Fatigue is associated with reduced quality of life and social participation, and poor employment outcomes. However, most studies examining fatigue are limited by small sample sizes or short follow-up periods.To characterize the natural history of fatigue.The North American Research Committee on Multiple Sclerosis Registry participants with ≥7 years of longitudinal data between 2004 and 2019 and a relapsing disease course were included. A subset of participants enrolled within 5 years of diagnosis was identified. The Fatigue Performance Scale assessed fatigue and ≥1-point increase in Fatigue Performance Scale sustained at the next survey defined fatigue worsening.Of 3057 participants with longitudinal data, 944 were within 5 years of multiple sclerosis diagnosis. Most participants (52%) reported fatigue worsening during follow-up. Median time to fatigue worsening ranged from 3.5 to 5 years at lower levels of index fatigue. Fatigue worsening was associated with lower annual income, increasing disability, lower initial fatigue level, taking injectable disease-modifying therapies and increasing depression levels in the relapsing multiple sclerosis participants.Most multiple sclerosis participants early in their disease suffer from fatigue and at least half reported fatigue worsening over time. Understanding factors associated with fatigue may help to identify populations most at risk of fatigue worsening will be informative for the overall management of patients with multiple sclerosis.
Brain volume loss (BVL) has been identified as a predictor of disability progression in relapsing multiple sclerosis (RMS). As many available disease-modifying treatments (DMTs) have shown an effect on slowing BVL, this is becoming an emerging clinical endpoint in RMS clinical trials.
In the Phase Ill OPTIMUM study, treatment with ponesimod (20 mg) has shown less brain atrophy from baseline to Week 108 compared with teriflunomide (14 mg). Here we model and evaluate Brain Volume Loss (BVL) across randomized clinical trials (RCTs).
To assess clinical and magnetic resonance imaging (MRI) outcomes in RMS patients at 48 weeks of follow-up after short-term interruption and re-initiation of ponesimod treatment.
Background:
Current multiple sclerosis (MS) disease-modifying treatments alter patients' immune system due to different pharmacokinetic/pharmacodynamic profiles. Clinical situations such as pregnancies, infections or live vaccinations may require rapid drug elimination and a fully functioning immune system. Lymphocyte counts return to normal range in >90% of patients within 1 week of stopping ponesimod treatment. It is important to evaluate MS disease activity over time following ponesimod treatment interruption and re-initiation.
Design/Methods:
Patients who completed 108 weeks of ponesimod or teriflunomide treatment in the Phase-3 OPTIMUM study and underwent an accelerated elimination procedure were eligible for the open-label extension (OLE) study and received ponesimod 20mg. Of 567 patients randomized to ponesimod in OPTIMUM, 439 (77.4%) entered the OLE and 239 (42.2%) had ≥48 weeks of follow up. The annualized relapse rate (ARR) and cumulative number of combined-unique-active-lesions (CUALs) following short-term treatment interruption (between OPTIMUM and OLE) and re-initiation (at start of the OLE) were evaluated in 239 patients.
Results:
The mean duration of ponesimod treatment interruption (between the end of OPTIMUM and initiation of OLE) was 17.6 days (range 13–45). The ARR at OLE week 48, and considering treatment interruption and re-initiation, was 0.191 (95% CI:0.140, 0.261). This was numerically lower than the 2-year ARR of 0.234 (95% CI: 0.186, 0.296) with a relative rate reduction (RRR) of 18.4% (RRR: 0.816, 95% CI: 0.595, 1.120). At OLE week 48, patients had 1.73 CUALs/year (95% CI:1.30, 2.31), which was not statistically significantly different from 1.48 CUALs/year (95% CI: 1.19, 1.82) in OPTIMUM.
