2017 EULAR recommendations for a core data set to support observational research and clinical care in rheumatoid arthritis
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu konsensus - konference, časopisecké články, práce podpořená grantem
Grantová podpora
G0902272
Medical Research Council - United Kingdom
PubMed
29301783
DOI
10.1136/annrheumdis-2017-212256
PII: S0003-4967(24)00924-5
Knihovny.cz E-zdroje
- Klíčová slova
- outcomes research, quality indicators, rheumatoid arthritis,
- MeSH
- konsensus MeSH
- lidé MeSH
- pozorovací studie jako téma metody normy MeSH
- revmatoidní artritida * MeSH
- sběr dat metody normy MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- konsensus - konference MeSH
- práce podpořená grantem MeSH
Personalised medicine, new discoveries and studies on rare exposures or outcomes require large samples that are increasingly difficult for any single investigator to obtain. Collaborative work is limited by heterogeneities, both what is being collected and how it is defined. To develop a core set for data collection in rheumatoid arthritis (RA) research which (1) allows harmonisation of data collection in future observational studies, (2) acts as a common data model against which existing databases can be mapped and (3) serves as a template for standardised data collection in routine clinical practice to support generation of research-quality data. A multistep, international multistakeholder consensus process was carried out involving voting via online surveys and two face-to-face meetings. A core set of 21 items ('what to collect') and their instruments ('how to collect') was agreed: age, gender, disease duration, diagnosis of RA, body mass index, smoking, swollen/tender joints, patient/evaluator global, pain, quality of life, function, composite scores, acute phase reactants, serology, structural damage, treatment and comorbidities. The core set should facilitate collaborative research, allow for comparisons across studies and harmonise future data from clinical practice via electronic medical record systems.
Academic Rheumatology Department King's College London London UK
Biomedical Research Centre NIHR Birmingham Birmingham UK
Department of Biomedical Informatics Columbia University New York USA
Department of Internal Medicine 3 Division of Rheumatology Medical University Vienna Vienna Austria
Department of Medicine Solna Karolinska Institutet Stockholm Sweden
Department of Patient and Care Maastricht University Medical Centre Maastricht The Netherlands
Department of Rheumatology 1st Faculty of Medicine Charles University Prague Czech Republic
Department of Rheumatology and Clinical Immunology Charité University Medicine Berlin Berlin Germany
Department of Rheumatology AP HP Hopital Pitie Salpetriere Paris France
Department of Rheumatology Bernhoven Uden The Netherlands
Department of Rheumatology Erasmus Medical Center Rotterdam The Netherlands
Department of Rheumatology Karolinska University Hospital Stockholm Sweden
Department of Rheumatology Leiden University Medical Center Leiden The Netherlands
Department of Rheumatology Martina Hansens Hospital Gjettum Norway
Department of Rheumatology North Devon UK
Institute of Rheumatology Institute of Rheumatology Prague Czech Republic
Instituto de Salud Musculoesquelética Instituto de Salud Musculoesquelética Madrid Spain
Janssen Research and Development Janssen Titusville USA
Norwegian University of Science and Technology Trondheim Norway
Patient Partner of Romanian League Against Rheumatism Bucharest Romania
Patient Research Partner Paris France
Rheumatology Department Gartnavel General Hospital Glasgow UK
Rheumatology Department Sorbonne Universités UPMC University Paris Paris France
Sandwell and West Birmingham Hospitals NHS Trust Birmingham UK
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