Modelling disease progression in relapsing-remitting onset multiple sclerosis using multilevel models applied to longitudinal data from two natural history cohorts and one treated cohort

Tilling K, Lawton M, Robertson N, Tremlett H, Zhu F, Harding K, Oger J, Ben-Shlomo Y
Record ID 32016001092
English
Authors' objectives: The ability to better predict disease progression represents a major unmet need in multiple sclerosis (MS), and would help to inform therapeutic and management choices. This study aims to develop multilevel models using longitudinal data on disease progression in patients with relapsing–remitting MS (RRMS) or secondary-progressive MS (SPMS); and to use these models to estimate the association of disease-modifying therapy (DMT) with progression.
Authors' recommendations: EDSS score progression in two natural history cohorts of MS patients showed a similar pattern. Progression in the natural history cohorts was slightly faster than EDSS score progression in the DMT-treated cohort, up to 6 years post treatment.
Details
Project Status: Completed
URL for project: http://www.nets.nihr.ac.uk/projects/hta/105501
Year Published: 2016
URL for published report: http://www.journalslibrary.nihr.ac.uk/hta/hta20810/#/abstract
English language abstract: An English language summary is available
Publication Type: Not Assigned
Country: England, United Kingdom
MeSH Terms
  • Humans
  • Disease Progression
  • Multilevel Analysis
  • Multiple Sclerosis
  • Multiple Sclerosis, Relapsing-Remitting
Contact
Organisation Name: NIHR Health Technology Assessment programme
Contact Address: NIHR Journals Library, National Institute for Health and Care Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK
Contact Name: journals.library@nihr.ac.uk
Contact Email: journals.library@nihr.ac.uk
Copyright: Queen's Printer and Controller of HMSO
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