Association of serum glial fibrillary acidic protein with progression independent of relapse activity in multiple sclerosis

OBJECTIVE

Insidious disability worsening is a common feature in relapsing-remitting multiple sclerosis (RRMS). Many patients experience progression independent of relapse activity (PIRA) despite being treated with high efficacy disease-modifying therapies. We prospectively investigated associations of body-fluid and imaging biomarkers with PIRA.

METHODS

Patients with early RRMS (n = 104) were prospectively included and followed up for 60 months. All patients were newly diagnosed and previously untreated. PIRA was defined using a composite score including the expanded disability status scale, 9-hole peg test, timed 25 foot walk test, and the symbol digit modalities test. Eleven body fluid and imaging biomarkers were determined at baseline and levels of serum neurofilament light (sNfL) and glial fibrillary acidic protein (sGFAP) were also measured annually thereafter. Association of baseline biomarkers with PIRA was investigated in multivariable logistic regression models adjusting for clinical and demographic confounding factors. Longitudinal serum biomarker dynamics were investigated in mixed effects models.

RESULTS

Only sGFAP was significantly higher in PIRA at baseline (median [IQR] 73.9 [60.9-110.1] vs. 60.3 [45.2-79.9], p = 0.01). A cut-off of sGFAP > 65 pg/mL resulted in a sensitivity of 68% and specificity of 61%, to detect patients at higher risk of PIRA. In a multivariable logistic regression, sGFAP > 65 pg/mL was associated with higher odds of developing PIRA (odds ratio 4.3, 95% CI 1.44-12.86, p = 0.009). Repeated measures of sGFAP levels showed that patients with PIRA during follow-up had higher levels of sGFAP along the whole follow-up compared to stable patients (p < 0.001).

CONCLUSION

Determination of sGFAP at baseline and follow-up may be useful in capturing disability accrual independent of relapse activity in early RRMS.

The Role of Glial Fibrillary Acidic Protein as a Biomarker in Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorder: A Systematic Review and Meta-Analysis

There is debate on the role of glial fibrillary acidic protein (GFAP) as a reliable biomarker in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), and its potential to reflect disease progression. This review aimed to investigate the role of GFAP in MS and NMOSD. A systematic search of electronic databases, including PubMed, Embase, Scopus, and Web of Sciences, was conducted up to 20 December 2023 to identify studies that measured GFAP levels in people with MS (PwMS) and people with NMOSD (PwNMOSD). R software version 4.3.3. with the random-effect model was used to pool the effect size with its 95% confidence interval (CI). Of 4109 studies, 49 studies met our inclusion criteria encompassing 3491 PwMS, 849 PwNMOSD, and 1046 healthy controls (HCs). The analyses indicated that the cerebrospinal fluid level of GFAP (cGFAP) and serum level of GFAP (sGFAP) were significantly higher in PwMS than HCs (SMD = 0.7, 95% CI: 0.54 to 0.86, p < 0.001, I2 = 29%, and SMD = 0.54, 95% CI: 0.1 to 0.99, p = 0.02, I2 = 90%, respectively). The sGFAP was significantly higher in PwNMOSD than in HCs (SMD = 0.9, 95% CI: 0.73 to 1.07, p < 0.001, I2 = 10%). Among PwMS, the Expanded Disability Status Scale (EDSS) exhibited significant correlations with cGFAP (r = 0.43, 95% CI: 0.26 to 0.59, p < 0.001, I2 = 91%) and sGFAP (r = 0.36, 95% CI: 0.23 to 0.49, p < 0.001, I2 = 78%). Regarding that GFAP is increased in MS and NMOSD and has correlations with disease features, it can be a potential biomarker in MS and NMOSD and indicate the disease progression and disability in these disorders.

Baseline serum neurofilament light chain levels differentiate aggressive from benign forms of relapsing-remitting multiple sclerosis: a 20-year follow-up cohort

BACKGROUND AND OBJECTIVES

Serum biomarkers are emerging as useful prognostic tools for multiple sclerosis (MS); however, long-term studies are lacking. We aimed to evaluate the long-term prognostic value of the serum levels of neurofilament light chain (NfL), total tau, glial fibrillary acidic protein (GFAP), and chitinase 3-like-1 (CHI3L1) measured close to the time of MS onset.

