, Missouri, USA.
Paul DelmarF. Hoffmann-La Roche Ltd., Basel, Switzerland.
Randall J BatemanDepartment of Neurology, Division of Biostatistics, School of Medicine, Washington University, St. Louis, Missouri, USA.
Lon SchneiderDepartment of Psychiatry and The Behavioral Sciences, Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.

Funding

DIAN-TU Next Generation Prevention Trial - Data Request Management SupplementR01AG053267 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2017 to 2023
$34.9M
Dominantly Inherited Alzheimer's Network Trials Unit - Adaptive Prevention TrialR01AG046179 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2014 to 2019
$26.6M
DOMINANTLY INHERITED ALZHEIMER NETWORK TRIAL: AN OPPORTUNITY TO PREVENT DEMENTIAU01AG042791 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2013 to 2018
$8.9M
Accelerating Medicines Partnership R01AG046179Accelerating Medicines Partnership R01AG053267-S1FNIHNIA NIH HHSNIA NIH HHS R01 AG046179NIA NIH HHS R01 AG053267NIA NIH HHS U01 AG042791NIH HHS U01AG042791NIH HHS U01AG042791-S1
6 · The paper itself

Abstract

introductionEstimating treatment effects as time savings in disease progression may be more easily interpretable than assessing the absolute difference or a percentage reduction. In this study, we investigate the statistical considerations of the existing method for estimating time savings and propose alternative complementary methods.

methodsWe propose five alternative methods to estimate the time savings from different perspectives. These methods are applied to simulated clinical trial data that mimic or modify the Clinical Dementia Rating Sum of Boxes progression trajectories observed in the Clarity AD lecanemab trial.

resultsOur study demonstrates that the proposed methods can generate more precise estimates by considering two crucial factors: (1) the absolute difference between treatment arms, and (2) the observed progression rate in the treatment arm. DISCUSSION: Quantifying treatment effects as time savings in disease progression offers distinct advantages. To provide comprehensive estimations, it is important to use various methods. HIGHLIGHTS: We explore the statistical considerations of the current method for estimating time savings. We proposed alternative methods that provide time savings estimations based on the observed absolute differences. By using various methods, a more comprehensive estimation of time savings can be achieved.

Indexed as

Alzheimer DiseaseDisease ProgressionClinical Trials as TopicComputer SimulationHumansModels, StatisticalTime FactorsTreatment OutcomeAlzheimer's diseaseproportional mixed models for repeated measuressemi‐real trial datatime savings

Identifiers

PMID39030751
PMCPMC11350030

What OpenQuestion holds

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LicenceCC BY
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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.