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http://hdl.handle.net/1942/28184
Title: | Multidisciplinary data infrastructures in multiple sclerosis: Why they are needed and can be done! | Authors: | PEETERS, Liesbet van Munster, Caspar E. VAN WIJMEERSCH, Bart BRUYNDONCKX, Robin LAMERS, Ilse HELLINGS, Niels POPESCU, Veronica Thalheim, Christoph FEYS, Peter |
Issue Date: | 2018 | Source: | Multiple Sclerosis Journal, 25(4), p. 500-509 | Abstract: | Personalized treatment is highly desirable in multiple sclerosis (MS). We believe that multidisciplinary measurements including clinical, functional and patient-reported outcome measures in combination with extensive patient profiling can enhance personalized treatment and rehabilitation strategies. We elaborate on four reasons behind this statement: (1) MS disease activity and progression are complex and multidimensional concepts in nature and thereby defy a one-size-fits-all description, (2) functioning, progression, treatment, and rehabilitation effects are interdependent and should be investigated together, (3) personalized healthcare is based on the dynamics of system biology and on technology that confirms a patient’s fundamental biology and (4) inclusion of patient-reported outcome measures can facilitate patient-relevant healthcare. We discuss currently available multidisciplinary MS data initiatives and introduce joint actions to further increase the overall success. With this topical review, we hope to drive the MS community to invest in expanding towards more multidisciplinary and longitudinal data collection. | Keywords: | Individualized medicine; data management; multidisciplinary treatment; multiple sclerosis | Document URI: | http://hdl.handle.net/1942/28184 | ISSN: | 1352-4585 | e-ISSN: | 1477-0970 | DOI: | 10.1177/1352458518807076 | ISI #: | 000461643500001 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2020 |
Appears in Collections: | Research publications |
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1352458518807076.pdf Restricted Access | Published version | 965.04 kB | Adobe PDF | View/Open Request a copy |
peeters-et-al-multidisciplinary-data-infrastructures-arg-comments-3-8-2018.pdf | Non Peer-reviewed author version | 835.79 kB | Adobe PDF | View/Open |
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