METHODS

In this retrospective, exploratory, observational, case and controls study, patients with relapsing-remitting MS (RRMS) with available baseline serum samples and prospectively follow-up in our MS unit for a long time were selected based on their clinical evolution to form two groups: (1) a benign RRMS (bRRMS) group, defined as patients with an Expanded Disability Status Scale (EDSS) score of ≤ 3 at ≥ 10 years of follow-up; (2) an aggressive RRMS (aRRMS) group, defined as patients with an EDSS score of ≥ 6 at ≤ 15 years of follow-up. An age-matched healthy control (HC) group was selected. NfL, total tau, and GFAP serum levels were quantified using a single-molecule array (SIMOA), and CHI3L1 was quantified using ELISA.

RESULTS

Thirty-one patients with bRRMS, 19 with aRRMS, and 10 HC were included. The median follow-up time from sample collection was 17.74 years (interquartile range, 14.60-20.37). Bivariate and multivariate analyses revealed significantly higher NfL and GFAP levels in the aRRMS group than in the bRRMS group. A receiver operating characteristic curve analysis identified serum NfL level as the most efficient marker for distinguishing aRRMS from bRRMS.

DISCUSSION

This proof-of-concept study comparing benign and aggressive RRMS groups reinforces the potential role of baseline NfL serum levels as a promising long-term disability prognostic marker. In contrast, serum GFAP, total tau, and CHI3L1 levels demonstrated a lower or no ability to differentiate between the long-term outcomes of RRMS.

Emerging Cerebrospinal Fluid Biomarkers of Disease Activity and Progression in Multiple Sclerosis

Importance

Biomarkers distinguishing nonrelapsing progressive disease biology from relapsing biology in multiple sclerosis (MS) are lacking. Cerebrospinal fluid (CSF) is an accessible fluid that most closely reflects central nervous system biology.

Objective

To identify CSF biological measures associated with progressive MS pathobiology.

Design, Setting, and Participants

This cohort study assessed data from 2 prospective MS cohorts: a test cohort provided serial CSF, clinical, and imaging assessments in a multicenter study of patients with relapsing MS (RMS) or primary progressive MS (PPMS) who were initiating anti-CD20 treatment (recruitment: 2016-2018; analysis: 2020-2023). A single-site confirmation cohort was used to assess CSF at baseline and long-term (>10 year) clinical follow-up (analysis: 2022-2023).

Exposures

Test-cohort participants initiated standard-of-care ocrelizumab treatment. Confirmation-cohort participants were untreated or received standard-of-care disease-modifying MS therapies.

Main Outcomes and Measures

Twenty-five CSF markers, including neurofilament light chain, neurofilament heavy chain, and glial fibrillary acid protein (GFAP); 24-week confirmed disability progression (CDP24); and brain magnetic resonance imaging measures reflecting focal injury, tissue loss, and progressive biology (slowly expanding lesions [SELs]).

Results

The test cohort (n = 131) included 100 patients with RMS (mean [SD] age, 36.6 [10.4] years; 68 [68%] female and 32 [32%] male; Expanded Disability Status Scale [EDSS] score, 0-5.5), and 31 patients with PPMS (mean [SD] age, 44.9 [7.4] years; 15 [48%] female and 16 [52%] male; EDSS score, 3.0-6.5). The confirmation cohort (n = 68) included 41 patients with RMS and 27 with PPMS enrolled at diagnosis (age, 40 years [range, 20-61 years]; 47 [69%] female and 21 [31%] male). In the test cohort, GFAP was correlated with SEL count (r = 0.33), greater proportion of T2 lesion volume from SELs (r = 0.24), and lower T1-weighted intensity within SELs (r = -0.33) but not with acute inflammatory measures. Neurofilament heavy chain was correlated with SEL count (r = 0.25) and lower T1-weighted intensity within SELs (r = -0.28). Immune markers correlated with measures of acute inflammation and, unlike GFAP, were impacted by anti-CD20. In the confirmation cohort, higher baseline CSF GFAP levels were associated with long-term CDP24 (hazard ratio, 2.1; 95% CI, 1.3-3.4; P = .002).

Conclusions and Relevance

In this study, activated glial markers (in particular GFAP) and neurofilament heavy chain were associated specifically with nonrelapsing progressive disease outcomes (independent of acute inflammatory activity). Elevated CSF GFAP was associated with long-term MS disease progression.

