Understanding multiple sclerosis as a disease spectrum: above and below the clinical threshold.

PURPOSE OF REVIEW: Research in multiple sclerosis (MS) has long been predicated on clinical groupings that do not reflect the underlying biologic heterogeneity apparent within patient populations. This review explicates the various levels of explanation through which the spectrum of disease is described and investigated both above and below the clinical threshold of detection, as framed by the topographical model of MS, to help advance a cogent mechanistic framework. RECENT FINDINGS: Contemporary evidence has amended the view of MS as consisting of sequential disease phases in favor of a spectrum of disease with an admixture of interdependent and dynamic pathobiological axes driving tissue injury and progression. Recent studies have shown the presence of acute and compartmentalized inflammation and mechanisms of neurodegeneration beginning early and evolving throughout the disease continuum. Still, the gap between the understanding of immunopathologic processes in MS and the tools used to measure relevant molecular, laboratory, radiologic, and clinical metrics needs attention to enable better prognostication of disease and monitoring for changes along specific pathologic axes and variable treatment outcomes. SUMMARY: Aligning on a consistently-applied mechanistic framework at distinct levels of explanation will enable greater precision across bench and clinical research, and inform discourse on drivers of disability progression and delivery of care for individuals with MS.

Treatment transitions in neuromyelitis optica spectrum disorder increase risk for disease advancement.

BACKGROUND: People with neuromyelitis optica spectrum disorder (PwNMOSD) commonly switch between disease modifying therapies, yet the consequence of transitions remains unknown. We aimed to understand if treatment transitions due to medical, non-medical, and tolerability reasons were related to disease progression. METHODS: A retrospective study of medical records for PwNMOSD was performed between 2008 and 2022. A comprehensive clinical timeline was created for each person including details related to treatment history and associated clinical and radiological outcomes (i.e., hospital admission, relapses, and MRI advancement). If a transition occurred, the reason for the switch was categorized as being due to medical, non-medical, or tolerability issues. A proportional hazards model was created, and the assumptions were tested based on weighted residuals. RESULTS: The cohort included 164 aquaporin-4 IgG positive NMOSD subjects with 89 (79 female; median disease duration (range) = 10.1 years (y) (1.7-32.8)) people switching therapies at least once (once: 42; twice: 26; three times: 12; four times: 6; 5 or more times: 3). A similar amount of higher efficacy therapies was used by PwNMOSD that switched due to a non-medical/tolerability or a medical-related reason. The results of the recurrent event survival analysis revealed that after an initial transition due to non-medical/tolerability reasons, the risk of a hospital admission, relapse, and MRI advancement decreases by 40.3 % (p = 0.005), 53.1 % (p = 0.002), and 65.9 % (p = 0.005), respectively. However, with each additional discontinuation due to non-medical/tolerability reasons, the risk of hospitalization increased by 25.2 % (p = 0.0003) and risk for MRI advancement increased by 41.9 % (p = 0.03). For transitions due to medical reasons, a significant increased risk of MRI advancement by 32.2 % (p = 0.005) for the first switch was identified with no associated observed risk with each additional discontinuation (p = 0.33). Within the first six months after stopping a medication due to non-medical/tolerability reasons, the rate of starting a new medication was less (p<0.0001) when compared to a discontinuation due to a medical-related event. CONCLUSIONS: The risk associated with the time course of treatment transitions for people with NMOSD may assist in transforming the way healthcare providers bridge the gap between therapies and the approach to the timing of a switch. These data highlight additional factors that may be equatable to the efficacy of prescribed treatments in the prevention of acute neurological events.

Hiding in plain sight: The magnitude of unused disease modifying therapies in multiple sclerosis and strategies for reducing the economic burden of care.

