Vol 56, No 3 (2022)
Invited Review Article
Published online: 2022-06-17

open access

Page views 4899
Article views/downloads 772
Get Citation

Connect on Social Media

Connect on Social Media

INVITED REVIEW ARTICLE

Neurologia i Neurochirurgia Polska

Polish Journal of Neurology and Neurosurgery

2022, Volume 56, no. 3, pages: 228–235

DOI: 10.5603/PJNNS.a2022.0041

Copyright © 2022 Polish Neurological Society

ISSN: 0028-3843, e-ISSN: 1897-4260

Clinical trials in multiple sclerosis: past, present, and future

Navid Manouchehri1Afsaneh Shirani2Victor H. Salinas1Lauren Tardo1Rehana Z. Hussain1David Pitt3Olaf Stuve14
1Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, United States
2Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, United States
3Department of Neurology, Yale University, New Haven, CT, United States
4Neurology Section, VA North Texas Health Care System, Dallas, TX, United States

Address for correspondence: Olaf Stuve, Department of Neurology University of Texas Southwestern Medical Center, Dallas, TX 75216-8813, United States; e-mail: olaf.stuve@utsouthwestern.edu

ABSTRACT
For the past four decades, multiple sclerosis (MS) has been a focus for clinical trial development and execution. Advances in translational neuroimmunology have led to the development of effective disease-modifying therapies (DMTs) that greatly benefit patients with MS and mitigate their burden of disease. These achievements also stem from continued progress made in the definition and discovery of sensitive disease diagnostic criteria, objective disability assessment scales, precise imaging techniques, and disease-specific biomarkers. As a result, our knowledge of MS pathophysiology is more mature; the established clinical practice for the diagnosis and management of MS could serve as a roadmap to guide the development of more disease-specific interventions. In this article we briefly review the main achievements in the evolution of clinical trials for MS, and discuss opportunities for improvements.
Key words: multiple sclerosis, clinical trials, pharmacology
(Neurol Neurochir Pol 2022; 56 (3): 228–235

Introduction

The widespread use of today disease-modifying therapies (DMTs) as the mainstay of treatment in multiple sclerosis (MS) draws on data provided by clinical trials over the past two decades. In parallel with the rapidly growing treatment landscape for MS, clinical trials have evolved to incorporate innovative designs and mechanistic insights [1]. Revised diag­nostic criteria and the characterisation of MS phenotypes across the age range have improved MS pharmacotherapy trials [2, 3]. Today, MS trials benefit from sensitive diagnostic criteria and clinically relevant follow-up data permitted by the latest imaging techniques and objective disability progression documentation i.e. the expanded disability status scale (EDSS). Furthermore, new frontiers in para-clinical exams provide a growing list of biomarkers, some of which might hold potential biological significance.

All currently approved DMTs diminish two types of disease activity: the occurrence of inflammatory signal changes on magnetic resonance imaging (MRI); and the frequency of clinical relapses. MS trials can now consider potential pathophysiological differences between active and non-active disease, and recruit patients into prospective trials accordingly.

MS is a clinically, radiologically and pathologically hete­rogeneous condition. Treatment with various DMTs with different mechanisms of action (MOA) further differentiates patients with MS. This introduces statistical and ethical challenges to future trials. For instance, rather than placebo, novel treatments are likely to be compared to approved effective control DMTs, which might affect estimates of the magnitude of treatment effect and subsequently the success rate of the future trial. As the global cohort of patients diagnosed with MS reach advanced ages, they can be expected to transition to secondary progressive non-active MS. Regrettably, in spite of all their success in treating active MS, current DMTs have failed to provide meaningful clinical benefit for older patients living with progressive non-active MS. Here, we discuss how trials have evolved and contributed to the current state of clinical practice and research in MS.

Milestones in evolution of MS trials

MS diagnosis

Consistency in patient recruitment for trials depends on a consensus regarding diagnostic criteria. Optimal trial design in MS requires the appreciation of differences that distinguish MS subtypes. Originally, clinical disease course was adopted as a mean to categorise these subtypes and unify trials efforts in early studies.

