Bone health in patients with multiple sclerosis relapses
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Updated: Mar 22, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Olwen Murphy1, Michael S Zandi2, Nitzan Lindenberg3
1Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London and National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, United Kingdom; Department of Neurology, Cork University Hospital, Wilton, Cork, Ireland.
Objectives:
To evaluate the bone health and vitamin D levels of a cohort of patients with relapses of multiple sclerosis (MS) and to propose an algorithm for the management of bone health in this patient group.
Methods:
We prospectively studied 56 consecutive patients from our acute relapse clinic. 3 patients were excluded from analysis as they were not deemed to have experienced an acute MS relapse. Bone health was assessed with vitamin D levels and Dual Energy X-ray Absorptiometry (DEXA) scanning (10 patients failed to attend for DEXA). Statistical analyses were used to compare groups and identify predictive variables. A review of the literature led to a proposed management protocol.
Results:
Pre-relapse the baseline EDSS was ≤6.5 in all subjects, and <4.0 in the majority (66%). Most received corticosteroids. 51% had low bone mineral density (BMD) as defined by a T-score less than -1.0 on DEXA scanning. Three were osteoporotic (T-score less than -2.5). Thirty one of fifty (62%) subjects were Vitamin D deficient (25(OH)D less than 50nmol/L). A range of variables, including previous corticosteroid usage, were not significantly predictive of reduced BMD.
Conclusions:
There was a high frequency of both low BMD and Vitamin D deficiency in this cohort of relatively young and largely ambulatory patients experiencing MS relapses. Current tools, such as the WHO FRAX algorithm, are inadequate in assessing bone status and fracture risk in this patient group, predominantly as they are focused on older age groups. We propose a simple clinical management algorithm.
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