Real-world effectiveness of dimethyl fumarate versus fingolimod in a cohort of patients with multiple sclerosis using standardized, quantitative outcome metrics

Background Prior studies suggest comparable effectiveness of dimethyl fumarate (DMF) and fingolimod (FTY) in multiple sclerosis (MS) using relapse, Expanded Disability Status Score (EDSS), and magnetic resonance imaging (MRI) lesion metrics. Objective Compare the real-world effectiveness of DMF versus FTY using quantitative, validated neuroperformance tests, MRI, and serum neurofilament light chain (sNfL) outcomes while controlling for between-group differences. Methods Patients were eligible if on DMF or FTY when first enrolled in the MS Partners Advancing Technology and Health Solutions (MS PATHS) network and had ≥1-year follow-up in MS PATHS. Sensitivity analysis included a subgroup who started DMF/FTY ≤2 years from enrolment. After propensity score weighting, differences in means and in mean 1-year change of neuroperformance and MRI outcomes were compared. sNfL levels were assessed. This was a non-randomized comparison. Results In the overall cohort, no significant differences were observed between DMF ( n = 702) and FTY ( n = 600) in neuroperformance or MRI outcomes including brain volume loss; mean time (SD) since treatment initiation was 1.98 (0.68) years for DMF and 2.02 (0.75) years for FTY. A sensitivity analysis controlling for DMF and FTY treatment duration yielded similar results. Conclusion In this study, DMF and FTY demonstrated similar effects on physical and cognitive neuroperformance and MRI outcomes. Direct comparisons to other fumarates and S1P receptor modulators were not conducted.

The Role of Glial Cells in Regulating Feeding Behavior: Potential Relevance to Anorexia Nervosa

Eating behavior is controlled by hypothalamic circuits in which agouti-related peptide-expressing neurons when activated in the arcuate nucleus, promote food intake while pro-opiomelanocortin-producing neurons promote satiety. The respective neurotransmitters signal to other parts of the hypothalamus such as the paraventricular nucleus as well as several extra-hypothalamic brain regions to orchestrate eating behavior. This complex process of food intake may be influenced by glia cells, in particular astrocytes and microglia. Recent studies showed that GFAP+ astrocyte cell density is reduced in the central nervous system of an experimental anorexia nervosa model. Anorexia nervosa is an eating disorder that causes, among the well-known somatic symptoms, brain volume loss which was associated with neuropsychological deficits while the underlying pathophysiology is unknown. In this review article, we summarize the findings of glia cells in anorexia nervosa animal models and try to deduce which role glia cells might play in the pathophysiology of eating disorders, including anorexia nervosa. A better understanding of glia cell function in the regulation of food intake and eating behavior might lead to the identification of new drug targets.

Natalizumab Induces Changes of Cerebrospinal Fluid Measures in Multiple Sclerosis

Background: There is a lack of knowledge about the evolution of cerebrospinal fluid (CSF) markers in multiple sclerosis (MS) patients undergoing natalizumab treatment. Aim: We aimed to evaluate the effect of natalizumab on basic inflammatory CSF and MRI measures. Methods: Together, 411 patients were screened for eligibility and 93 subjects with ≥2 CSF examinations ≤6 months before and ≥12 months after natalizumab initiation were recruited. The effect of natalizumab on CSF as well as clinical and paraclinical measures was analyzed using adjusted mixed models. Results: Natalizumab induced a decrease in CSF leukocytes (p < 1 × 10−15), CSF protein (p = 0.00007), the albumin quotient (p = 0.007), the IgG quotient (p = 6 × 10−15), the IgM quotient (p = 0.0002), the IgG index (p = 0.0004), the IgM index (p = 0.003) and the number of CSF-restricted oligoclonal bands (OCBs) (p = 0.0005). CSF-restricted OCBs positivity dropped from 94.6% to 86% but 26 patients (28%) had an increased number of OCBs at the follow-up. The baseline to follow-up EDSS and T2-LV were stable; a decrease in the relapse rate was consistent with a decrease in the CSF inflammatory markers and previous knowledge about the effectiveness of natalizumab. The average annualized brain volume loss during the follow-up was −0.50% (IQR = −0.96, −0.16) and was predicted by the baseline IgM index (B = −0.37; p = 0.003). Conclusions: Natalizumab is associated with a reduction of basic CSF inflammatory measures supporting its strong anti-inflammatory properties. The IgM index at the baseline predicted future brain volume loss during the course of natalizumab treatment.