Charcot’s triad utilised nystagmus, intention tremor, and scanning speech in an initial attempt to define MS [4, 5]. In hindsight, this approach probably described patients with a preponderance of demyelinating lesions in specific locations of the central nervous system (CNS) such as the cerebellum, rather than an actual subset which holds any relevance for guiding clinical trial design and tailored treatment development. Historical MS diagnostic criteria, such as Schumacher’s, defined the disease as an inflammatory disorder of the CNS with dissemination in time and space [6]. This was later expanded by Poser to address data driven from cerebrospinal fluid (CSF) and imaging components [7]. Eventually, it was the McDonald criteria that incorporated clinical aspects, MRI data and CSF oligoclonal bands to further simplify MS diagnosis. Revisions to the original McDonald criteria included gadolinium (Gd) enhancing lesions as a correlate of dissemination in time, and the co-existence of periventricular, juxtacortical, infratentorial or spinal cord lesions as a correlate of dissemination in space [8]. The diagnostic sensitivity of subsequently revised criteria was even further enhanced by considering patients presenting with clinically isolated syndrome (CIS) as definite MS, when MRI and CSF finding corroborated the diagnosis [9–14]. This increase in diagnostic sensitivity facilitated the recruitment of patients into potential trials. Currently, the approved criteria allow for a definite MS diagnosis within a single time frame pertinent to a typical demyelinating event, without waiting for a second attack.

Inadvertently earlier enrollment of patients during the course of the disease can artificially improve prognosis, due to lead-time bias. This is especially important when drawing comparisons involving historical trials in a fast-evolving paradigm like DMTs in MS. Under the 2001 and 2017 McDonald criteria, within 12 months of presentation, 50% of patients with CIS proceeded to definite MS. But based on the Poser criteria, only a 20% conversion rate to definite MS diagnosis was observed, underlining the sensitivity of the McDonald criteria [15]. It is difficult to ascertain to what extent the current perceived improvement in patients’ clinical status is attributable to an expedited diagnosis, independent of DMT effect. Compared to historical cohorts of people with MS, modern MS cohorts, on average, have a lower annualised relapse rate (ARR) and a milder course of disease [16]. In fact, even patients in the placebo groups are experiencing longer relapse-free durations following their enrollments in trials; however, this is not as pronounced compared to DMT-treated patients who show statistically significant improvement in tangible clinical outcomes [2, 16].

More empirical evidence is urgently required in order to precisely calculate the extent of lead-time bias in the overall improved outcome of patients with MS receiving second or third generation DMTs. The TRaditional versus Early Aggressive Therapy for MS (TREAT-MS) trial is a randomised controlled trial that aims to: (A) evaluate, jointly and independently among patients deemed at higher risk vs lower risk for disability accumulation, whether an early therapeutic intervention considered highly effective versus a first-generation agent impacts the medium-term risk of disability; and (B) assess if, among patients deemed at lower risk for disability who start on first-line MS agents but experience breakthrough disease, those who switch to a higher-efficacy intervention versus a new first-line therapy have a different medium-term risk of disability (ClinicalTrials.gov/NCT03500328).

Regarding progressive MS, trials so far have used incongruous inclusion criteria to enroll patients. This lack of consistency has diminished the quality of pertinent trials for meta-analytical purposes. An objective definition of non-active progressive MS is crucial for trials that specifically seek to evaluate DMT efficacy in primary and secondary progressive MS phenotypes [17]. Building on the diagnostic acumen provided by the McDonald criteria, the 2013 Lublin consensus criteria drawn up by a panel of experts ratified a more precise definition for active vs. non-active disease and drew distinctions between relapsing, worsening, and progressive MS, thus paving the way for consistency in related trials [18]. Current methods in trials involving active relapsing MS allows for reliable appreciation of correlations between measures of disease activity and response to novel DMTs. Once prospective trials for non-active progressive MS achieve the recruitment of homogenous participants, similar novel objective measures may be developed to allow the evaluation of potential therapeutics.

