Evidence map›Paper›PMID 40065919›Full record

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

Blood-based biomarker prescreening with different testing combinations and cutoffs: A simulation study examining efficacy and cost-effectiveness in Alzheimer's disease prevention studies.

Kenichiro Sato, Yoshiki Niimi, Ryoko Ihara, Atsushi Iwata, Kazushi Suzuki, Takeshi Iwatsubo

Abstract read
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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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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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

5 citing papers in PubMed.

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4 · The record

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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

6 authors.

Kenichiro SatoDepartment of Neuropathology Graduate School of Medicine The University of Tokyo Bunkyo-ku Tokyo Japan.ORCID https://orcid.org/0000-0003-4351-9526
Yoshiki NiimiUnit for Early and Exploratory Clinical Development The University of Tokyo Hospital Bunkyo-ku Tokyo Japan.
Ryoko IharaDepartment of Neurology Tokyo Metropolitan Institute for Geriatrics and Gerontology Itabashi-ku Tokyo Japan.
Atsushi IwataDepartment of Neurology Tokyo Metropolitan Institute for Geriatrics and Gerontology Itabashi-ku Tokyo Japan.
Kazushi SuzukiDivision of Neurology, Internal Medicine National Defense Medical College Tokorozawa-shi Saitama Japan.
Takeshi IwatsuboDepartment of Neuropathology Graduate School of Medicine The University of Tokyo Bunkyo-ku Tokyo Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBlood-based biomarkers (BBBMs), including plasma amyloid beta (Aβ) or phosphorylated tau (p-tau), combined with apolipoprotein E (

methodsWe conducted a simulation study utilizing data from our ongoing Japanese Trial-Ready Cohort (J-TRC) onsite study (

resultsApplying BBBM prescreening significantly decreased sensitivity and increased specificity and PPV compared to the no-prescreening scenario. Although no single model was superior in all performance metrics, a trade-off between sensitivity and specificity was observed. Generalized linear models (GLMs) simultaneously incorporating plasma Aβ42/Aβ40 ratio and p-tau217 showed a balanced efficacy (the best level of improvement in number needed to screen (NNS) but modest worsening in sensitivity) and the best level of cost-effectiveness compared to other models, although there were substantial overlaps in their 95% confidence intervals (CIs). The minimum-required PET/BBBM cost ratio to achieve improved cost-effectiveness by employing the prescreening process was negatively associated with the background prevalence of amyloid positivity. DISCUSSION: The choice of prescreening strategy in AD prevention studies/trials should be tailored to specific trial requirements, considering the relative importance of sensitivity versus cost-effectiveness, local testing cost environments, and background population characteristics. Highlights: We investigated different models of blood-based biomarker (BBBM) prescreening.Data from Japanese Trial-Ready Cohort Study were used for simulation.BBBM reduced the number needed to screen with positron emission tomography (PET) but decreased the sensitivity.The cost-effectiveness improved with a higher PET/BBBM cost ratio.No single model was optimal for all scenarios.

Indexed as

Alzheimer's diseaseblood‐based biomarkerclinical trialcost‐effectivenesspredictive performanceprescreening

Identifiers

PMID40065919
PMCPMC11891560

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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.