Relapses add to permanent disability in relapsing multiple sclerosis patients

Proteomic profile of extracellular vesicles from plasma and CSF of multiple sclerosis patients reveals disease activity-associated EAAT2

BACKGROUND AND OBJECTIVES

There is an urgent need to discover blood-based biomarkers of multiple sclerosis (MS) to better define the underlying biology of relapses and monitor disease progression. The main goal of this study is to search for candidate biomarkers of MS relapses associated with circulating extracellular vesicles (EVs), an emerging tool for biomarker discovery.

METHODS

EVs, purified from unpaired plasma and CSF samples of RRMS patients by size-exclusion chromatography (SEC), underwent proteomic analysis to discover novel biomarkers associated with MS relapses. The candidate biomarkers of disease activity were detected by comparison approach between plasma- and CSF-EV proteomes associated with relapses. Among them, a selected potential biomarker was evaluated in a cohort of MS patients, using a novel and highly reproducible flow cytometry-based approach in order to detect low abundant EV subsets in a complex body fluid such as plasma.

RESULTS

The proteomic profiles of both SEC-purified plasma EVs (from 6 patients in relapse and 5 patients in remission) and SEC-purified CSF EVs (from 4 patients in relapse and 3 patients in remission) revealed a set of proteins associated with MS relapses significant enriched in the synaptic transmission pathway. Among common proteins, excitatory amino-acid transporter 2, EAAT2, responsible for the majority of the glutamate uptake in CNS, was worthy of further investigation. By screening plasma samples from 110 MS patients, we found a significant association of plasma EV-carried EAAT2 protein (EV-EAAT2) with MS relapses, regardless of disease-modifying therapies. This finding was confirmed by investigating the presence of EV-EAAT2 in plasma samples collected longitudinally from 10 RRMS patients, during relapse and remission. Moreover, plasma EV-EAAT2 levels correlated positively with Expanded Disability Status Scale (EDSS) score in remitting MS patients but showed a negative correlation with age in patients with secondary progressive (SPMS).

CONCLUSION

Our results emphaticize the usefulness of plasma EVs as a source of accessible biomarkers to remotely analyse the CNS status. Plasma EV-EAAT2 showed to be a promising biomarker for MS relapses. Further studies are required to assess the clinical relevance of this biomarker also for disability progression independent of relapse activity and transition from RRMS towards SPMS.

A comparison of natalizumab and ocrelizumab on disease progression in multiple sclerosis

OBJECTIVE

No direct comparisons of the effect of natalizumab and ocrelizumab on progression independent of relapse activity (PIRA) and relapse-associated worsening (RAW) events are currently available. We aimed to compare the risk of achieving first 6 months confirmed PIRA and RAW events and irreversible Expanded Disability Status Scale (EDSS) 4.0 and 6.0 in a cohort of naïve patients treated with natalizumab or ocrelizumab from the Italian Multiple Sclerosis Register.

METHODS

Patients with a first visit within 1 year from onset, treated with natalizumab or ocrelizumab, and ≥3 visits were extracted. Pairwise propensity score-matched analyses were performed. Risk of reaching the first PIRA, RAW, and EDSS 4.0 and 6.0 events were estimated using multivariable Cox proportional hazards models. Kaplan-Meier curves were used to show cumulative probabilities of reaching outcomes.

RESULTS

In total, 770 subjects were included (natalizumab = 568; ocrelizumab = 212) and the propensity score-matching retrieved 195 pairs. No RAW events were found in natalizumab group and only 1 was reported in ocrelizumab group. A first PIRA event was reached by 23 natalizumab and 25 ocrelizumab exposed patients; 7 natalizumab- and 10 ocrelizumab-treated patients obtained an irreversible EDSS 4.0, while 13 natalizumab- and 15 ocrelizumab-treated patients reached an irreversible EDSS 6.0. No differences between the two groups were found in the risk (HR, 95%CI) of reaching a first PIRA (1.04, 0.59-1.84; p = 0.88) event, an irreversible EDSS 4.0 (1.23, 0.57-2.66; p = 0.60) and 6.0 (0.93, 0.32-2.68; p = 0.89).

INTERPRETATION

Both medications strongly suppress RAW events and, in the short term, the risk of achieving PIRA events, EDSS 4.0 and 6.0 milestones is not significantly different.

Regression Analyses and Their Particularities in Observational Studies—Part 32 of a Series on Evaluation of Scientific Publications

BACKGROUND

Regression analysis is a standard method in medical research. It is often not clear, however, how the individual components of regression models are to be understood and interpreted. In this article, we provide an overview of this type of analysis and discuss its special features when used in observational studies.

METHODS

Based on a selective literature review, the individual components of a regression model for differently scaled outcome variables (metric: linear regression; binary: logistic regression; time to event: Cox regression; count variable: Poisson or negative binomial regression) are explained, and their interpretation is illustrated with respect to a study on multiple sclerosis. The prerequisites for the use of each of these models, their applications, and their limitations are described in detail.

RESULTS

Regression analyses are used to quantify the relation between several variables and the outcome variable. In randomized clinical trials, this flexible statistical analysis method is usually lean and prespecified. In observational studies, where there is a need to control for potential confounders, researchers with knowledge of the topic in question must collaborate with experts in statistical modeling to ensure high model quality and avoid errors. Causal diagrams are an increasingly important basis for evaluation. They should be constructed in collaboration and should differentiate between confounders, mediators, and colliders.

