Evidence map›Paper›PMID 29365053›Full record

ArticleBrain : a journal of neurology2018

Predicting progression from normal cognition to mild cognitive impairment for individuals at 5 years.

Marilyn Albert, Yuxin Zhu, Abhay Moghekar, Susumu Mori, Michael I Miller, Anja Soldan, Corinne Pettigrew, Ola Selnes, Shanshan Li, Mei-Cheng Wang

Open access · bronzeAbstract read
In one paragraph

Article in Brain : a journal of neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 2 pooled it
8.2field-weighted citation impact, top 2% of its field
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

61 citing papers in PubMed, 2 syntheses or guidelines pooled it, 126 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
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  6. Review
  7. Change points for dynamic biomarkers in the Alzheimer's disease pathological cascade: A 30-year cohort study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
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  17. Article
  18. Association of Plasma AβNeurology · 2023
    Article
  19. Review
  20. Article

1 more citing papers are in PubMed but not listed here.

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

10 authors at 3 institutions in 1 country.

Marilyn AlbertDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Yuxin ZhuDepartment of Biostatistics, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD 21205, USA.
Abhay MoghekarDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Susumu MoriDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Michael I MillerDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Anja SoldanDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Corinne PettigrewDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Ola SelnesDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Shanshan LiDepartment of Biostatistics, Indiana University School of Public Health, Indianapolis, IN, USA.
Mei-Cheng WangDepartment of Biostatistics, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD 21205, USA.
Johns Hopkins University · USJohns Hopkins Medicine · USIndiana University – Purdue University Indianapolis · US

Funding

Project 2 MeasurementU19AG033655 · NIA · JOHNS HOPKINS UNIVERSITY · PI Abhay Moghekar · 2014 to 2026
$51.5M
'T V ASSESSMENT - MEMORY DISORDERED PATIENTS'P50AG005146 · NIA · JOHNS HOPKINS UNIVERSITY · PI HUGANIR, RICHARD L · 1985 to 2019
$37.6M
X-LINKED ADRENOLEUKODYSTROPHYP41RR015241 · NCRR · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI MC DONALD, JOHN · 2001 to 2011
$18.5M
TR&D 4: Algorithms for functional and anatomical brain analysisP41EB015909 · NIBIB · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI VAN ZIJL, PETER CM · 2012 to 2020
$13.1M
NCRR NIH HHS P41 RR015241NIA NIH HHS P50 AG005146NIA NIH HHS U19 AG033655NIBIB NIH HHS P41 EB015909
6 · The paper itself

Abstract

Recent evidence indicates that measures from cerebrospinal fluid, MRI scans and cognitive testing obtained from cognitively normal individuals can be used to predict likelihood of progression to mild cognitive impairment several years later, for groups of individuals. However, it remains unclear whether these measures are useful for predicting likelihood of progression for an individual. The increasing focus on early intervention in clinical trials for Alzheimer's disease emphasizes the importance of improving the ability to identify which cognitively normal individuals are more likely to progress over time, thus allowing researchers to efficiently screen participants, as well as determine the efficacy of any treatment intervention. The goal of this study was to determine which measures, obtained when individuals were cognitively normal, predict on an individual basis, the onset of clinical symptoms associated with a diagnosis of mild cognitive impairment due to Alzheimer's disease. Cognitively normal participants (n = 224, mean baseline age = 57 years) were evaluated with a range of measures, including: cerebrospinal fluid amyloid-β and phosphorylated-tau, hippocampal and entorhinal cortex volume, cognitive tests scores and APOE genotype. They were then followed to determine which individuals developed mild cognitive impairment over time (mean follow-up = 11 years). The primary outcome was progression from normal cognition to the onset of clinical symptoms of mild cognitive impairment due to Alzheimer's disease at 5 years post-baseline. Time-dependent receiver operating characteristic analyses examined the sensitivity and specificity of individual measures, and combinations of measures, as predictors of the outcome. Six measures, in combination, were the most parsimonious predictors of transition to mild cognitive impairment 5 years after baseline (area under the curve = 0.85; sensitivity = 0.80, specificity = 0.75). The addition of variables from each domain significantly improved the accuracy of prediction. The incremental accuracy of prediction achieved by adding individual measures or sets of measures successively to one another was also examined, as might be done when enrolling individuals in a clinical trial. The results indicate that biomarkers obtained when individuals are cognitively normal can be used to predict which individuals are likely to develop clinical symptoms at 5 years post-baseline. As a number of the measures included in the study could also be used as subject selection criteria in a clinical trial, the findings also provide information about measures that would be useful for screening in a clinical trial aimed at individuals with preclinical Alzheimer's disease.

Indexed as

Disease ProgressionAgedAmyloid beta-PeptidesAniline CompoundsApolipoproteins EBrainCognitive DysfunctionCohort StudiesFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeuropsychological TestsPositron-Emission TomographyPredictive Value of Tests2-(4'-(methylamino)phenyl)-6-hydroxybenzothiazoleAmyloid beta-PeptidesAniline CompoundsApolipoproteins Etau ProteinsThiazoles

Identifiers

PMID29365053
PMCPMC5837651
OpenAlexW2790793038

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.