Disability assessment in MS

The earliest therapeutic attempts to alter the disease course in MS by controlling inflammation were performed by Miller et al. and later by Rose et al., via the administration of adrenocorticotropic hormone (ACTH) or a saline placebo in patients believed to have had an acute clinical relapse [19, 20]. These studies implemented seemingly identical interventions; however, the outcome measures were fundamentally different. While Miller et al. measured treatment efficacy through subjective reports of improvement during follow up interviews, Rose et al. derived an objective assessment of improvement through neurological disability status scales [21]. Subsequent longitudinal data challenged the treatment intervention in both these trials, since adopting long-term monotherapy with corticosteroids eventually proved ineffective in MS management [22]. However, the implementation of the disability scale used in the latter approach grew to become a pillar of clinical data appraisal for MS trials involving treatment efficacy.

The move to define disability as an objective disease outcome started with the works of Arkin et al. [23, 24]. A diverse neurological scale was originally suggested, and this was later simplified by Kurtzke into a 10-point disability scale [21]. The new scale could track clinical status in patients with MS and gave uniform and reproducible results. The introduction of half points further refined this tool; the expanded disability status scale (EDSS) is used today by all MS clinicians to assess disability in patients with MS. Alternatively, the MS functional composite (MSFC) for assessment of disability in MS was later developed to mitigate the inherent shortcomings of the EDSS including its over-dependence on bipedal ambulation, its lack of sensitivity to cognitive decline, and its non-linearity [25]. MSFC successfully registered arm function, dexterity, and cognitive capacity on top of ambulation. MSFC was criticised for the learning phenomenon during paced auditory serial addition test (PASAT). MSFC utilises z-scores to depict deviation from a reference population, and this might have contributed to its failure to replace the easily available EDSS as the standard assessment tool in MS clinical trials.

The term ‘no evidence of disease activity’ (NEDA) was introduced in 2013 to clinical practice and research into MS [26]. It describes a disease-free status as a surrogate marker for treatment response in patients with MS. The early NEDA criteria comprised data pertaining to relapse rate, new or enlarging T2 lesions or Gd-enhancing lesions, as well as confirmed disability worsening as measured by EDSS. To capture more subtle disease-mediated insults and pertinent treatment effects, the original NEDA criteria have since been updated several times. NEDA-4 expanded on its predecessor by including brain atrophy. Higher domain NEDA status later incorporated the use of neurofilament light chain (NfL) levels in CSF as a close correlate of ongoing axonal injury [27]. The NEDA criteria encapsulate an expanding yet granular view of MS disease activity. Previous studies have commented on the prognostic value of NEDA for future disability accumulation [28]. It is conceivable that NEDA could be employed independently as a holistic outcome measure in future DMT trials.

CNS imaging in MS

Prior to the age of MRI, computed tomography (CT) scans were the only option for investigating CNS structural attributes in neurological disorders including MS. Naturally, CT scans were ill-equipped to record many therapeutically relevant structural changes recognised today in MS patients. At best, CT scans could register contrast enhancing lesions, originally correlated with an active disease; these lesions appeared to be resolved on subsequent CT scans after short steroid regimens [29].

The advent of MRI permitted a leap forward in the appreciation of structural changes pertinent to disease activity that were detectable through imaging. This also provided a revolutionary advantage for MS trials [30]. As one of the earliest effective DMTs, interferon β-1b (IFNβ-1b) injection was successfully attempted by Paty et al. as an intervention for MS treatment between 1988 and 1993. Demonstration of IFNβ1-b’s clinical success was greatly augmented by the evidence provided through MRI technology. MRI data proved that besides a better clinical outcome, treatment with IFNβ-1b significantly reduced the number of new and Gd enhancing lesions.

These results for the first time tied the MS imaging data to the approval of a novel therapy, setting a precedent for MRI as a reliable outcome measure in MS trials [31]. Today new Gd enhancing lesions, along with new or enlarging T2-lesions on MRI, are associated with immunologically active disease. Brain and spinal cord atrophy has been shown to correlate with disability progression [32, 33].

