Effect of siponimod on lymphocyte subsets in active secondary progressive multiple sclerosis and clinical implications.

BACKGROUND: Circulating immune cells play a pathogenic role in multiple sclerosis (MS). However, the role of specific lymphocyte subpopulations is not unveiled yet, especially in progressive stages. We aimed to investigate lymphocyte changes during siponimod treatment in active secondary progressive MS (aSPMS) and their associations with clinical outcomes. METHODS: We enrolled 46 aSPMS patients starting on siponimod treatment with at least 6 months of follow-up and two visits within the scheduled timeframes and 14 sex- and age-matched healthy controls (HCs). Clinical and laboratory data were collected retrospectively at baseline, 3rd, 6th, 12th, and 24th month for MS patients, and at baseline for HCs. RESULTS: At baseline SPMS patients presented with increased naïve regulatory T lymphocytes (p = 0.02) vs. HCs. Over time, SPMS patients showed decreased T CD4+ (coeff. range = -24/-17, 95% CI range = -31.60 to -10.40), B lymphocyte (coeff. range = -3.77/-2.54, 95% CI range = -6.02 to -0.35), memory regulatory B cells (coeff. range = -0.78/-0.57, 95% CI range = -1.24 to -0.17) and CD4/CD8 ratio (coeff. range = -4.44/-0.67, 95% CI range = -1.61 to -0.17) from month 3 thereafter vs. baseline, and reduced CD3+CD20+ lymphocytes from month 12 thereafter (coeff. range = -0.32/-0.24, 95% CI range = -0.59 to -0.03). Patients not experiencing disability progression while on siponimod treatment showed B lymphocyte reduction from month 3 (coeff. range = -4.23/-2.32, 95% CI range = -7.53 to -0.15) and CD3+CD20+ lymphocyte reduction from month 12 (coeff. range = -0.32/-0.24, 95% CI range = -0.59 to -0.03) vs. patients experiencing progression. CONCLUSIONS: Patients treated with siponimod showed a T and B lymphocyte reduction, especially CD4+, CD3+CD20+ and naïve regulatory T cells and memory regulatory B cells. Disability progression while on siponimod treatment was associated with a less pronounced effect on B and CD3+CD20+ lymphocytes.

Switching to ozanimod as a strategy to adjust fingolimod-related lymphopenia.

INTRODUCTION: Fingolimod is a disease-modifying therapy for multiple sclerosis (MS) that modulates sphingosine 1-phospate receptors, impeding the egress of lymphocytes from lymphnodes and thus causing lymphopenia. Severe lymphopenia should lead to fingolimod discontinuation. We aim to evaluate whether switching from fingolimod to ozanimod can adjust fingolimod-related lymphopenia while maintaining clinical efficacy. METHODS: In this real-world observational study, we included 18 people with MS (47.7 ± 7.6 years of age, 77.8 % of women, 13.9 ± 6.9 years of disease duration, median EDSS 3.0) at the time of fingolimod discontinuation due to lymphopenia. We collected laboratory (lymphocyte absolute count on the same hematological counter) and clinical variables at fingolimod discontinuation, at ozanimod prescription, and 6 months after ozanimod prescription. RESULTS: From 13 cases of grade 3 and 4 lymphopenia at the time of fingolimod discontinuation, we observed only 2 cases of grade 3 and no cases of grade 4 lymphopenia after 6 months of ozanimod treatment. On paired t-tests, absolute lymphocyte count at fingolimod discontinuation were lower than ozanimod prescription (p<0.001), and after 6 months (p<0.001). We observed no clinical changes. DISCUSSION: People with MS who have severe fingolimod-related lymphopenia and are clinically stable, can exhibit increased absolute lymphocyte counts when switched to ozanimod, while preserving clinical stability.

Google Maps Timeline: An open-access digital tool to monitor walking abilities in people with multiple sclerosis.

