Evidence map›Paper›PMID 38835820›Full record

ArticleAlzheimer's & dementia (New York, N. Y.)

Assessing tilavonemab efficacy in early Alzheimer's disease via longitudinal item response theory modeling.

Xiaoxiao Zhou, Haotian Zou, Michael W Lutz, Konstantin Arbeev, Igor Akushevich, Anatoli Yashin, Kathleen A Welsh-Bohmer, Sheng Luo

Abstract read
In one paragraph

Article in Alzheimer's & dementia (New York, N. Y.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

8 authors.

Xiaoxiao ZhouDepartment of Biostatistics & Bioinformatics Duke University Durham North Carolina USA.ORCID https://orcid.org/0000-0003-3950-1980
Haotian ZouDepartment of Biostatistics & Bioinformatics Duke University Durham North Carolina USA.
Michael W LutzDivision of Translational Brain Sciences Department of Neurology Duke University Medical Center Durham North Carolina USA.
Konstantin ArbeevSocial Science Research Institute Duke University Durham North Carolina USA.
Igor AkushevichSocial Science Research Institute Duke University Durham North Carolina USA.
Anatoli YashinSocial Science Research Institute Duke University Durham North Carolina USA.
Kathleen A Welsh-BohmerDepartment of Psychiatry Duke University Durham North Carolina USA.
Sheng LuoDepartment of Biostatistics & Bioinformatics Duke University Durham North Carolina USA.ORCID https://orcid.org/0000-0003-4214-5809

Funding

Research Education Component CoreP30AG072958 · NIA · DUKE UNIVERSITY · PI GWENN A GARDEN, Heather E. Whitson · 2021 to 2026
$24.1M
Integrative modeling and dynamic prediction of Alzheimer's diseaseR01AG064803 · NIA · DUKE UNIVERSITY · PI LUO, SHENG · 2020 to 2024
$2.3M
Integrative modeling and dynamic prediction of Alzheimer's diseaseR56AG064803 · NIA · DUKE UNIVERSITY · PI LUO, SHENG · 2019 to 2019
$483k
NIA NIH HHS P30 AG072958NIA NIH HHS R01 AG064803NIA NIH HHS R56 AG064803
6 · The paper itself

Abstract

introductionAlzheimer's disease (AD) is a neurodegenerative disorder characterized by declines in cognitive and functional severities. This research utilized the Clinical Dementia Rating (CDR) to assess the influence of tilavonemab on these deteriorations.

methodsLongitudinal Item Response Theory (IRT) models were employed to analyze CDR domains in early-stage AD patients. Both unidimensional and multidimensional models were contrasted to elucidate the trajectories of cognitive and functional severities.

resultsWe observed significant temporal increases in both cognitive and functional severities, with the cognitive severity deteriorating at a quicker rate. Tilavonemab did not demonstrate a statistically significant effect on the progression in either severity. Furthermore, a significant positive association was identified between the baselines and progression rates of both severities. DISCUSSION: While tilavonemab failed to mitigate impairment progression, our multidimensional IRT analysis illuminated the interconnected progression of cognitive and functional declines in AD, suggesting a comprehensive perspective on disease trajectories. Highlights: Utilized longitudinal Item Response Theory (IRT) models to analyze the Clinical Dementia Rating (CDR) domains in early-stage Alzheimer's disease (AD) patients, comparing unidimensional and multidimensional models.Observed significant temporal increases in both cognitive and functional severities, with cognitive severity deteriorating at a faster rate, while tilavonemab showed no statistically significant effect on either domain's progression.Found a significant positive association between the baseline severities and their progression rates, indicating interconnected progression patterns of cognitive and functional declines in AD.Introduced the application of multidimensional longitudinal IRT models to provide a comprehensive perspective on the trajectories of cognitive and functional severities in early AD, suggesting new avenues for future research including the inclusion of time-dependent random effects and data-driven IRT models.

Indexed as

bayesian modelingclinimetricsdisease progressionlongitudinal data

Identifiers

PMID38835820
PMCPMC11148533

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LicenceCC BY-NC-ND
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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.