Advanced imaging techniques provide better resolution and precision; for instance, diffusion tensor imaging and magnetic resonance spectroscopy have been able to confirm disease activity beyond MRI lesion borders and within normal-appearing CNS tissues [34]. Similarly, seven-Tesla MRI has shown how conventional MRI studies might have underestimated the true MS lesion burden, especially in cortical grey matter [35]. Much like the leap that took place when MRI replaced CT scans, advanced imaging techniques may shine a light on new measures of disease activity and provide further therapeutic targets for future trials. Of note is the volumetric analysis of the choroid plexus; this immunologically-sensitive organ closely tracks the biological events pertinent to CSF and exhibits volume alterations relative to both MS disease activity and type of DMT [36, 37], and the identification and longitudinal assessment of chronic active MS lesions, also termed ‘smouldering lesions’ with paramagnetic rims [38–41].

DMT mechanism of action

The earliest clinical interventions in MS treatment trials depict the consensus on the disease pathophysiology; namely, acute inflammation drives MS activity which warrants treatment with corticosteroids or their agonists (i.e. ACTH) [19, 20]. Corticosteroids have been employed as treatment during active MS relapses as an attempt to mitigate organ damage [42], although longitudinal observations have not supported meaningful benefits to patients’ long term clinical prognosis [22, 43, 44].

In contrast, data generated during IFNβ-1b trials showed a clinically meaningful benefit of IFNβ-1b treatment and affirmed IFNβ-1b as the first DMT approved for MS [45]. The validating study did also speculate about possible MOAs for the favourable results seen with IFNβ-1b therapy. Specifically, interferon gamma (IFNγ) antagonism, suppression of immune response via suppressor T cells, and reduction in antigen presentation capacity of antigen presenting cells were suggested [46, 47]. To date, the exact MOA for IFNβ-1b in MS treatment remains controversial; however, this benchmark study cemented the paradigm that immunomodulation may prove favourable for MS, paving the way towards the development of other DMTs [48–50]. In fact, subsequent introduction of monoclonal antibodies as highly effective DMTs provided evidence for target-specificity against immunological cell subsets in relation to MS pathogenesis [51, 52]; furthermore, traffic-inhibiting agents suggested compartment-specificity of immunological events in relation to CNS autoimmunity. Natalizumab in particular showed how the access of encephalitho­genic cells across the blood-brain barrier is a crucial step for disease establishment and ongoing activity [53–55]. Moreover, the success of B cell depleting therapies implied involvement of B cells in disease pathogenesis [56–58].

Future novel therapies will have to outperform the current DMTs, therefore facing higher thresholds before they are adopted into routine clinical care. Nonetheless, these thresholds should and will revolve around unexplored MOAs that may prove relevant in relation to MS activity and progression, in particular in relation to non-active progressive MS, where most DMTs have failed. While studies on ocrelizumab for primary progressive MS and on siponimod for secondary progressive MS have suggested relative efficacies compared to placebo, it is likely that the observed efficacies were driven by a minority of enrolled patients with active disease [17, 59–61]. Future trials in progressive MS may prioritise neuroprotection, regeneration, and remyelination as their primary goal.

Trial designs

As stated before, more sensitive diagnostic criteria, along with the availability of treatments with proven clinical benefits, have complicated future MS trial design. Earlier diagnosis and aggressive treatment strategies have significantly benefited MS patients and reduced the overall disease activity in MS cohorts. In current trials, unexpected disease activity may warrant rescue therapies with available effective DMT, dimini­shing the overall ARR of the respective cohort. In contrast, disproportionate enrollment of refractory MS phenotypes, i.e. non-responders to current DMTs in trials for new candidate therapies, might artificially deflate the potential efficacy of such therapies. Evidently, a head-to-head comparison of all available DMTs in randomised clinical trials is logistically and ethically impossible. As a result, MS trial designs over time have adopted changes in order to address some of these constraints.

