Evidence map›Paper›PMID 29752462›Full record

ReviewNature reviews. Rheumatology2018

The role of radiography and MRI for eligibility assessment in DMOAD trials of knee OA.

Frank W Roemer, C Kent Kwoh, Daichi Hayashi, David T Felson, Ali Guermazi

Abstract readReview
In one paragraph

Review in Nature reviews. Rheumatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing 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

53 citing papers in PubMed.

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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

5 authors.

Frank W RoemerDepartment of Radiology, University of Erlangen-Nuremberg, Erlangen, Germany. frank.roemer@uk-erlangen.de.ORCID 0000-0001-9238-7350
C Kent KwohUniversity of Arizona Arthritis Center & Division of Rheumatology, University of Arizona College of Medicine, Tucson, AZ, USA.
Daichi HayashiQuantitative Imaging Center (QIC), Department of Radiology, Boston University School of Medicine, Boston, MA, USA.
David T FelsonClinical Epidemiology Research and Training Unit, Boston University School of Medicine, Boston, MA, USA.
Ali GuermaziQuantitative Imaging Center (QIC), Department of Radiology, Boston University School of Medicine, Boston, MA, USA.

Funding

Risk of Incident Knee OA & Clinical Outcomes Based on Imaging BiomarkersR01AR066601 · NIAMS · UNIVERSITY OF ARIZONA · PI GUERMAZI, ALI, KWOH, C KENT · 2014 to 2018
$6.2M
NIAMS NIH HHS R01 AR066601
6 · The paper itself

Abstract

Currently, no disease-modifying osteoarthritis drugs (DMOADs) have been approved. Past clinical trials have failed for several reasons, including the commonly applied definition of eligibility based on radiographic assessment of joint structure. In the context of precision medicine, finding the appropriate patient for a specific treatment approach will be of increasing relevance. Phenotypic stratification by use of imaging at the time of determining eligibility for clinical trials will be paramount and cannot be achieved using radiography alone. Furthermore, identification of joints at high risk of rapid progression of osteoarthritis is needed in order to enable a more efficient DMOAD trial design. In addition, joints at high risk of collapse need to be excluded at screening. The use of MRI might offer advantages over radiography in this context. Technological advances and simplified image assessment address many of the commonly perceived barriers to the application of MRI to assessment of eligibility for DMOAD clinical trials.

Indexed as

Antirheumatic AgentsClinical Trials as TopicDisease ProgressionHumansKnee JointMagnetic Resonance ImagingOsteoarthritis, KneePatient SelectionPrecision MedicineRadiographyResearch DesignAntirheumatic Agents

Identifiers

PMID29752462
PMCPMC6008101

What OpenQuestion holds

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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.