Literature DB >> 31229952

EULAR points to consider for the use of big data in rheumatic and musculoskeletal diseases.

Laure Gossec1,2, Joanna Kedra3,2, Hervé Servy4, Aridaman Pandit5, Simon Stones6, Francis Berenbaum7, Axel Finckh8, Xenofon Baraliakos9,10, Tanja A Stamm11, David Gomez-Cabrero12, Christian Pristipino13, Remy Choquet14, Gerd R Burmester15, Timothy R D J Radstake5.   

Abstract

BACKGROUND: Tremendous opportunities for health research have been unlocked by the recent expansion of big data and artificial intelligence. However, this is an emergent area where recommendations for optimal use and implementation are needed. The objective of these European League Against Rheumatism (EULAR) points to consider is to guide the collection, analysis and use of big data in rheumatic and musculoskeletal disorders (RMDs).
METHODS: A multidisciplinary task force of 14 international experts was assembled with expertise from a range of disciplines including computer science and artificial intelligence. Based on a literature review of the current status of big data in RMDs and in other fields of medicine, points to consider were formulated. Levels of evidence and strengths of recommendations were allocated and mean levels of agreement of the task force members were calculated.
RESULTS: Three overarching principles and 10 points to consider were formulated. The overarching principles address ethical and general principles for dealing with big data in RMDs. The points to consider cover aspects of data sources and data collection, privacy by design, data platforms, data sharing and data analyses, in particular through artificial intelligence and machine learning. Furthermore, the points to consider state that big data is a moving field in need of adequate reporting of methods and benchmarking, careful data interpretation and implementation in clinical practice.
CONCLUSION: These EULAR points to consider discuss essential issues and provide a framework for the use of big data in RMDs. © Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  epidemiology; health services research; outcomes research

Year:  2019        PMID: 31229952     DOI: 10.1136/annrheumdis-2019-215694

Source DB:  PubMed          Journal:  Ann Rheum Dis        ISSN: 0003-4967            Impact factor:   19.103


  15 in total

1.  Meta-analysis in the era of big data.

Authors:  Lucía Silva-Fernández; Loreto Carmona
Journal:  Clin Rheumatol       Date:  2019-07-04       Impact factor: 2.980

Review 2.  Big data and data processing in rheumatology: bioethical perspectives.

Authors:  Amaranta Manrique de Lara; Ingris Peláez-Ballestas
Journal:  Clin Rheumatol       Date:  2020-02-15       Impact factor: 2.980

Review 3.  The basics of data, big data, and machine learning in clinical practice.

Authors:  David Soriano-Valdez; Ingris Pelaez-Ballestas; Amaranta Manrique de Lara; Alfonso Gastelum-Strozzi
Journal:  Clin Rheumatol       Date:  2020-06-05       Impact factor: 2.980

Review 4.  Digital health technologies: opportunities and challenges in rheumatology.

Authors:  Daniel H Solomon; Robert S Rudin
Journal:  Nat Rev Rheumatol       Date:  2020-07-24       Impact factor: 20.543

Review 5.  Big data in systemic sclerosis: Great potential for the future.

Authors:  Mislav Radic; Tracy M Frech
Journal:  J Scleroderma Relat Disord       Date:  2020-07-06

6.  Profiling of IgG antibodies targeting unmodified and corresponding citrullinated autoantigens in a multicenter national cohort of early arthritis in Germany.

Authors:  Stefan Vordenbäumen; Ralph Brinks; Patrick Schriek; Angelika Lueking; Jutta G Richter; Petra Budde; Peter Schulz-Knappe; Hans-Dieter Zucht; Johanna Callhoff; Matthias Schneider
Journal:  Arthritis Res Ther       Date:  2020-07-06       Impact factor: 5.156

7.  Current status of use of big data and artificial intelligence in RMDs: a systematic literature review informing EULAR recommendations.

Authors:  Joanna Kedra; Timothy Radstake; Aridaman Pandit; Xenofon Baraliakos; Francis Berenbaum; Axel Finckh; Bruno Fautrel; Tanja A Stamm; David Gomez-Cabrero; Christian Pristipino; Remy Choquet; Hervé Servy; Simon Stones; Gerd Burmester; Laure Gossec
Journal:  RMD Open       Date:  2019-07-18

Review 8.  Current status of use of high throughput nucleotide sequencing in rheumatology.

Authors:  Sebastian Boegel; John C Castle; Andreas Schwarting
Journal:  RMD Open       Date:  2021-01

Review 9.  Aromatase Inhibitors-Induced Musculoskeletal Disorders: Current Knowledge on Clinical and Molecular Aspects.

Authors:  Sara Tenti; Pierpaolo Correale; Sara Cheleschi; Antonella Fioravanti; Luigi Pirtoli
Journal:  Int J Mol Sci       Date:  2020-08-06       Impact factor: 5.923

Review 10.  Wearable Activity Trackers in the Management of Rheumatic Diseases: Where Are We in 2020?

Authors:  Thomas Davergne; Antsa Rakotozafiarison; Hervé Servy; Laure Gossec
Journal:  Sensors (Basel)       Date:  2020-08-25       Impact factor: 3.576

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