Plasma glial fibrillary acidic protein levels correlate with paramagnetic rim lesions in people with radiologically isolated syndrome

BACKGROUND

There are no specific, evidence-based recommendations for the management of individuals with radiologically isolated syndrome. Imaging and blood biomarkers may have prognostic utility.

OBJECTIVE

To determine whether plasma neurofilament light protein (NfL) or glial fibrillary acidic protein (GFAP) levels in people with radiologically isolated syndrome correlate with imaging measures that have been shown to be associated with negative clinical outcomes in people with multiple sclerosis.

METHODS

Cross-sectional analysis of people with radiologically isolated syndrome. Participants underwent magnetic resonance imaging (MRI) of the brain and cervical spinal cord, and plasma was collected. Plasma NfL and GFAP levels were measured with a single-molecule array, and correlations with MRI measures were assessed, including the number of: T1-black holes, white-matter lesions demonstrating the central vein sign, paramagnetic rim lesions, cervical spinal cord lesions and infratentorial lesions.

RESULTS

Plasma GFAP levels, but not NfL levels, showed correlations with the number of T1-black holes, white matter lesions demonstrating the central vein sign and paramagnetic rim lesions (all p < 0.05).

CONCLUSION

We found correlations between plasma GFAP levels and imaging measures associated with poor clinical outcomes and chronic inflammation in individuals with radiologically isolated syndrome. Plasma GFAP may have prognostic utility in clinical trials and clinical practice.

How Early Is Early Multiple Sclerosis?

The development and further optimization of the diagnostic criteria for multiple sclerosis (MS) emphasize the establishment of an early and accurate diagnosis. So far, numerous studies have revealed the significance of early treatment administration for MS and its association with slower disease progression and better late outcomes of the disease with regards to disability accumulation. However, according to current research results, both neuroinflammatory and neurodegenerative processes may exist prior to symptom initiation. Despite the fact that a significant proportion of individuals with radiologically isolated syndrome (RIS) progress to MS, currently, there is no available treatment approved for RIS. Therefore, our idea of "early treatment administration" might be already late in some cases. In order to detect the individuals who will progress to MS, we need accurate biomarkers. In this review, we present notable research results regarding the underlying pathology of MS, as well as several potentially useful laboratory and neuroimaging biomarkers for the identification of high-risk individuals with RIS for developing MS. This review aims to raise clinicians' awareness regarding "subclinical" MS, enrich their understanding of MS pathology, and familiarize them with several potential biomarkers that are currently under investigation and might be used in clinical practice in the future for the identification of individuals with RIS at high risk for conversion to definite MS.

Increasing Neurofilament and Glial Fibrillary Acidic Protein After Treatment Discontinuation Predicts Multiple Sclerosis Disease Activity

BACKGROUND AND OBJECTIVES

Stable patients with multiple sclerosis (MS) may discontinue treatment, but the risk of disease activity is unknown. Serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein (sGFAP) are biomarkers of subclinical disease activity and may help risk stratification. In this study, sNfL and sGFAP levels in stable patients were evaluated before and after treatment discontinuation to determine association with disease activity.

METHODS

This observational study included patients enrolled in the Comprehensive Longitudinal Investigation in MS at the Brigham and Women's Hospital who discontinued treatment after >2 years disease activity-free. Two serum samples within 2 years, before and after treatment stop, were sent for sNfL and sGFAP measurements by single-molecule array. Biannual neurologic examinations and yearly MRI scans determined disease activity by 3 time-to-event outcomes: 6-month confirmed disability worsening (CDW), clinical attacks, and MRI activity (new T2 or contrast-enhancing lesions). Associations between each outcome and log-transformed sNfL and sGFAP levels pretreatment stop and posttreatment stop and the percent change were estimated using multivariable Cox regression analysis adjusting for age, disability, disease duration, and duration from attack before treatment stop.

RESULTS

Seventy-eight patients (92% female) discontinued treatment at a median (interquartile range) age of 48.5 years (39.0-55.7) and disease duration of 12.3 years (7.5-18.8) and were followed up for 6.3 years (4.2-8.5). CDW occurred in 27 patients (35%), new attacks in 19 (24%), and new MRI activity in 26 (33%). Higher posttreatment stop sNfL level was associated with CDW (adjusted hazard ratio (aHR) 2.80, 95% CI 1.36-5.76, p = 0.005) and new MRI activity (aHR 3.09, 95% CI 1.42-6.70, p = 0.004). Patients who had >100% increase in sNfL level from pretreatment stop to posttreatment stop had greater risk of CDW (HR 3.87, 95% CI 1.4-10.7, p = 0.009) and developing new MRI activity (HR 4.02, 95% CI 1.51-10.7, p = 0.005). Patients who had >50% increase in sGFAP level also had greater risk of CDW (HR 5.34, 95% CI 1.4-19.9, p = 0.012) and developing new MRI activity (HR 5.16, 95% CI 1.71-15.6, p = 0.004).

