Evidence map›Paper›PMID 32019594›Full record

ReviewAlzheimer's research & therapy2020

University College London/University of Gothenburg PhD course "Biomarkers in neurodegenerative diseases" 2019-course organisation.

Ayesha Khatun, Ross W Paterson, Michael Schöll

Abstract readReview
In one paragraph

Review in Alzheimer's research & therapy, 2020. 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

3 authors.

Ayesha KhatunDementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK.
Ross W PatersonDementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK.
Michael SchöllDementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK. michael.scholl@neuro.gu.se.ORCID 0000-0001-7800-1781

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biomarkers are increasingly employed for effective research into neurodegenerative diseases. They have become essential for reaching an accurate clinical diagnosis, monitoring disease, and refining entry criteria for participation in clinical treatment trials, and will be key in measuring target engagement and treatment outcome in disease-modifying therapies. Emerging techniques and research combining different biomarker modalities continue to strengthen our understanding of the underlying pathology and the sequence of pathogenic events. Given recent advances, we are now at a pivotal stage in biomarker research. PhD students working in the field of neurodegenerative disease require a working knowledge of a range of biomarkers available and their limitations, to correctly interpret scientific literature and to design and conduct successful research studies themselves. Here, we outline the University College London/University of Gothenburg "Biomarkers in neurodegenerative diseases course", the first initiative of its kind aimed to bring together both experts and PhD students from all areas within the field of neurodegeneration, to provide comprehensive knowledge of biomarker research for the next generation of scientists.

Indexed as

BiomarkersEducation, GraduateNeurodegenerative DiseasesUniversitiesCurriculumHumansLondonNeurologySwedenBiomarkersAmyloidBiomarkersBlood biomarkersCerebrospinal fluidMagnetic resonance imagingNeurodegenerative diseasesPositron emission tomographyTau

Identifiers

PMID32019594
PMCPMC7001332

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.