Disease-modifying therapy initiation patterns in multiple sclerosis in three large MS populations.

Background: Treatment guidelines recommend early disease-modifying therapy (DMT) initiation after diagnosis of multiple sclerosis (MS). Multinational comparative studies that assess time to DMT initiation in MS may allow detection of barriers inherent to healthcare systems to explain potential adverse systematic delays in commencing DMTs. Objectives: To investigate and compare the time to first DMT and its association with sociodemographic and clinical variables after MS diagnosis in three large MS registries. Design: This observational study was conducted using data from the German MS Registry (GMSR), the North American Research Committee on MS Registry (NARCOMS, US data only), and the United Kingdom MS Registry (UKMSR, both self- and clinician-reported). Methods: Data from relapsing people with MS (PwMS), with a diagnosis of MS between 2014 and 2019, and available DMT and disability status were pooled using a meta-analytic approach. Results: A total of 5395 PwMS were included in the analysis (GMSR: n = 2658; NARCOMS: n = 447; UKMSR: n = 2290). Kaplan-Meier estimates for the time to first DMT [median months (95% CI)] were 2.0 (1.9-2.0), 3.0 (2-4), and 9.0 (7.7-10.6) for GMSR, NARCOMS, and UKMSR, respectively. Pooled multivariable Cox regression demonstrated shorter time to first DMT for PwMS diagnosed after 2017 [1.65 (1.42-1.92), p < 0.01], and longer time to DMT when a higher-efficacy DMT was selected (0.69 (0.54-0.90), p < 0.0001]. Conclusion: Time to DMT initiation differs across the populations studied, indicating that barriers may exist in early access to DMT, particularly in the United Kingdom. However, a consistent decrease in time to DMT initiation was noted since 2017 across all registries. Further studies are warranted comparing the effects of time to DMT and time to higher-efficacy DMT on long-term outcome.

Vaccination status and self-reported side effects after SARS-CoV-2 vaccination in relation to psychological and clinical variables in patients with multiple sclerosis.

The recent SARS-CoV-2 pandemic and the vaccination campaign posed a challenge to patients with autoimmune disease, such as multiple sclerosis (MS). We aimed for investigating whether psychological/sociodemographic/clinical characteristics of MS patients are associated with SARS-CoV-2 vaccination status and self-reported vaccination side effects (SEs). We have asked patients with MS about their willingness to receive recommended standard vaccinations pre-pandemically since June 2019. Between 10/2021 and 01/2022, we surveyed 193 of these MS patients about their current SARS-CoV-2 vaccination status, their perception of vaccination-related SEs, and reasons for and against SARS-CoV-2 vaccination. 75.6% of the patients declared their willingness to receive standard vaccinations before the pandemic. 84.5%, 78.2%, and 13.0% of the patients had received the first, second, and third SARS-CoV-2 vaccination, respectively, until the follow-up survey. The most common reason for not getting vaccinated against SARS-CoV-2 was concern about possible side effects (82.1%), followed by the belief that the vaccines had not been adequately tested (64.3%). Vaccination-related SEs were reported by 52.8% of the patients. Younger age, higher education, lower degree of disability, relapsing disease course, shorter disease duration, not receiving a disease-modifying therapy and higher anxiety and depression levels were associated with the occurrence of certain vaccination-related SEs. Concerns about novel vaccines are widespread among MS patients and necessitate targeted education of the patients, especially to those with more severe psychopathological symptoms (anxiety or depression) and those who are generally skeptical of vaccination.

Treatment switches of disease-modifying therapies in people with multiple sclerosis: long-term experience from the German MS Registry.

Background: The spectrum of disease-modifying therapies (DMTs) for people with multiple sclerosis (PwMS) has expanded over years, but data on treatment strategies is largely lacking. DMT switches are common clinical practice. Objective: To compare switchers and non-switchers, characterize the first DMT switch and identify reasons and predictors for switching the first DMT. Methods: Data on 2722 PwMS from the German MS Registry were retrospectively analyzed regarding sociodemographic/clinical differences between 1361 switchers (PwMS discontinuing the first DMT) and non-switchers matched according to age, sex, and observation period. Frequencies of first and second DMTs were calculated and switch reasons identified. Predictors for DMT switches were revealed using univariable and multivariable regression models. Results: Switchers and non-switchers differed significantly regarding time to first DMT, education, calendar period of the first DMT start (2014-2017 versus 2018-2021), first DMT class used [mild-to-moderate efficacy (MME) versus high-efficacy (HE) DMT], time on first DMT, and disease activity at first DMT start or cessation/last follow-up. The majority of PwMS started with MME DMTs (77.1%), with the most common being glatiramer acetate, dimethyl/diroximel fumarate, and beta-interferon variants. Switchers changed treatment more often to HE DMTs (39.6%), most commonly sphingosine-1-phosphate receptor modulators, anti-CD20 monoclonal antibodies, and natalizumab. Fewer PwMS switched to MME DMTs (35.9%), with the most common being dimethyl/diroximel fumarate, teriflunomide, or beta-interferon. Among 1045 PwMS with sufficient data (76.8% of 1361 switchers), the most frequent reasons for discontinuing the first DMT were disease activity despite DMT (63.1%), adverse events (17.1%), and patient request (8.3%). Predictors for the first DMT switch were MME DMT as initial treatment [odds ratio (OR) = 2.83 (1.76-4.61), p < 0.001; reference: HE DMT], first DMT initiation between 2014 and 2017 [OR = 11.55 (6.93-19.94), p < 0.001; reference: 2018-2021], and shorter time on first DMT [OR = 0.22 (0.18-0.27), p < 0.001]. Conclusion: The initial use of MME DMTs was among the strongest predictors of DMT discontinuation in a large German retrospective MS cohort, arguing for the need for prospective treatment strategy trials, not only but also on the initial broad use of HE DMTs in PwMS.