Health Economic Impact of Software-Assisted Brain MRI on Therapeutic Decision-Making and Outcomes of Relapsing-Remitting Multiple Sclerosis Patients—A Microsimulation Study

Aim: To develop a microsimulation model to assess the potential health economic impact of software-assisted MRI in detecting disease activity or progression in relapsing-remitting multiple sclerosis (RRMS) patients. Methods: We develop a simulated decision analytical model based on a hypothetical cohort of RRMS patients to compare a baseline decision-making strategy in which only clinical evolution (relapses and disability progression) factors are used for therapy decisions in MS follow-up, with decision-making strategies involving MRI. In this context, we include comparisons with a visual radiologic assessment of lesion evolution, software-assisted lesion detection, and software-assisted brain volume loss estimation. The model simulates clinical (EDSS transitions, number of relapses) and subclinical (new lesions and brain volume loss) disease progression and activity, modulated by the efficacy profiles of different disease-modifying therapies (DMTs). The simulated decision-making process includes the possibility to escalate from a low efficacy DMT to a high efficacy DMT or to switch between high efficacy DMTs when disease activity is detected. We also consider potential error factors that may occur during decision making, such as incomplete detection of new lesions, or inexact computation of brain volume loss. Finally, differences between strategies in terms of the time spent on treatment while having undetected disease progression/activity, the impact on the patient’s quality of life, and costs associated with health status from a US perspective, are reported. Results: The average time with undetected disease progression while on low efficacy treatment is shortened significantly when using MRI, from around 3 years based on clinical criteria alone, to 2 when adding visual examination of MRI, and down to only 1 year with assistive software. Hence, faster escalation to a high efficacy DMT can be performed when MRI software is added to the radiological reading, which has positive effects in terms of health outcomes. The incremental utility shows average gains of 0.23 to 0.37 QALYs over 10 and 15 years, respectively, when using software-assisted MRI compared to clinical parameters only. Due to long-term health benefits, the average annual costs associated with health status are lower by $1500–$2200 per patient when employing MRI and assistive software. Conclusions: The health economic burden of MS is high. Using assistive MRI software to detect and quantify lesions and/or brain atrophy has a significant impact on the detection of disease activity, treatment decisions, health outcomes, utilities, and costs in patients with MS.

BrainFD: Measuring the Intracranial Brain Volume With Fractal Dimension

A few methods and tools are available for the quantitative measurement of the brain volume targeting mainly brain volume loss. However, several factors, such as the clinical conditions, the time of the day, the type of MRI machine, the brain volume artifacts, the pseudoatrophy, and the variations among the protocols, produce extreme variations leading to misdiagnosis of brain atrophy. While brain white matter loss is a characteristic lesion during neurodegeneration, the main objective of this study was to create a computational tool for high precision measuring structural brain changes using the fractal dimension (FD) definition. The validation of the BrainFD software is based on T1-weighted MRI images from the Open Access Series of Imaging Studies (OASIS)-3 brain database, where each participant has multiple MRI scan sessions. The software is based on the Python and JAVA programming languages with the main functionality of the FD calculation using the box-counting algorithm, for different subjects on the same brain regions, with high accuracy and resolution, offering the ability to compare brain data regions from different subjects and on multiple sessions, creating different imaging profiles based on the Clinical Dementia Rating (CDR) scores of the participants. Two experiments were executed. The first was a cross-sectional study where the data were separated into two CDR classes. In the second experiment, a model on multiple heterogeneous data was trained, and the FD calculation for each participant of the OASIS-3 database through multiple sessions was evaluated. The results suggest that the FD variation efficiently describes the structural complexity of the brain and the related cognitive decline. Additionally, the FD efficiently discriminates the two classes achieving 100% accuracy. It is shown that this classification outperforms the currently existing methods in terms of accuracy and the size of the dataset. Therefore, the FD calculation for identifying intracranial brain volume loss could be applied as a potential low-cost personalized imaging biomarker. Furthermore, the possibilities measuring different brain areas and subregions could give robust evidence of the slightest variations to imaging data obtained from repetitive measurements to Physicians and Radiologists.

