Evidence map›Paper›PMID 28975068›Full record

ArticleNeuroImage. Clinical2017

Longitudinal white matter change in frontotemporal dementia subtypes and sporadic late onset Alzheimer's disease.

Fanny M Elahi, Gabe Marx, Yann Cobigo, Adam M Staffaroni, John Kornak, Duygu Tosun, Adam L Boxer, Joel H Kramer, Bruce L Miller, Howard J Rosen

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
6.4field-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

38 citing papers in PubMed, 58 citations in OpenAlex.

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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.

Fanny M ElahiMemory and Aging Center, Department of Neurology, University of California, San Francisco, United States.
Gabe MarxMemory and Aging Center, Department of Neurology, University of California, San Francisco, United States.
Yann CobigoMemory and Aging Center, Department of Neurology, University of California, San Francisco, United States.
Adam M StaffaroniMemory and Aging Center, Department of Neurology, University of California, San Francisco, United States.
John KornakDepartment of Epidemiology and Biostatistics, University of California, San Francisco, United States.
Duygu TosunDepartment of Veteran Affairs Medical Center, San Francisco, CA, United States.
Adam L BoxerMemory and Aging Center, Department of Neurology, University of California, San Francisco, United States.
Joel H KramerMemory and Aging Center, Department of Neurology, University of California, San Francisco, United States.
Bruce L MillerMemory and Aging Center, Department of Neurology, University of California, San Francisco, United States.
Howard J RosenMemory and Aging Center, Department of Neurology, University of California, San Francisco, United States.
University of California, San Francisco · USUniversity Memory and Aging Center · USSan Francisco VA Medical Center · US

Funding

TDP-43 Loss-of-Function: Biology to BiomarkersP01AG019724 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Jennifer Merrilees · 2002 to 2026
$67.2M
PrPSc SPECIFIC INTERACTION WITH NOVEL PrP-Fc FUSION PROTEINSP50AG023501 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MILLER, BRUCE L · 2004 to 2018
$27.1M
Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS)U01AG045390 · NIA · MAYO CLINIC ROCHESTER · PI BOEVE, BRADLEY F, ROSEN, HOWARD J · 2014 to 2018
$16.9M
The Frontotemporal Lobar Degeneration Neuroimaging InitiativeR01AG032306 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ROSEN, HOWARD J · 2009 to 2013
$10.0M
Multidisciplinary Research Fellowship in Alzheimer’s disease and Related DementiasT32AG023481 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BRUCE L MILLER, HOWARD J ROSEN · 2005 to 2026
$7.4M
Training - The Frontotemporal Lobar Degeneration Clinical Research ConsortiumU54NS092089 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BOXER, ADAM L. · 2014 to 2018
$6.4M
PREDICT-ADFTD: Multimodal Imaging Prediction of AD/FTD and Differential DiagnosisR01AG055121 · NIA · OHIO STATE UNIVERSITY · PI ROSEN, HOWARD J, WANG, LEI · 2017 to 2020
$2.8M
Multimodal Imaging in Frontotemporal DegenerationK24AG045333 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ROSEN, HOWARD J · 2013 to 2023
$1.9M
NIA NIH HHS K24 AG045333NIA NIH HHS P01 AG019724NIA NIH HHS P50 AG023501NIA NIH HHS R01 AG032306NIA NIH HHS R01 AG055121NIA NIH HHS T32 AG023481NIA NIH HHS U01 AG045390NINDS NIH HHS U54 NS092089
6 · The paper itself

Abstract

backgroundDegradation of white matter microstructure has been demonstrated in frontotemporal lobar degeneration (FTLD) and Alzheimer's disease (AD). In preparation for clinical trials, ongoing studies are investigating the utility of longitudinal brain imaging for quantification of disease progression. To date only one study has examined sample size calculations based on longitudinal changes in white matter integrity in FTLD.

objectiveTo quantify longitudinal changes in white matter microstructural integrity in the three canonical subtypes of frontotemporal dementia (FTD) and AD using diffusion tensor imaging (DTI).

methods60 patients with clinical diagnoses of FTD, including 27 with behavioral variant frontotemporal dementia (bvFTD), 14 with non-fluent variant primary progressive aphasia (nfvPPA), and 19 with semantic variant PPA (svPPA), as well as 19 patients with AD and 69 healthy controls were studied. We used a voxel-wise approach to calculate annual rate of change in fractional anisotropy (FA) and mean diffusivity (MD) in each group using two time points approximately one year apart. Mean rates of change in FA and MD in 48 atlas-based regions-of-interest, as well as global measures of cognitive function were used to calculate sample sizes for clinical trials (80% power, alpha of 5%).

resultsAll FTD groups showed statistically significant baseline and longitudinal white matter degeneration, with predominant involvement of frontal tracts in the bvFTD group, frontal and temporal tracts in the PPA groups and posterior tracts in the AD group. Longitudinal change in MD yielded a larger number of regions with sample sizes below 100 participants per therapeutic arm in comparison with FA. SvPPA had the smallest sample size based on change in MD in the fornix (n = 41 participants per study arm to detect a 40% effect of drug), and nfvPPA and AD had their smallest sample sizes based on rate of change in MD within the left superior longitudinal fasciculus (n = 49 for nfvPPA, and n = 23 for AD). BvFTD generally showed the largest sample size estimates (minimum n = 140 based on MD in the corpus callosum). The corpus callosum appeared to be the best region for a potential study that would include all FTD subtypes. Change in global measure of functional status (CDR box score) yielded the smallest sample size for bvFTD (n = 71), but clinical measures were inferior to white matter change for the other groups.

conclusionsAll three of the canonical subtypes of FTD are associated with significant change in white matter integrity over one year. These changes are consistent enough that drug effects in future clinical trials could be detected with relatively small numbers of participants. While there are some differences in regions of change across groups, the genu of the corpus callosum is a region that could be used to track progression in studies that include all subtypes.

Indexed as

AgedAlzheimer DiseaseBrainCross-Sectional StudiesDiffusion Tensor ImagingFemaleFrontotemporal DementiaHumansLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesSample SizeWhite MatterADBehavioral variant FTDClinical trialDTIFTDLongitudinalPrimary progressive aphasiaSample sizeWhite matter integrity

Identifiers

PMID28975068
PMCPMC5614750
OpenAlexW2755256217

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.