The MS population is ageing: over half of all MS patients are now ≥50 years of age. The effectiveness of DMT declines with age, while the risk of adverse events increases. Discontinuing DMT is an option, but the optimal patient profile for this approach has yet to be established. Therefore, Dr René Carvajal (Vall Hebron University Hospital, Spain) and colleagues conducted a study to characterise DMT discontinuation (incidence, reason for) and compare inflammatory and neurodegenerative outcomes in patients who discontinued versus those who continued treatment [1]. They included patients with MS who were ≥50 years of age and had received DMT for ≥6 months between 1994 and 2024.
Among 3,197 older MS participants in the prospective cohort, 563 were eligible for inclusion. Patients on immune reconstitution therapies were excluded. Of the participants included, 113 (20%) discontinued therapy; the median age was 58 years, the median disease duration was 21 years, the median Expanded Disability Status Scale (EDSS) score was 5.5, and the median time free of inflammatory activity was 4.5 years. Baseline was set 6 months after treatment discontinuation. A propensity score of 6:1 was used to match the continuation and discontinuation groups.
Of these 113 participants, 82 (73%) stopped first-line therapies (mainly due to tolerability issues), 26 (23%) discontinued anti-CD20 treatment, and 5 (4%) stopped anti-trafficking therapy (in both groups primarily due to safety concerns/infections).
Results after a median follow-up of about 5 years were compared with those of 581 patients who continued therapy. In patients ≥50 years of age, discontinuation was associated with higher inflammatory activity, with the highest levels observed in those treated with anti-trafficking DMTs and the lowest in the anti-CD20 therapy users group. MRI activity was also higher, but did not translate into a clear clinical impact. In the discontinuation group, 19.2% of participants experienced relapses versus 14.1% in the continuation group (P=0.6); MRI activity was observed in 40.9% versus 17.9%, respectively (P<0.005).
The risks associated with discontinuation were attenuated in patients >60 years of age (P=0.027) and were not linked to disease stability or treatment duration. In patients >60 years of age, the likelihood of resuming therapy was 93% lower than in those 50–55 years of age. Dr Carvajal stressed that anti-trafficking therapies should not be withdrawn without a clear exit strategy.
- Carvajal R, et al. Defining optimal profiles for treatment discontinuation in older MS patients. O006, ECTRIMS 2025 Congress, 24–26 September 2025, Barcelona, Spain.
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Table of Contents: ECTRIMS 2025
Featured articles
Letter from the Editor
Treatment Trials
Frexalimab shows favourable long-term safety and efficacy
Mesenchymal stem cells show no neuroregenerative benefit in PMS
Small remyelinating effect of metformin plus clemastine
Safety
Live attenuated MMR and varicella vaccines do not increase relapse risk
Treatment Strategies
Major shift in France from moderate-efficacy to anti-CD20 therapies
Caution is needed when discontinuing DMT in individuals under 60
Halving the yearly rituximab dose maintains efficacy in RRMS
Progressive MS
High-dose ocrelizumab has no additional benefit in PPMS
Nurr1 activation: A novel approach to preventing neurodegeneration in MS
Ocrelizumab delays disability progression in older patients with PPMS
Prevention and diagnosis
High intake of ultra-processed food linked to increased MS activity
Applying the new McDonald criteria increases the rate of MS diagnosis
Paediatric MS
Anti-CD20 therapies outperform platform DMTs in prepubertal MS
Ocrelizumab established as a new option for children with MS
NMOSD and MOGAD
Maintenance MOGAD therapy can be safely discontinued
Novel anti-CD20 antibody shows efficacy in AQP4-IgG-positive NMOSD
Cognition
Machine learning enables personalised prediction of cognitive decline in MS
“Give physical and cognitive symptoms equal attention in MS”
Biomarkers and Phenotypes
A 13-protein panel firmly predicts PIRA over the next year
Artificial Intelligence
No clear link between comorbidities and risk of PIRA
Machine learning applied to MRI data can identify MS subtypes
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