Characterisation of MS phenotypes across the age span using a novel data set integrating 34 clinical trials (NO.MS cohort): Age is a key contributor to presentation

Abstract

Background: The Oxford Big Data Institute, multiple sclerosis (MS) physicians and Novartis aim to address unresolved questions in MS with a novel comprehensive clinical trial data set. Objective: The objective of this study is to describe the Novartis–Oxford MS (NO.MS) data set and to explore the relationships between age, disease activity and disease worsening across MS phenotypes. Methods: We report key characteristics of NO.MS. We modelled MS lesion formation, relapse frequency, brain volume change and disability worsening cross-sectionally, as a function of patients’ baseline age, using phase III study data (≈8000 patients). Results: NO.MS contains data of ≈35,000 patients (>200,000 brain images from ≈10,000 patients), with >10 years follow-up. (1) Focal disease activity is highest in paediatric patients and decreases with age, (2) brain volume loss is similar across age and phenotypes and (3) the youngest patients have the lowest likelihood (<25%) of disability worsening over 2 years while risk is higher (25%–75%) in older, disabled or progressive MS patients. Young patients benefit most from treatment. Conclusion: NO.MS will illuminate questions related to MS characterisation, progression and prognosis. Age modulates relapse frequency and, thus, the phenotypic presentation of MS. Disease worsening across all phenotypes is mediated by age and appears to some extent be independent from new focal inflammatory activity.

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“…Age, gender and disability at baseline or acquired within 3 years before withdrawal from treatment (with mostly injectable drugs) determine the risk of not remaining stable in the long term [13][14][15][16]. These data are in accordance with circumstantial evidence that the inflammatory component of MS, and consequently the efficacy of DMD, declines with increasing age [17,18].…”

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“…It comprised simple comparisons of MRI outcome measures as well as correction for significantly different baseline parameters through multiple linear regression models and through a single binary logistic model. Weighing potential confounders, we prioritized age in the selections step as it considerably influences the course of MS [27][28][29] and the speed of GM loss even in normal aging [30,31]. To this end, we selected only patients of an age within the overlapping range of both treatment groups.…”

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“…B. [ 27 , 125 ]). Grob lässt sich sagen, dass die Entzündungsaktivität und auch der Effekt der Immuntherapie, insbesondere die Beeinflussung der Progression, mit dem Alter abnimmt.…”