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Record W4312087239 · doi:10.1002/alz.066159

Longitudinal changes in plasma p‐tau181 as a surrogate variable to populational interventions

2022· article· en· W4312087239 on OpenAlexaff
Pâmela C.L. Ferreira, João Pedro Ferrari‐Souza, Andréa Lessa Benedet, Nicholas J. Ashton, Cécile Tissot, Bruna Bellaver, Douglas Teixeira Leffa, Wagner S. Brum, Joseph Therriault, Mira Chamoun, Firoza Z Lussier, Min Su Kang, Jenna Stevenson, Jean‐Paul Soucy, Serge Gauthier, Thomas K. Karikari, Henrik Zetterberg, Kaj Blennow, Eduardo R. Zimmer, Pedro Rosa‐Neto, Tharick A. Pascoal

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsLongitudinal studyInternal medicineMedicineDementiaAlzheimer's diseasePsychologyDiseaseCardiologyPathology

Abstract

fetched live from OpenAlex

Abstract Background It has already been shown that longitudinal changes in plasma phosphorylated tau 181 (p‐tau181) correlate with longitudinal Alzheimer’s disease (AD) progression. However, it is unclear whether longitudinal plasma p‐tau181 is a suitable measure to be used as a surrogate variable in clinical trials. This study aims to evaluate the utility of using longitudinal changes in plasma p‐tau181 to monitor drug effects in AD clinical trials. Method We evaluated 715 individuals (227 cognitively unimpaired (CU) amyloid‐beta (Aβ ) negative, 103 CU Aβ positive, 265 mild cognitive impairment (MCI) Aβ positive, and 120 Alzheimer’s disease (AD) dementia Aβ positive) from the Alzheimer’s Disease Neuroimaging Initiative. Individuals diagnosed with AD or MCI were classified as cognitive impaired (CI). The subjects had [18F]florbetapir Aβ PET at baseline and longitudinal plasma p‐tau181 (up to 4‐year follow‐up duration). We determined the longitudinal rates of change in plasma p‐tau181 concentrations and its effect sizes, calculated as mean change divided by the standard deviation. Logistic regression tested whether the longitudinal change in p‐tau181 status was associated with individuals’ clinical deterioration. Result Plasma p‐tau181 slope of change was positively associated with baseline plasma p‐tau concentrations (Fig 1). Longitudinal increase in plasma p‐tau181 was correlated with longitudinal worsening in cognition. Long‐term increase in plasma p‐tau181 values was more consistent in CU Aβ negative (48‐month effects size=0.4) and CU Aβ positive (48‐month effects size=0.6) than in CI Aβ positive (48‐month effects size=0.2) individuals (Fig 2). Conclusion Monitoring change in plasma p‐tau181 status from negative to positive can be helpful to identify individuals on the verge of cognitive deterioration in clinical practice. Longitudinal changes in plasma p‐tau181 values can open a new frontier in AD research offering a cost‐effective and scalable alternative to be used as a surrogate variable in large‐scale trials designed to test the effects of population interventions on the natural history of tau pathology in elderly populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.357
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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