BACKGROUND: The rising costs associated with multiple sclerosis (MS) disease modifying therapies (DMTs) creates challenges for patients and the healthcare system in the United States (U.S.). Within a specialty medicine waste project, we quantified the magnitude of unused medications and corresponding value, the primary factors driving treatment switches, and explored reasons for discontinuations by race and ethnicity. METHODS: Over one calendar year, MS DMTs were recovered from new and existing patients from a single neuroimmunologist within a tertiary MS care center. Baseline demographic and clinical information, including reasons for medication discontinuation or transitions were captured. Patients were stratified into three treatment transition categories: (i) non-medical, (ii) medical, or (iii) tolerability reasons. Cause-specific Cox proportional hazard functions were fit for possible causes for treatment changes. RESULTS: A total of 422 patients (female: 73.2%, median age at diagnosis: 32.9 years (y)) comprised of 86.3% Whites, 11.6% Black or African Americans, 1.4% Asians, and 0.7% Native Americans were included, representing 23% of patients evaluated within 2018, with a mean disease duration of 12.8 years (y) (standard deviation (SD): 8.2) and treatment duration of 2.9y (3.4). Women were more likely to switch due to injection fatigue or desire for an oral DMT when compared to men (95% CI [0.26, 0.78], p = 0.01). Being Black or African American people with MS increased the hazard of switching treatment due to injection fatigue and desire for an oral medication relative to White patients with MS by 91% (95% CI [1.07, 3.42], p = 0.03) and switching to a new DMT based on the subjective report of a perceived lack of efficacy was 221% greater (95% CI [1.04, 4.70], p = 0.04), but not in relation to side effects, being 50% less likely to switch (95% CI [0.28, 0.90], p = 0.02). In the passive recruitment phase over a single calendar year, DMTs with a retail value of $5.2 million (Average Wholesale Price (AWP)) were recovered. In the 1-month active recruitment phase within the same year involving 49 people with MS, unused MS DMTs of $1.1 million (AWP) were acquired. Of the 471 patients studied, 56.2% reported transitions in DMTs for reasons other than adequate disease control and tolerability at one point in their treatment history, underscoring the need for individualized therapy selections that enhance persistence and increase the likelihood of reducing further neurological disability. CONCLUSION: The magnitude of unused and wasted MS DMTs is staggering and these findings allude to a larger, more pervasive problem within the healthcare system with financial resources being applied to therapies that go unused.

The topographical model of MS: Empirical evaluation of the recapitulation hypothesis.

OBJECTIVE: Using the topographical model of multiple sclerosis (MS) to evaluate a longitudinal cohort we (1) test the recapitulation hypothesis, positing that patients' "disease topography" predicts the clinical pattern of disability accumulation; and (2) identify leading indicators of progression. METHODS: 10 patients who transitioned from relapsing-remitting MS to secondary progressive MS (SPMS) were evaluated. Neurologic exams were analyzed from relapses, at time of SPMS diagnosis, and most recent visit. Functional systems (FS), location/laterality, and recovery were recorded. The pyramidal/motor system was the target FS assessing symptom laterality and severity at relapse and SPMS time-points. Each patient's clinical course was mapped using the topographical model software. RESULTS: Cohort was 80% female, age 31.6 ± 8.6 years at diagnosis, followed average 23.8 ± 8.8 years, mean 3.1 relapses before SPMS. 83.3 ± 0.2% of relapse symptoms were present at transition to SPMS, increasing to 91.0 ± 0.2% at most recent visit. This demonstrates concordance between the topographical distribution of relapse symptoms and deficits from subsequent progression. In the topographical model, progression became apparent 7.75 years earlier than SPMS was diagnosed in practice. CONCLUSIONS: We demonstrate the model's utility in depicting patients' disease topography as the loci of clinical progression. This could allow for earlier recognition of progressive disease by identifying leading indicators of progression.

The topographical model of multiple sclerosis: A dynamic visualization of disease course.

Relapses and progression contribute to multiple sclerosis (MS) disease course, but neither the relationship between them nor the spectrum of clinical heterogeneity has been fully characterized. A hypothesis-driven, biologically informed model could build on the clinical phenotypes to encompass the dynamic admixture of factors underlying MS disease course. In this medical hypothesis, we put forth a dynamic model of MS disease course that incorporates localization and other drivers of disability to propose a clinical manifestation framework that visualizes MS in a clinically individualized way. The topographical model encapsulates 5 factors (localization of relapses and causative lesions; relapse frequency, severity, and recovery; and progression rate), visualized utilizing dynamic 3-dimensional renderings. The central hypothesis is that, like symptom recrudescence in Uhthoff phenomenon and pseudoexacerbations, progression clinically recapitulates prior relapse symptoms and unmasks previously silent lesions, incrementally revealing underlying lesion topography. The model uses real-time simulation software to depict disease course archetypes and illuminate several well-described but poorly reconciled phenomena including the clinical/MRI paradox and prognostic significance of lesion location and burden on disease outcomes. Utilization of this model could allow for earlier and more clinically precise identification of progressive MS and predictive implications can be empirically tested.