CONCLUSION

Researchers need a basic understanding of regression models so that these models will be well defined and their findings will be fully reported and correctly interpreted.

The Impact of Insurance Restrictions in Newly Diagnosed Individuals With Multiple Sclerosis

BACKGROUND

The medical system in the United States has been riddled with insurance restrictions used by insurance companies to limit health care costs. The effects of insurance restrictions on patients receiving disease-modifying therapies for multiple sclerosis (MS) have not been specifically studied.

METHODS

A retrospective cross-sectional study of 52 individuals recently diagnosed with MS at a tertiary neurology clinic was conducted to measure the association between prior authorization (PA) duration and other variables of interest. The Cox proportional hazards model was used to determine likelihood of approval. Further analysis included multivariable logistic regression to assess the influence of variables of interest on the initial decision from the insurance company and the effect of the PA on disease activity.

RESULTS

Of 52 PAs, 50% were initially denied. An initial denial decreased the likelihood of approval by 98% (HR, 0.02; 95% CI, <0.01-0.09; P < .001). The odds of denial for oral medications (odds ratio [OR], 4.91; 95% CI, 1.33-21.52; P = .02) and infusions (OR, 8.35; 95% CI, 1.10-88.77; P = .05) were significantly higher than for injections. Medicaid had higher odds of denial compared with commercial insurance (OR, 4.51; 95% CI, 1.13-22.01; P = .04). An initial denial by insurance significantly increased the likelihood of disease activity (OR, 6.18; 95% CI, 1.33-44.86; P = .03).

CONCLUSIONS

Insurance restrictions delay necessary treatments, increase the likelihood of disease activity, and rarely change the approved disease-modifying therapy. Reducing PAs may lead to improved outcomes for patients with MS.

Mortality of multiple sclerosis in Iceland population-based mortality of MS in incidence and prevalence cohorts

Introduction

Mortality is an important feature of the natural history of multiple sclerosis (MS). We report the mortality of all individuals with MS in Iceland, identified in a nationwide population-based study.

Patients and Methods

The results are based on a prevalence cohort and an incidence cohort. The prevalence cohort consisted of all patients with MS (n = 526) living in Iceland on the 31 December 2007. The incidence cohort consisted of all residents of Iceland (n = 222) diagnosed with MS during 2002 to 2007. Mortality was determined by following both the incidence cohort (from diagnosis) and the prevalence cohort (from the prevalence day) until death or 31 December 2020. The mortality, associated with MS, was compared with that expected in the Icelandic population (standardized mortality ratio (SMR)).

Results

(a) Prevalence cohort (n = 526). The mean follow up was 12.0 years (range 0.3-13.0). The SMR was 1.6 (95% confidence interval (CI) 1.3-2.0). (b) Incidence cohort (n = 222). The mean follow up was 15.4 years (range 3.7-18.5). The SMR was 1.2 (95% CI 0.6-2.2).

Conclusion

During the follow-up period, there was a substantial increase in mortality among the patients with MS, compared with the general population. There was no increase in mortality among the incidence cohort, when followed for up to 18.5 years following diagnosis.

OUP accepted manuscript

Patients with multiple sclerosis acquire disability either through relapse-associated worsening (RAW) or progression independent of relapse activity (PIRA). This study addresses the relative contribution of relapses to disability worsening over the course of the disease, how early progression begins and the extent to which multiple sclerosis therapies delay disability accumulation.

Using the Novartis-Oxford multiple sclerosis (NO.MS) data pool spanning all multiple sclerosis phenotypes and paediatric multiple sclerosis, we evaluated ∼200 000 Expanded Disability Status Scale (EDSS) transitions from >27 000 patients with ≤15 years follow-up. We analysed three datasets: (i) A full analysis dataset containing all observational and randomized controlled clinical trials in which disability and relapses were assessed (n = 27 328); (ii) all phase 3 clinical trials (n = 8346); and (iii) all placebo-controlled phase 3 clinical trials (n = 4970). We determined the relative importance of RAW and PIRA, investigated the role of relapses on all-cause disability worsening using Andersen-Gill models and observed the impact of the mechanism of worsening and disease-modifying therapies on the time to reach milestone disability levels using time continuous Markov models.

PIRA started early in the disease process, occurred in all phenotypes and became the principal driver of disability accumulation in the progressive phase of the disease. Relapses significantly increased the hazard of all-cause disability worsening events; following a year in which relapses occurred (versus a year without relapses), the hazard increased by 31–48% (all P < 0.001). Pre-existing disability and older age were the principal risk factors for incomplete relapse recovery. For placebo-treated patients with minimal disability (EDSS 1), it took 8.95 years until increased limitation in walking ability (EDSS 4) and 18.48 years to require walking assistance (EDSS 6). Treating patients with disease-modifying therapies delayed these times significantly by 3.51 years (95% confidence limit: 3.19, 3.96) and 3.09 years (2.60, 3.72), respectively. In patients with relapsing-remitting multiple sclerosis, those who worsened exclusively due to RAW events took a similar length of time to reach milestone EDSS values compared with those with PIRA events; the fastest transitions were observed in patients with PIRA and superimposed relapses.

Our data confirm that relapses contribute to the accumulation of disability, primarily early in multiple sclerosis. PIRA begins in relapsing-remitting multiple sclerosis and becomes the dominant driver of disability accumulation as the disease evolves. Pre-existing disability and older age are the principal risk factors for further disability accumulation. The use of disease-modifying therapies delays disability accrual by years, with the potential to gain time being highest in the earliest stages of multiple sclerosis.