DISCUSSION

Stable patients who discontinue treatment may be risk stratified by sNfL and sGFAP levels measured before and after discontinuing treatment. Further studies are needed to validate findings and determine whether resuming treatment in patients with increasing biomarker levels reduces risk of subsequent disease activity.

Association between serum multi-protein biomarker profile and real-world disability in multiple sclerosis

Few studies examined blood biomarkers informative of patient-reported outcome (PRO) of disability in people with multiple sclerosis (MS). We examined the associations between serum multi-protein biomarker profiles and patient-reported MS disability. In this cross-sectional study (2017-2020), adults with diagnosis of MS (or precursors) from two independent clinic-based cohorts were divided into a training and test set. For predictors, we examined seven clinical factors (age at sample collection, sex, race/ethnicity, disease subtype, disease duration, disease-modifying therapy [DMT], and time interval between sample collection and closest PRO assessment) and 19 serum protein biomarkers potentially associated with MS disease activity endpoints identified from prior studies. We trained machine learning (ML) models (Least Absolute Shrinkage and Selection Operator regression [LASSO], Random Forest, Extreme Gradient Boosting, Support Vector Machines, stacking ensemble learning, and stacking classification) for predicting Patient Determined Disease Steps (PDDS) score as the primary endpoint and reported model performance using the held-out test set. The study included 431 participants (mean age 49 years, 81% women, 94% non-Hispanic White). For binary PDDS score, combined feature input of routine clinical factors and the 19 proteins consistently outperformed base models (comprising clinical features alone or clinical features plus one single protein at a time) in predicting severe (PDDS ≥ 4) versus mild/moderate (PDDS < 4) disability across multiple machine learning approaches, with LASSO achieving the best area under the curve (AUCPDDS = 0.91) and other metrics. For ordinal PDDS score, LASSO model comprising combined clinical factors and 19 proteins as feature input (R2PDDS = 0.31) again outperformed base models. The two best-performing LASSO models (i.e., binary and ordinal PDDS score) shared six clinical features (age, sex, race/ethnicity, disease subtype, disease duration, DMT efficacy) and nine proteins (cluster of differentiation 6, CUB-domain-containing protein 1, contactin-2, interleukin-12 subunit-beta, neurofilament light chain [NfL], protogenin, serpin family A member 9, tumor necrosis factor superfamily member 13B, versican). By comparison, LASSO models with clinical features plus one single protein at a time as feature input did not select either NfL or glial fibrillary acidic protein (GFAP) as a final feature. Forcing either NfL or GFAP as a single protein feature into models did not improve performance beyond clinical features alone. Stacking classification model using five functional pathways to represent multiple proteins as meta-features implicated those involved in neuroaxonal integrity as significant contributors to predictive performance. Thus, serum multi-protein biomarker profiles improve the prediction of real-world MS disability status beyond clinical profile alone or clinical profile plus single protein biomarker, reaching clinically actionable performance.

Do the current MS clinical course descriptors need to change and if so how? A survey of the MS community

BACKGROUND AND OBJECTIVES

The current clinical course descriptors of multiple sclerosis (MS) include a combination of clinical and magnetic resonance imaging (MRI) features. Recently there has been a growing call to base these descriptors more firmly on biological mechanisms. We investigated the implications of proposing a new mechanism-driven framework for describing MS.

METHODS

In a web-based survey, multiple stakeholders rated the need to change current MS clinical course descriptors, the definitions of disease course and their value in clinical practice and related topics.

RESULTS

We received 502 responses across 49 countries. In all, 77% of the survey respondents supported changing the current MS clinical course descriptors. They preferred a framework that informs treatment decisions, aids the design and conduct of clinical trials, allows patients to understand their disease, and links disease mechanisms and clinical expression of disease. Clinical validation before dissemination and ease of communication to patients were rated as the most important aspects to consider when developing any new framework for describing MS.