Trials for the earliest DMTs, which enrolled placebo-treated controls, had clinical and statistical significance of effects being established against virtually no modification to natural disease course. IFNβ-1b and glatiramer acetate were each approved in such double-blind randomised placebo-controlled trials [45, 48]. A plethora of evidence attests to the detrimental consequences of delays in MS treatment, and therefore a generic placebo-controlled approach in MS trial design was deemed no longer ethical by an international task force in 2000 and 2008 [62, 63]. However, it recognised certain conditions that could allow for the use of placebo in trials. These conditions included patient refusal of available treatments, treatment failure, or regional unavailability of other treatments. In fact, teriflunomide, dimethyl fumarate, and fingolimod were all approved in comparison to placebo arms in spite of available and approved DMTs [64]. Considering the weight of evidence behind the pivotal role of early treatment in MS, the phase III trial for peginterferon β1-a was perhaps the last conservable account for placebo-controlled MS trials [65]. The dynamic nature of MS pathophysiology, specifically in response to different treatments, backs the rationale for placebo-controlled trials. Alemtuzumab, a highly effective DMT, was approved in 2014 without any comparison to placebo, setting a precedent for future novel therapies [66, 67]. Different classes of DMTs, including anti-CD20 B cell depleting agents, ocrelizumab and ofatumumab, as well as ozanimod, a sphingosine-1 phosphate receptor modulator, were all approved in trials with active comparator controls, confirming the feasibility of such a design in trials of new MS therapeutics [58, 68, 69]. Given the range of currently effective DMTs, one could argue that cessation of placebo-controlled trials is in fact in the best interest of MS patients. Any new DMT that is validated in an active-comparator design outperforms the benchmark for treatment efficacy. However, this very mechanism also requires the said trials to recruit larger sample cohorts, rendering them more costly to perform. Similarly, other designs such as combination trials may entail the recruitment of large sample sizes and longer follow ups before any meaningful synergistic benefits are detectable; however, within a select subset of therapies with complementary MOAs, DMT synergism may be interrogated in phase IV open label studies with relatively small samples (Clinical trials.gov/ NCT03135249, NCT04178005).

Outlook for MS clinical trials

Traditionally, MRI-based outcome measures and disability scales have proven useful in establishing DMT efficacy in trials. Their usefulness, however, is challenged by the ever- -expanding scope of current and future trials. The downside to these outcome measures is twofold. First, they require the enrollment of very large patient cohorts, something which has become increasingly difficult with the availability of effective approved DMTs.

Second, many of the pathophysiological events pertinent to MS activity and progression do not reach their detection threshold. In fact, the hesitance of regulatory authorities, clinicians and researchers to adopt more sensitive and efficient measures is primarily because of the unavailability of alternative established reproducible measures with clinical relevance.

A major barrier specific to MS is the lack of representative biomarkers. Trials in the context of other conditions rely on such biomarkers as seen in the case of treatment development for cancer [70]. Disease-specific biomarkers would permit objective classification algorithms for diagnostic purposes as well, contributing to homogenisation of recruited samples in validating trials.

The main culprit behind MS, i.e. the immune system, is a dynamic entity; therefore a representative biomarker in MS, with reliable diagnostic and prognostic values to replace clinical correlates, is likely to prove elusive.

Efforts have been made to enhance the data gleaned from current imaging techniques. For instance, MRI-derived lesion load and brain atrophy sensitively measure current and past disease activity and facilitate an expedited transition to phase III trials for promising candidates [71]. The evolving imaging paradigms now attribute more weight to regional atrophy in CNS areas that are more sensitive to change and have better prognostic power including grey matter, thalamus and cerebellum [72, 73]. Optical coherence topography has seen an interest in trials to assess treatment efficacy as thinning of the retinal nerve fibre layer correlates to axonal injury [74]. Trials involving non-active progressive MS in particular might benefit from further validation of such methods. Non-traditional trial designs, such as multi-arm multistage adaptive trials or recruiting from biomarker-driven MS endophenotypes, to maximise the potential for response to new treatments, may further facilitate the validation of effective therapies in progressive MS [75, 76].

Biological fluid biomarkers are ideal outcome measures for trial purposes and patient follow up. Among the many nominees for a potential fluid biomarker in MS, so far only NFL has produced promising results in terms of correlation with ongoing neuroaxonal injury in patients with MS. Specifi­cally, it has been shown to correlate with relapse incidence, EDSS scores, MRI lesion load, and brain or spinal cord atrophy [77–79]. NFL is especially interesting since its plasma levels correlate with its CSF levels, allowing for less invasive measures; however as a sensitive measure, NFL plasma level is prone to MS-independent fluctuations. Prospective multicentre studies are required before NFL is widely adopted by clinicians and MS researchers.