Conclusions:
Based on clinical and imaging outcomes at 48 weeks following short-term interruption and re-initiation of ponesimod, disease activity remained consistent with that observed prior to interruption. Disclosure: Alexander Keenan has received personal compensation for serving as an employee of Janssen Pharmaceuticals. Alexander Keenan has received stock or an ownership interest from Johnson and Johnson. The institution of Dr. Kappos has received research support from Bayer. The institution of Dr. Kappos has received research support from Biogen. The institution of Dr. Kappos has received research support from Genentech. The institution of Dr. Kappos has received research support from Genzyme. The institution of Dr. Kappos has received research support from Janssen. The institution of Dr. Kappos has received research support from Merck Serono. The institution of Dr. Kappos has received research support from Minoryx. The institution of Dr. Kappos has received research support from Novartis. The institution of Dr. Kappos has received research support from Roche. The institution of Dr. Kappos has received research support from Sanofi. The institution of Dr. Kappos has received research support from Santhera. The institution of Dr. Kappos has received research support from Swiss MS Society, Swiss National Research Foundation, European Union, Roche Research Foundation, Innosuisse. The institution of Dr. Kappos has received research support from Shionogi. The institution of Dr. Kappos has received research support from Japan Tobacco. The institution of Dr. Kappos has received research support from Auriga Vision AG. The institution of Dr. Kappos has received research support from EMD Serono. The institution of Dr. Kappos has received research support from Glaxo Smith Kline. The institution of Dr. Kappos has received research support from Wellmera AG. The institution of Dr. Kappos has received research support from Eli Lilly (Suisse) SA. The institution of Dr. Kappos has received research support from Bristol Myers Squibb. The institution of Dr. Kappos has received research support from Celltrion Inc. Dr. Kappos has received intellectual property interests from a discovery or technology relating to health care. Dr. Ait Tihyaty has received personal compensation for serving as an employee of Janssen. Ms. Gandhi has received personal compensation for serving as an employee of Janssen Pharmaceuticals. Ms. Gandhi has received personal compensation for serving as an employee of Pfizer. An immediate family member of Ms. Gandhi has received personal compensation for serving as an employee of AstraZeneca LLC. Ms. Gandhi has stock in Janssen Pharmaceuticals. An immediate family member of Ms. Gandhi has stock in AstraZeneca LLC. Dr. Turkoz has received personal compensation for serving as an employee of Janssen R&D. Dr. Turkoz has received stock or an ownership interest from J&J. Dr. Wong has received personal compensation for serving as an employee of Janssen Research & Development. Dr. Wong has received personal compensation for serving as an employee of Biogen. Dr. Wong has stock in Biogen. Dr. Sidorenko has received personal compensation for serving as an employee of Actelion Pharmaceuticals Ltd, a Janssen Pharmaceutical company of Johnson&Johnson. Dr. Sidorenko has stock in Johnson&Johnson. Dr. Lublin has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Roche/Genentech. Dr. Lublin has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Biogen. Dr. Lublin has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Neurogene. Dr. Lublin has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Novartis. Dr. Lublin has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Medimmune/Viela Bio/Horizon. Dr. Lublin has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Receptos/Celgene/BMS. Dr. Lublin has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Immunic. Dr. Lublin has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Labcorp. Dr. Lublin has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Neuralight. Dr. Lublin has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Entelexo. Dr. Lublin has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Janssen. Dr. Lublin has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Avotres. Dr. Lublin has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Sanofi. Dr. Lublin has received personal compensation in the range of $5,000-$9,999 for serving on a Speakers Bureau for Biogen. Dr. Lublin has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for EMD Serono. Dr. Lublin has received personal compensation in the range of $100,000-$499,999 for serving as an Expert Witness for Multiple entities. Dr. Lublin has stock in Avotres. Dr. Lublin has stock in Neuralight. The institution of Dr. Lublin has received research support from Brainstorm. The institution of Dr. Lublin has received research support from biogen. The institution of Dr. Lublin has received research support from NIH.
Abstract Background Brain volume loss (BVL) has been identified as a predictor of disability progression in relapsing multiple sclerosis (RMS). As many available disease-modifying treatments (DMTs) have shown an effect on slowing BVL, this is becoming an emerging clinical endpoint in RMS clinical trials. Methods In this study, a systematic literature review was conducted to identify BVL results from randomized controlled trials of DMTs in RMS. Indirect treatment comparisons (ITCs) were conducted to estimate the relative efficacy of DMTs on BVL using two approaches: a model-based meta-analysis (MBMA) with adjustment for measurement timepoint and DMT dosage, and a network meta-analysis (NMA). Results In the MBMA, DMTs associated with significantly reduced BVL versus placebo at two years included fingolimod (mean difference [MD] = 0.25; 95% confidence interval [CI] = 0.15–0.36), ozanimod (MD = 0.26; 95% CI = 0.12–0.41), teriflunomide (MD = 0.38; 95% CI = 0.20–0.55), alemtuzumab (MD = 0.38; 95% CI = 0.10–0.67) and ponesimod (MD = 0.71; 95% CI = 0.48–0.95), whereas interferons and natalizumab performed the most poorly. The results of NMA analysis were generally comparable with those of the MBMA. Conclusions Limitations of these analyses included the potential for confounding due to pseudoatrophy, and a lack of long-term clinical data for BVL. Our findings suggest that important differences in BVL may exist between DMTs. Continued investigation of BVL in studies of RMS is important to complement traditional disability endpoints, and to foster a better understanding of the mechanisms by which DMTs can slow BVL.
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