CONCLUSION

A majority of MS stakeholders agreed that the current MS clinical course descriptors need to change. Any change process will need to engage a wide range of affected stakeholders and be guided by foundational principles.

Accuracy of serum neurofilament light to identify contrast-enhancing lesions in multiple sclerosis

BACKGROUND

Contrast-enhancing magnetic resonance imaging (MRI) lesions (CELs) indicate acute multiple sclerosis inflammation. Serum biomarkers, neurofilament light (sNfL), and glial fibrillary acidic protein (sGFAP) may increase in the presence of CELs, and indicate a need to perform MRI.

OBJECTIVE

We assessed the accuracy of biomarkers to detect CELs.

METHODS

Patients with two gadolinium-enhanced MRIs and serum biomarkers tested within 3 months were included (N = 557, 66% female). Optimal cut-points from Bland-Altman analysis for spot biomarker level and Youden's index for delta-change from remission were evaluated.

RESULTS

A total of 116 patients (21%) had CELs. A spot sNfL measurement >23.0 pg/mL corresponded to 7.0 times higher odds of CEL presence (95% CI: 3.8, 12.8), with 25.9% sensitivity, 95.2% specificity, operating characteristic curve (AUC) 0.61; while sNfL delta-change >30.8% from remission corresponded to 5.0 times higher odds (95% CI: 3.2, 7.8), 52.6% sensitivity, 81.9% specificity, AUC 0.67. sGFAP had poor CEL detection. In patients > 50 years, neither cut-point remained significant. sNfL delta-change outperformed spot levels at identifying asymptomatic CELs (AUC 0.67 vs 0.59) and in patients without treatment escalation between samples (AUC 0.67 vs 0.57).

CONCLUSION

Spot sNfL >23.0 pg/mL or a 30.8% increase from remission provides modest prediction of CELs in patients <50 years; however, low sNfL does not obviate the need for MRI.

Glial fibrillary acidic protein and multiple sclerosis progression independent of acute inflammation

BACKGROUND

The clinical relevance of serum glial fibrillary acidic protein (sGFAP) concentration as a biomarker of MS disability progression independent of acute inflammation has yet to be quantified.

OBJECTIVE

To test whether baseline values and longitudinal changes in sGFAP concentration are associated with disability progression without detectable relapse of magnetic resonance imaging (MRI) inflammatory activity in participants with secondary-progressive multiple sclerosis (SPMS).

METHODS

We retrospectively analyzed longitudinal sGFAP concentration and clinical outcome data from the Phase 3 ASCEND trial of participants with SPMS, with no detectable relapse or MRI signs of inflammatory activity at baseline nor during the study (n = 264). Serum neurofilament (sNfL), sGFAP, T2 lesion volume, Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk (T25FW), 9-Hole Peg Test (9HPT), and composite confirmed disability progression (CDP) were measured. Linear and logistic regressions and generalized estimating equations were used in the prognostic and dynamic analyses.

RESULTS

We found a significant cross-sectional association between baseline sGFAP and sNfL concentrations and T2 lesion volume. No or weak correlations between sGFAP concentration and changes in EDSS, T25FW, and 9HPT, or CDP were observed.

CONCLUSION

Without inflammatory activity, changes in sGFAP concentration in participants with SPMS were neither associated with current nor predictive of future disability progression.

Early neurofilament light and glial fibrillary acidic protein levels improve predictive models of multiple sclerosis outcomes

BACKGROUND

Early risk-stratification in multiple sclerosis (MS) may impact treatment decisions. Current predictive models have identified that clinical and imaging characteristics of aggressive disease are associated with worse long-term outcomes. Serum biomarkers, neurofilament (sNfL) and glial fibrillary acidic protein (sGFAP), reflect subclinical disease activity through separate pathological processes and may contribute to predictive models of clinical and MRI outcomes.

