Prognostic factors for long-term outcomes in relapsing-remitting multiple sclerosis.
| Autor: | Traboulsee AL; Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada., Cornelisseª P; Merck Serono S.A., Geneva, Switzerland., Sandberg-Wollheim M; Department of Neurology, University Hospital, Lund, Sweden., Uitdehaag BM; MS Center Amsterdam, Department of Neurology, VU Medical Center, Amsterdam, The Netherlands., Kappos L; Departments of Neurology and Biomedicine, University of Basel, Basel, Switzerland., Jongen PJ; University Groningen, University Medical Center Groningen, Department of Community & Occupational Medicine, Groningen, The Netherlands., Constantinescu CS; Division of Clinical Neurology, University of Nottingham, Nottingham, UK., di Cantogno EV; Ares Trading S.A., Aubonne, Switzerland., Li DK; Department of Radiology, University of British Columbia, Vancouver, BC, Canada. |
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| Jazyk: | angličtina |
| Zdroj: | Multiple sclerosis journal - experimental, translational and clinical [Mult Scler J Exp Transl Clin] 2016 Sep 06; Vol. 2, pp. 2055217316666406. Date of Electronic Publication: 2016 Sep 06 (Print Publication: 2016). |
| DOI: | 10.1177/2055217316666406 |
| Abstrakt: | Objective: The objective of this article is to investigate potential clinical and MRI predictors of long-term outcomes in multiple sclerosis (MS). Methods: This was a post hoc analysis using data from all 382 patients in the PRISMS long-term follow-up (LTFU) study collected up to eight years after randomisation. An additional analysis was performed including only those patients originally randomised to receive early subcutaneous interferon (IFN) β-1a ( n = 259). Baseline/prestudy variables, indicators of early clinical and MRI activity (baseline to month 24), and indicators of IFN β-1a treatment exposure (including medication possession ratio (MPR)) were investigated as candidate prognostic factors for outcomes measured from baseline and from month 24 to LTFU. Explanatory variables identified from univariate regression models ( p ≤ 0.15) were selected for inclusion in stepwise multiple regression models. Results: Candidate prognostic factors selected by the univariate analysis ( p ≤ 0.15) included age, MS duration, baseline brain volume, EDSS score, and log(T2 burden of disease (BOD)). In most of the multivariate regression models applied, higher baseline brain volume and MPR predicted better long-term clinical outcomes, while higher baseline and greater early increase in EDSS score predicted worse outcomes. Conclusion: Identification of markers that may be prognostic for long-term disability could help identify MS patients at higher risk of disability progression. |
| Databáze: | MEDLINE |
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