Measurement of neurofilaments improves stratification of future disease activity in early multiple sclerosis

Background: The added value of neurofilament light chain levels in serum (sNfL) to the concept of no evidence of disease activity-3 (NEDA-3) has not yet been investigated in detail. Objective: To assess whether combination of sNfL with NEDA-3 status improves identification of patients at higher risk of disease activity during the following year. Methods: We analyzed 369 blood samples from 155 early relapsing-remitting MS patients on interferon beta-1a. We compared disease activity, including the rate of brain volume loss in subgroups defined by NEDA-3 status and high or low sNfL (> 90th or < 90th percentile). Results: In patients with disease activity (EDA-3), those with higher sNFL had higher odds of EDA-3 in the following year than those with low sNFL (86.5% vs 57.9%; OR = 4.25, 95% CI: [2.02, 8.95]; p = 0.0001) and greater whole brain volume loss during the following year (β = −0.36%; 95% CI = [−0.60, −0.13]; p = 0.002). Accordingly, NEDA-3 patients with high sNfL showed numerically higher disease activity (EDA-3) in the following year compared with those with low sNfL (57.1% vs 31.1%). Conclusion: sNfL improves the ability to identify patients at higher risk of future disease activity, beyond their NEDA-3 status. Measurement of sNfL may assist clinicians in decision-making by providing more sensitive prognostic information.

MRI brain volume loss, lesion burden, and clinical outcome in secondary progressive multiple sclerosis

Background: Magnetic resonance imaging (MRI) of brain volume measures are widely used outcomes in secondary progressive multiple sclerosis (SPMS), but it is unclear whether they are associated with physical and cognitive disability. Objective: To investigate the association between MRI outcomes and physical and cognitive disability worsening in people with SPMS. Methods: We used data from ASCEND, a large randomized controlled trial ( n = 889). We investigated the association of change in whole brain and gray matter volume, contrast enhancing lesions, and T2 lesions with significant worsening on the Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk (T25FW), Nine-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT) with logistic regression models. Results: We found no association between MRI measures and EDSS or SDMT worsening. T25FW worsening at 48 and 96 weeks, and NHPT worsening at 96 weeks were associated with cumulative new or newly enlarging T2 lesions at 96 weeks. NHPT worsening at 48 and 96 weeks was associated with normalized brain volume loss at 48 weeks, but not with other MRI outcomes. Conclusion: The association of standard MRI outcomes and disability was noticeably weak and inconsistent over 2 years of follow-up. These MRI outcomes may not be useful surrogates of disability measures in SPMS.

Evolution of Brain Volume Loss Rates in Early Stages of Multiple Sclerosis

ObjectiveTo describe the dynamics of brain volume loss (BVL) at different stages of relapsing-remitting multiple sclerosis (RRMS), to describe the association between BVL and clinical measures, and to investigate an effect of treatment escalation on the rate of BVL.MethodsTogether, 1903 patients predominantly with RRMS from the Avonex-Steroids-Azathioprine cohort (N = 166), the study of early IFN-β1a treatment cohort (N = 180), and the quantitative MRI cohort (N = 1,557) with ≥2 MRI scans and ≥1-year of follow-up were included. Brain MRI scans (N = 7,203) were performed using a single 1.5-T machine. Relationships between age or disease duration and global and tissue-specific BVL rates were analyzed using mixed models.ResultsAge was not associated with the rate of BVL (β = −0.003; Cohen f2 = 0.0005; adjusted p = 0.39). Although disease duration was associated with the rate of BVL, its effect on the BVL rate was minimal (β = −0.012; Cohen f2 = 0.004; adjusted p = 4 × 10−5). Analysis of association between tissue-specific brain volume changes and age (β = −0.019 to −0.011; adjusted p = 0.028–1.00) or disease duration (β = −0.028 to −0.008; adjusted p = 0.16–0.96) confirmed these results. Although increase in the relapse rate (β = 0.10; adjusted p = 9 × 10−9), Expanded Disability Status Scale (EDSS; β = 0.17; adjusted p = 8 × 10−5), and EDSS change (β = 0.15; adjusted p = 2 × 10−5) were associated with accelerated rate of BVL, their effect on the rate of BVL was minimal (all Cohen f2 ≤ 0.007). In 94 patients who escalated therapy, the rate of BVL decreased following treatment escalation by 0.29% (β = −0.29; Cohen f2 = 0.133; p = 5.5 × 10−8).ConclusionsThe rate of BVL is relatively stable throughout the course of RRMS. The accelerated BVL is weakly associated with concurrent higher disease activity, and timely escalation to high-efficacy immunotherapy helps decrease the rate of BVL.