METHODS

We conducted a retrospective analysis of the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB study), where patients with multiple sclerosis are seen every 6 months and undergo Expanded Disability Status Scale (EDSS) assessment, have annual brain MRI scans where volumetric analysis is conducted to calculate T2-lesion volume (T2LV) and brain parenchymal fraction (BPF), and donate a yearly blood sample for subsequent analysis. We included patients with newly diagnosed relapsing-remitting MS and serum samples obtained at baseline visit and 1-year follow-up (both within 3 years of onset), and were assessed at 10-year follow-up. We measured sNfL and sGFAP by single molecule array at baseline visit and at 1-year follow-up. A predictive clinical model was developed using age, sex, Expanded Disability Status Scale (EDSS), pyramidal signs, relapse rate, and spinal cord lesions at first visit. The main outcome was odds of developing of secondary progressive (SP)MS at year 10. Secondary outcomes included 10-year EDSS, brain T2LV and BPF. We compared the goodness-of-fit of the predictive clinical model with and without sNfL and sGFAP at baseline and 1-year follow-up, for each outcome by area under the receiver operating characteristic curve (AUC) or R-squared.

RESULTS

A total 144 patients with median MS onset at age 37.4 years (interquartile range: 29.4-45.4), 64% female, were included. SPMS developed in 25 (17.4%) patients. The AUC for the predictive clinical model without biomarker data was 0.73, which improved to 0.77 when both sNfL and sGFAP were included in the model (P = 0.021). In this model, higher baseline sGFAP associated with developing SPMS (OR=3.3 [95%CI:1.1,10.6], P = 0.04). Adding 1-year follow-up biomarker levels further improved the model fit (AUC = 0.79) but this change was not statistically significant (P = 0.15). Adding baseline biomarker data also improved the R-squared of clinical models for 10-year EDSS from 0.24 to 0.28 (P = 0.032), while additional 1-year follow-up levels did not. Baseline sGFAP was associated with 10-year EDSS (ß=0.58 [95%CI:0.00,1.16], P = 0.05). For MRI outcomes, baseline biomarker levels improved R-squared for T2LV from 0.12 to 0.27 (P<0.001), and BPF from 0.15 to 0.20 (P = 0.042). Adding 1-year follow-up biomarker data further improved T2LV to 0.33 (P = 0.0065) and BPF to 0.23 (P = 0.048). Baseline sNfL was associated with T2LV (ß=0.34 [95%CI:0.21,0.48], P<0.001) and 1-year follow-up sNfL with BPF (ß=-2.53% [95%CI:-4.18,-0.89], P = 0.003).

CONCLUSIONS

Early biomarker levels modestly improve predictive models containing clinical and MRI variables. Worse clinical outcomes, SPMS and EDSS, are associated with higher sGFAP levels and worse MRI outcomes, T2LV and BPF, are associated with higher sNfL levels. Prospective study implementing these predictive models into clinical practice are needed to determine if early biomarker levels meaningfully impact clinical practice.

Disease-modifying therapies for relapsing/active secondary progressive multiple sclerosis - a review of population-specific evidence from randomized clinical trials

Although the understanding of secondary progressive multiple sclerosis (SPMS) is evolving, early detection of relapse-independent progression remains difficult. This is further complicated by superimposed relapses and compensatory mechanisms that allow for silent progression. The term relapsing multiple sclerosis (RMS) subsumes relapsing-remitting multiple sclerosis (RRMS) and SPMS with relapses. The latter is termed 'active' SPMS, for which disease-modifying therapies (DMTs) approved for either RMS or active SPMS can be used. However, the level of evidence supporting efficacy and safety in SPMS differs between drugs approved for RMS and SPMS. Our review aims to identify current evidence from published clinical trials and European public assessment reports from the marketing authorization procedure on the efficacy, especially on progression, of DMTs approved for RMS and SPMS. To identify relevant evidence, a literature search has been conducted and European public assessment reports of DMTs approved for RMS have been screened for unpublished data specific to SPMS. Only two clinical trials demonstrated a significant reduction in disability progression in SPMS study populations: the EXPAND study for siponimod, which included a typical SPMS population, and the European study for interferon (IFN)-beta 1b s.c., which included patients with very early and active SPMS. Both DMTs also achieved significant reductions in relapse rates. Ocrelizumab, cladribine, ofatumumab, and ponesimod are all approved for RMS - ocrelizumab, ofatumumab, and ponesimod based on an RMS study, cladribine based on an RRMS study. Data on efficacy in SPMS are only available from post hoc analyses of very small subgroups, representing only up to 15% of the total study population. For these DMTs, approval for RMS, including active SPMS, was mainly based on the assumption that the reduction in relapse rate observed in patients with RRMS can also be applied to SPMS. Based on that, the potential of these drugs to reduce relapse-independent progression remains unclear.