Evidence map›Paper›PMID 25701074›Full record

ArticleDrugs & aging2015

Can we identify patients with high risk of osteoarthritis progression who will respond to treatment? A focus on epidemiology and phenotype of osteoarthritis.

Olivier Bruyère, Cyrus Cooper, Nigel Arden, Jaime Branco, Maria Luisa Brandi, Gabriel Herrero-Beaumont, Francis Berenbaum, Elaine Dennison, Jean-Pierre Devogelaer, Marc Hochberg and 7 more

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Drugs & aging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 60 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 1 pooled it
12.9field-weighted citation impact, top 1% 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

60 citing papers in PubMed, 1 synthesis or guideline pooled it, 134 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 15 institutions in 10 countries.

Olivier BruyèreDepartment of Public Health, Epidemiology and Health Economics, University of Liège, CHU Sart-Tilman B23, 4000, Liège, Belgium, olivier.bruyere@ulg.ac.be.
Cyrus Cooper
Nigel Arden
Jaime Branco
Maria Luisa Brandi
Gabriel Herrero-Beaumont
Francis Berenbaum
Elaine Dennison
Jean-Pierre Devogelaer
Marc Hochberg
John Kanis
Andrea Laslop
Tim McAlindon
Susanne Reiter
Pascal Richette
René Rizzoli
Jean-Yves Reginster
University of Liège · BEUniversity of Oxford · GBAustrian Agency for Health and Food Safety · ATFederal Institute for Drugs and Medical Devices · DEHospital de Egas Moniz · PTHospital Universitario Fundación Jiménez Díaz · ESMRC Lifecourse Epidemiology Unit · GBSorbonne Université · FRTufts Medical Center · USUCLouvain · BEUniversité Paris Cité · FRUniversity Hospital of Geneva · CHUniversity of Florence · ITUniversity of Maryland, Baltimore · USUniversity of Sheffield · GB

Funding

Medical Research Council G0400491Medical Research Council MC_U147574234Medical Research Council MC_U147574237Medical Research Council MC_U147585819Medical Research Council MC_U147585824Medical Research Council MC_U147585827Medical Research Council MC_UP_A620_1014Medical Research Council MC_UU_12011/1
6 · The paper itself

Abstract

Osteoarthritis is a syndrome affecting a variety of patient profiles. A European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis and the European Union Geriatric Medicine Society working meeting explored the possibility of identifying different patient profiles in osteoarthritis. The risk factors for the development of osteoarthritis include systemic factors (e.g., age, sex, obesity, genetics, race, and bone density) and local biomechanical factors (e.g., obesity, sport, joint injury, and muscle weakness); most also predict disease progression, particularly joint injury, malalignment, and synovitis/effusion. The characterization of patient profiles should help to better orientate research, facilitate trial design, and define which patients are the most likely to benefit from treatment. There are a number of profile candidates. Generalized, polyarticular osteoarthritis and local, monoarticular osteoarthritis appear to be two different profiles; the former is a feature of osteoarthritis co-morbid with inflammation or the metabolic syndrome, while the latter is more typical of post-trauma osteoarthritis, especially in cases with severe malalignment. Other biomechanical factors may also define profiles, such as joint malalignment, loss of meniscal function, and ligament injury. Early- and late-stage osteoarthritis appear as separate profiles, notably in terms of treatment response. Finally, there is evidence that there are two separate profiles related to lesions in the subchondral bone, which may determine benefit from bone-active treatments. Decisions on appropriate therapy should be made considering clinical presentation, underlying pathophysiology, and stage of disease. Identification of patient profiles may lead to more personalized healthcare, with more targeted treatment for osteoarthritis.

Indexed as

Bone and BonesBone DensityDisease ProgressionHumansOsteoarthritisPhenotypeRisk Factors

Identifiers

PMID25701074
PMCPMC4366553
OpenAlexW2119479015

What OpenQuestion holds

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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.