Evidence map›Paper›PMID 27830173›Full record

ArticleAlzheimer's & dementia (Amsterdam, Netherlands)2016

Alzheimer's disease severity, objectively determined and measured.

Alden L Gross, Dan M Mungas, Jeannie-Marie S Leoutsakos, Marilyn S Albert, Richard N Jones

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Alzheimer's & dementia (Amsterdam, Netherlands), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
7.5field-weighted citation impact, top 3% 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

12 citing papers in PubMed, 18 citations in OpenAlex.

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  11. AD risk score for the early phases of disease based on unsupervised machine learning.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2020
    Observational
  12. 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

5 authors at 4 institutions in 1 country.

Alden L GrossDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Johns Hopkins University Center on Aging and Health, Baltimore, MD, USA.
Dan M MungasDepartment of Psychiatry, University of California, San Diego, CA, USA.
Jeannie-Marie S LeoutsakosDepartment of Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Marilyn S AlbertDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Richard N JonesDepartment of Psychiatry, Warren Alpert Medical School, Brown University, Providence, RI, USA; Department of Human Behavior and Neurology, Warren Alpert Medical School, Brown University, Providence, RI, USA.
Johns Hopkins Medicine · USJohns Hopkins University · USBrown University · USUniversity of California, San Diego · US

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Project 2 MeasurementU19AG033655 · NIA · JOHNS HOPKINS UNIVERSITY · PI Mei Cheng Wang · 2014 to 2026
$51.5M
'T V ASSESSMENT - MEMORY DISORDERED PATIENTS'P50AG005146 · NIA · JOHNS HOPKINS UNIVERSITY · PI ALBERT, MARILYN S. · 1985 to 2019
$37.6M
X-LINKED ADRENOLEUKODYSTROPHYP41RR015241 · NCRR · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI BARKER, PETER B · 2001 to 2011
$18.5M
Conference on Advanced Psychometric Methods in Cognitive Aging ResearchR13AG030995 · NIA · UNIVERSITY OF CALIFORNIA AT DAVIS · PI MUNGAS, DAN M. · 2008 to 2022
$620k
NCRR NIH HHS P41 RR015241NIA NIH HHS P50 AG005146NIA NIH HHS R13 AG030995NIA NIH HHS U01 AG024904NIA NIH HHS U19 AG033655
6 · The paper itself

Abstract

introductionWith expansion of clinical trials to individuals across the spectrum of Alzheimer disease (AD) from preclinical to symptomatic phases, it is increasingly important to quantify AD severity using methods that capture underlying pathophysiology.

methodsWe derived an AD severity measure based on biomarkers from brain imaging, neuropathology, and cognitive testing using latent variable modeling. We used data from ADNI-1 (N = 822) and applied findings to BIOCARD study (N = 349). We evaluated criterion validity for distinguishing diagnostic groups and construct validity by evaluating rates of change in AD severity.

resultsThe AD severity factor cross-sectionally distinguishes cognitively normal participants from MCI (AUC = 0.87) and AD dementia (AUC = 0.94). Among ADNI MCI subjects, worsening scores predict faster progression to AD dementia (HR = 1.17; 95% CI, 1.13-1.22). In ADNI and BIOCARD, the pace of change in AD severity is steepest among progressors, with persisting differences by baseline diagnosis. DISCUSSION: Our content-valid latent variable measurement model is a reasonable approach for grading AD severity across a broad spectrum beginning at preclinical stages of AD.

Indexed as

Alzheimer's diseaseClinical trialsCognitive testingImagingItem response theoryLongitudinal follow-upMeasurement

Identifiers

PMID27830173
PMCPMC5078784
OpenAlexW2534074075

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.