Evidence map›Paper›PMID 41259269›Full record

ArticleJournal of Alzheimer's disease : JAD2026

Modeling the age-specific incidence of mild cognitive impairment incorporating the time-varying relationship of Alzheimer's disease biomarkers over 28 years.

Kexin Wang, Yuxin Zhu, Marilyn Albert, Michael Miller, Christos Davatzikos, Abhay Moghekar, Anja Soldan, Mei-Cheng Wang, BIOCARD Research Team

Abstract read
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In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Kexin WangDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID 0000-0003-0124-0631
Yuxin ZhuDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0001-8441-0290
Marilyn AlbertDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Michael MillerDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Christos DavatzikosCenter for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Abhay MoghekarDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Anja SoldanDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Mei-Cheng WangDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-0460-7956
BIOCARD Research Team

Funding

Project 2 MeasurementU19AG033655 · NIA · JOHNS HOPKINS UNIVERSITY · PI Abhay Moghekar · 2014 to 2026
$51.5M
Research Education ComponentP30AG066507 · NIA · JOHNS HOPKINS UNIVERSITY · PI Corinne Pettigrew · 2020 to 2026
$29.3M
Statistical methods for analyzing risk of Alzheimer's Disease and biomarker measurementsR01AG088637 · NIA · JOHNS HOPKINS UNIVERSITY · PI Mei Cheng Wang · 2025 to 2026
$898k
NIA NIH HHS P30 AG066507NIA NIH HHS R01 AG088637NIA NIH HHS U19 AG033655
6 · The paper itself

Abstract

BackgroundAs life expectancy increases, the prevalence of mild cognitive impairment (MCI) due to Alzheimer's disease is expected to rise. Biomarkers from cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI), combined with age-specific modeling, may enhance understanding of the timing and risk factors of MCI onset.ObjectiveTo estimate age-specific incidence rates of MCI onset and examine the impact of biomarkers and demographic factors on risk.MethodsWe analyzed data from 307 cognitively unimpaired BIOCARD participants with one or more CSF and MRI measurements. To account for competing risk of death, we applied age-specific cumulative incidence functions and cause-specific Cox proportional hazard models. Time-varying biomarker values were incorporated to assess their influence on MCI risk.ResultsThe cumulative incidence rate of MCI onset estimated in age brackets from 50 to 80 was 2.33% at age 55, 5.03% at age 60, 12.38% at age 65, 17.91% at age 70, 28.84% at age 75, and 46.91% at age 80.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAgedAged, 80 and overAge FactorsAmyloid beta-PeptidesApolipoprotein E4BiomarkersFemaleHumansIncidenceMagnetic Resonance ImagingMaleMiddle AgedRisk Factorstau ProteinsAmyloid beta-PeptidesApolipoprotein E4Biomarkerstau ProteinsAlzheimer's diseaseAPOE genotypeentorhinal cortex volumemagnetic resonance imagingmild cognitive impairmentphosphorylated tausex effecttotal tau

Identifiers

PMID41259269
PMCPMC13392838

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Registered trials

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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.