Introduction: Gait impairment is common in multiple sclerosis (MS), but difficult to evaluate in clinical practice. In this proof-of-concept observational study, we compared walking ability recorded by Google Maps Timeline to conventional clinical measures in people with MS. Methods: We used open-access Google Maps Timeline to record the total number of days with walking activity, walking distance, walking time, and walking speed. Each Google Maps Timeline variable was included in a different stepwise linear regression model including all conventional clinical variables. Results: We included nine people with MS (age 43.1 ± 6.6 years; females 55.6%; disease duration 12.7 ± 3.1 years; median Expanded Disability Status Scale 3.0 (range 1.0-5.5)). Higher percentage of days with recorded walking was associated with lower Fatigue Severity Scale (p = 0.01), and higher MS Walking Scale (p = 0.04). Longer average daily walking distance was associated with shorter Timed-25 Foot Walking Test (p = 0.02), lower Expanded Disability Status Scale (p = 0.01), and higher Euro-Quality of Life (p = 0.04). Longer average daily walking time was associated with shorter Timed-25 Foot Walking Test (p = 0.03). Higher walking speed was associated with lower Fatigue Severity Scale (p = 0.04). Conclusion: Google Maps Timeline parameters provide actual estimates of daily walking activities in MS.

Epidemiology of multiple sclerosis in the Campania Region (Italy): Derivation and validation of an algorithm to calculate the 2015-2020 incidence.

OBJECTIVE: We aim to validate an algorithm based on routinely-collected healthcare data to detect incidence of multiple sclerosis (MS) in the Campania Region (South Italy) and to explore its spatial and temporal variations. METHODS: We included individuals resident in the Campania Region who had at least one MS record in administrative datasets (drug prescriptions, hospital discharge, outpatients), from 2015 to 2020. We merged administrative to the clinical datasets to ascertain the actual date of diagnosis, and validated the minimum interval from our study baseline (Jan 1, 2015) to first MS records in administrative datasets to detect incident cases. We used Bayesian approach to explore geographical distribution, also including deprivation index as a covariate in the estimation model. We used the capture-recapture method to estimate the proportion of undetected cases. RESULTS: The best performance was achieved by the 12-month interval algorithm, detecting 2,150 incident MS cases, with 74.4% sensitivity (95%CI = 64.1%, 85.9%) and 95.3% specificity (95%CI = 90.7%, 99.8%). The cumulative incidence was 36.68 (95%CI = 35.15, 38.26) per 100,000 from 2016 to 2020. The mean annual incidence was 7.34 (95%CI = 7.03, 7.65) per 100,000 people-year. The geographical distribution of MS relative risk shows a decreasing east-west incidence gradient. The number of expected MS cases was 11% higher than the detected cases. CONCLUSIONS: We validated a case-finding algorithm based on administrative data to estimate MS incidence, and its spatial/temporal variations. This algorithm provides up-to-date estimates of MS incidence, and will be used in future studies to evaluate changes in MS incidence in relation to different risk factors.

The independent contribution of brain, spinal cord and gadolinium MRI in treatment decision in multiple sclerosis: A population-based retrospective study.

BACKGROUND: Spinal cord and gadolinium (Gd)-enhanced magnetic resonance imaging (MRI) can provide additional information to brain MRI to determine prognosis of multiple sclerosis (MS). However, the real-world impact of routine use of brain MRI with spinal cord and/or Gd sequences is unknown. Our aim was to evaluate the effect of brain, spinal cord and Gd MRI on treatment decisions in MS. METHODS: In this 2015-2020 population-based study, we performed a retrospective analysis on MS patients resident in the Campania Region (South Italy), with disease modifying treatment (DMT) prescription (n = 6,161). DMTs were classified as platform (dimethyl fumarate, glatiramer acetate, interferon-beta, peg-interferon-beta, teriflunomide), or high-efficacy (alemtuzumab, cladribine, fingolimod, natalizumab, ocrelizumab). We evaluated the association between binary MRI variables and switch from platform to high-efficacy DMT using multivariable logistic regression. RESULTS: The likelihood of switch from platform to high-efficacy DMT was 47% higher when including post-Gd acquisitions to brain and/or spinal cord MRI, 59% higher when including spinal cord acquisitions to brain MRI, and 132% higher when including any MRI compared with no MRI (all p < 0.05). The likelihood of switch to high-efficacy DMT decreased over time from treatment start. CONCLUSION: Our results show that spinal cord and Gd MRI acquisitions can provide relevant information to influence subsequent treatment decisions, especially in early treatment phases, compared with stand-alone brain MRI.