Objective
This study was undertaken to assess the impact of immunosuppressive and immunomodulatory therapies on the severity of coronavirus disease 2019 (COVID‐19) in people with multiple sclerosis (PwMS).
Methods
We retrospectively collected data of PwMS with suspected or confirmed COVID‐19. All the patients had complete follow‐up to death or recovery. Severe COVID‐19 was defined by a 3‐level variable: mild disease not requiring hospitalization versus pneumonia or hospitalization versus intensive care unit (ICU) admission or death. We evaluated baseline characteristics and MS therapies associated with severe COVID‐19 by multivariate and propensity score (PS)‐weighted ordinal logistic models. Sensitivity analyses were run to confirm the results.
Results
Of 844 PwMS with suspected (n = 565) or confirmed (n = 279) COVID‐19, 13 (1.54%) died; 11 of them were in a progressive MS phase, and 8 were without any therapy. Thirty‐eight (4.5%) were admitted to an ICU; 99 (11.7%) had radiologically documented pneumonia; 96 (11.4%) were hospitalized.
After adjusting for region, age, sex, progressive MS course, Expanded Disability Status Scale, disease duration, body mass index, comorbidities, and recent methylprednisolone use, therapy with an anti‐CD20 agent (ocrelizumab or rituximab) was significantly associated (odds ratio [OR] = 2.37, 95% confidence interval [CI] = 1.18–4.74, p = 0.015) with increased risk of severe COVID‐19. Recent use (<1 month) of methylprednisolone was also associated with a worse outcome (OR = 5.24, 95% CI = 2.20–12.53, p = 0.001). Results were confirmed by the PS‐weighted analysis and by all the sensitivity analyses.
Interpretation
This study showed an acceptable level of safety of therapies with a broad array of mechanisms of action. However, some specific elements of risk emerged. These will need to be considered while the COVID‐19 pandemic persists. ANN NEUROL 2021;89:780–789
We validated MRI lesion load, OCB and age at CIS as the strongest independent predictors of conversion to CDMS in this multicentre setting. A role for vitamin D is suggested but requires further investigation.
We provide evidence of long-term treatment benefit in a large registry cohort, and provide evidence of long-term protective effects of pregnancy against disability accrual. We demonstrate that high annualized relapse rate, particularly on-treatment relapse, is an indicator of poor prognosis. Ann Neurol 2016;80:89-100.
Results confirm a favourable effect on relapses as pregnancy proceeds, and an early postpartum peak. Pre-conception DMT exposure and low ARR were independently protective against postpartum relapse. This novel finding could provide clinicians with a strategy to minimise postpartum relapse risk in women with MS planning pregnancy.
The complexity of multiple sclerosis (MS) treatment means that doctors and decision-makers need the best available evidence to make the best decisions for patient care. Randomized controlled trials (RCTs) are accepted as the gold standard for assessing the efficacy and safety of any new drug, but conclusions of these trials do not always aid in daily decision-making processes. Indeed, RCTs are usually conducted in ideal conditions, so can measure efficacy only in restricted and unrepresentative populations. In the past decade, a growing number of MS databases and registries have started to produce long-term outcome data from large cohorts of patients with MS treated with disease-modifying therapies in real-world settings. Such observational studies are addressing issues that are otherwise difficult or impossible to study. In this Review, we focus on the most recently published observational studies designed to identify predictors of poor outcome and treatment response or failure, and to evaluate the relative and long-term effectiveness of currently used MS treatments. We also outline the statistical approaches that are most commonly used to reduce bias and limitations in these studies, and the challenges associated with the use of 'big MS data' to facilitate the implementation of personalized medicine in MS.
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