COVID-19 in Multiple Sclerosis: Clinically reported outcomes from the UK Multiple Sclerosis Register.

BACKGROUND: In March 2020, the United Kingdom Multiple Sclerosis Register (UKMSR) established an electronic case return form, designed collaboratively by MS neurologists, to record data about COVID-19 infections in people with MS (pwMS). OBJECTIVES: Examine how hospital admission and mortality are affected by disability, age and disease modifying treatments (DMTs) in people with Multiple Sclerosis with COVID-19. METHODS: Anonymised data were submitted by clinical teams. Regression models were tested for predictors of hospitalisation and mortality outcomes. Separate analyzes compared the first and second 'waves' of the pandemic. RESULTS: Univariable analysis found hospitalisation and mortality were associated with increasing age, male gender, comorbidities, severe disability, and progressive MS; severe disability showed the highest magnitude of association. Being on a DMT was associated with a small, lower risk. Multivariable analysis found only age and male gender were significant. Post hoc analysis demonstrated that factors were significant for hospitalisation but not mortality. In the second wave, hospitalisation and mortality were lower. Separate models of the first and second wave using age and gender found they had a more important role in the second wave. CONCLUSIONS: Features associated with poor outcome in COVID-19 are similar to other populations and being on a DMT was not found to be associated with adverse outcomes, consistent with smaller studies. Once in hospital, no factors were predictive of mortality. Reassuringly, mortality appears lower in the second wave.

Validating the portal population of the United Kingdom Multiple Sclerosis Register.

The UK Multiple Sclerosis Register (UKMSR) is a large cohort study designed to capture 'real world' information about living with multiple sclerosis (MS) in the UK from diverse sources. The primary source of data is directly from people with Multiple Sclerosis (pwMS) captured by longitudinal questionnaires via an internet portal. This population's diagnosis of MS is self-reported and therefore unverified. The second data source is clinical data which is captured from MS Specialist Treatment centres across the UK. This includes a clinically confirmed diagnosis of MS (by Macdonald criteria) for consented patients. A proportion of the internet population have also been consented at their hospital making comparisons possible. This dataset is called the 'linked dataset'. The purpose of this paper is to examine the characteristics of the three datasets: the self-reported portal data, clinical data and linked data, in order to assess the validity of the self-reported portal data. The internet (n = 11,021) and clinical (n = 3,003) populations were studied for key shared characteristics. We found them to be closely matched for mean age at diagnosis (clinical = 37.39, portal = 39.28) and gender ratio (female %, portal = 73.1, clinical = 75.2). The Two Sample Kolmogorov-Smirnov test was for the continuous variables to examine is they were drawn from the same distribution. The null hypothesis was rejected only for age at diagnosis (D = 0.078, p < 0.01). The populations therefore, were drawn from different distributions, as there are more patients with relapsing disease in the clinical cohort. In all other analyses performed, the populations were shown to be drawn from the same distribution. Our analysis has shown that the UKMSR portal population is highly analogous to the entirely clinical (validated) population. This supports the validity of the self-reported diagnosis and therefore that the portal population can be utilised as a viable and valid cohort of people with Multiple Sclerosis for study.