Update and Application of a Deep Learning Model for the Prediction of Interactions between Drugs Used by Patients with Multiple Sclerosis.

Patients with multiple sclerosis (MS) often take multiple drugs at the same time to modify the course of disease, alleviate neurological symptoms and manage co-existing conditions. A major consequence for a patient taking different medications is a higher risk of treatment failure and side effects. This is because a drug may alter the pharmacokinetic and/or pharmacodynamic properties of another drug, which is referred to as drug-drug interaction (DDI). We aimed to predict interactions of drugs that are used by patients with MS based on a deep neural network (DNN) using structural information as input. We further aimed to identify potential drug-food interactions (DFIs), which can affect drug efficacy and patient safety as well. We used DeepDDI, a multi-label classification model of specific DDI types, to predict changes in pharmacological effects and/or the risk of adverse drug events when two or more drugs are taken together. The original model with ~34 million trainable parameters was updated using >1 million DDIs recorded in the DrugBank database. Structure data of food components were obtained from the FooDB database. The medication plans of patients with MS (n = 627) were then searched for pairwise interactions between drug and food compounds. The updated DeepDDI model achieved accuracies of 92.2% and 92.1% on the validation and testing sets, respectively. The patients with MS used 312 different small molecule drugs as prescription or over-the-counter medications. In the medication plans, we identified 3748 DDIs in DrugBank and 13,365 DDIs using DeepDDI. At least one DDI was found for most patients (n = 509 or 81.2% based on the DNN model). The predictions revealed that many patients would be at increased risk of bleeding and bradycardic complications due to a potential DDI if they were to start a disease-modifying therapy with cladribine (n = 242 or 38.6%) and fingolimod (n = 279 or 44.5%), respectively. We also obtained numerous potential interactions for Bruton's tyrosine kinase inhibitors that are in clinical development for MS, such as evobrutinib (n = 434 DDIs). Food sources most often related to DFIs were corn (n = 5456 DFIs) and cow's milk (n = 4243 DFIs). We demonstrate that deep learning techniques can exploit chemical structure similarity to accurately predict DDIs and DFIs in patients with MS. Our study specifies drug pairs that potentially interact, suggests mechanisms causing adverse drug effects, informs about whether interacting drugs can be replaced with alternative drugs to avoid critical DDIs and provides dietary recommendations for MS patients who are taking certain drugs.

Polypharmacy in patients with multiple sclerosis and the impact on levels of care and therapy units.

Background: The aim of this study was to examine the societal costs of polypharmacy in patients with multiple sclerosis (MS). We therefore focused on the association between the number of medications on the level of care (LOC), the German classification of the need for care, and the number of therapy sessions (TTU). Methods: In addition to demographic information and medication, 101 MS patients performed the Multiple Sclerosis Health Resource Utilization Survey (MS-HRS). Medications were subdivided into a total number of medications (TD), MS-related medication [MSD, i.e., disease-modifying drugs (DMDs) and symptomatic treatment (SD)], and medication for comorbidities (CDs). Multivariate linear regression models were performed to estimate if the amount of each medication type affects LOC or TTU. Results: Polypharmacy appeared in 54 patients at the time of the survey. The relative risk (RR) of LOC 1 increased significantly by 2.46 (p = 0.001) per TD and by 2.55 (p = 0.004) per MSD, but not per CD (RR 1.44; p = 0.092). The effect of RR on MSD was driven by SD (RR 2.2; p = 0.013) but not DMD (RR 2.6; p = 0.4). RR of MSD remained significant for LOC 2 (1.77; p = 0.009) and LOC 3/4 (1.91; p = 0.015), with a strong trend in RR of SD, but not DMD. TTU increased significantly per MSD (p = 0.012), but not per TD (p = 0.081) and CD (p = 0.724). Conclusion: The number of MSDs is related to the likelihood of a higher level of care and the number of therapy sessions and is therefore a good indication of the extent of the societal costs.

Occurrence and Risk Factors of Relapse Activity after Vaccination against COVID-19 in People with Multiple Sclerosis: 1-Year Follow-Up Results from a Nationwide Longitudinal Observational Study.

Several studies reported post-SARS-CoV-2-vaccination (PV) symptoms. Even people with multiple sclerosis (PwMS) have concerns about disease activity following the SARS-CoV-2 vaccination. We aimed to determine the proportion of PwMS with PV relapses, the PV annualized relapse rate (ARR), the time from vaccination to subsequent relapses, and identify sociodemographic/clinical risk factors for PV relapses. PwMS were surveyed several times at baseline and four follow-ups as part of a longitudinal observational study regarding the safety and tolerability of the SARS-CoV-2 vaccination. The inclusion criteria for this analysis were age ≥18 years, ≥1 SARS-CoV-2 vaccination, and ≥1-year observation period since initial vaccination. Of 2466 PwMS, 13.8% reported PV relapses (mostly after second [N = 147] or booster vaccination [N = 145]) at a median of 8.0 (first/third quantile: 3.55/18.1) weeks PV, with the shortest period following initial vaccination (3.95 weeks). The ARR was 0.153 (95% confidence interval: 0.138-0.168), with a median observation period since initial vaccination of 1.2 years. Risk factors for PV relapses were younger age, female gender, moderate-severe disability levels, concurrent autoimmune diseases, relapsing-remitting MS courses, no DMT, and relapses within the year prior to the first vaccination. Patients' health conditions before/during initial vaccination may play a more important role in PV relapse occurrence than vaccination per se.