In conclusion, the evolving discovery and validation of DMTs in MS clinical trials have provided an array of therapeutics that have improved clinical outcomes and quality of life for patients with MS. Current achievements in disease diagnosis and detection of disease activity, along with a better understanding of the mechanisms underpinning the disease pathogenesis, have broadened the horizon for therapeutic possibilities. The future may well lie in biomarker-based individualised pharmacotherapy.

Conflict of interest: None.

Funding: None.

References

  1. De Gasperis-Brigante CD, Parker JL, O’Connor PW, et al. Reducing clinical trial risk in multiple sclerosis. Mult Scler Relat Disord. 2016; 5: 81–88, doi: 10.1016/j.msard.2015.11.007, indexed in Pubmed: 26856949.
  2. Uitdehaag BMJ, Barkhof F, Coyle PK, et al. The changing face of multiple sclerosis clinical trial populations. Curr Med Res Opin. 2011; 27(8): 1529–1537, doi: 10.1185/03007995.2011.591370, indexed in Pubmed: 21671851.
  3. Montalban X. Review of methodological issues of clinical trials in multiple sclerosis. J Neurol Sci. 2011; 311 Suppl 1: S35–S42, doi: 10.1016/S0022-510X(11)70007-7, indexed in Pubmed: 22206765.
  4. Poser CM, Brinar VV. Diagnostic criteria for multiple sclerosis: an historical review. Clin Neurol Neurosurg. 2004; 106(3): 147–158, doi: 10.1016/j.clineuro.2004.02.004, indexed in Pubmed: 15177763.
  5. Gafson A, Giovannoni G, Hawkes CH. The diagnostic criteria for multiple sclerosis: From Charcot to McDonald. Mult Scler Relat Disord. 2012; 1(1): 9–14, doi: 10.1016/j.msard.2011.08.002, indexed in Pubmed: 25876446.
  6. Schumacher GA, Beebe G, Kibler RF, et al. Problems of experimental trials of therapy in multiple sclerosis: report by the panel on the evaluation of experimental trials of therapy in multiple sclerosis. Ann N Y Acad Sci. 1965; 122: 552–568, doi: 10.1111/j.1749-6632.1965.tb20235.x, indexed in Pubmed: 14313512.
  7. Poser CM, Paty DW, Scheinberg L, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol. 1983; 13(3): 227–231, doi: 10.1002/ana.410130302, indexed in Pubmed: 6847134.
  8. McDonald WI, Compston A, Edan G, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol. 2001; 50(1): 121–127, doi: 10.1002/ana.1032, indexed in Pubmed: 11456302.
  9. Brownlee WJ, Hardy TA, Fazekas F, et al. Diagnosis of multiple sclerosis: progress and challenges. Lancet. 2017; 389(10076): 1336–1346, doi: 10.1016/S0140-6736(16)30959-X, indexed in Pubmed: 27889190.
  10. Polman CH, Reingold SC, Edan G, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann Neurol. 2005; 58(6): 840–846, doi: 10.1002/ana.20703, indexed in Pubmed: 16283615.
  11. Polman CH, Reingold SC, Banwell B, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011; 69(2): 292–302, doi: 10.1002/ana.22366, indexed in Pubmed: 21387374.
  12. Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018; 17(2): 162–173, doi: 10.1016/S1474-4422(17)30470-2, indexed in Pubmed: 29275977.
  13. Filippi M, Preziosa P, Meani A, et al. MAGNIMS Study Group. Performance of the 2017 and 2010 Revised McDonald Criteria in Predicting MS Diagnosis After a Clinically Isolated Syndrome: A MAGNIMS Study. Neurology. 2022; 98(1): e1–e14, doi: 10.1212/WNL.0000000000013016, indexed in Pubmed: 34716250.
  14. Tintore M, Cobo-Calvo A, Carbonell P, et al. Effect of changes in MS diagnostic criteria over 25 years on time to treatment and prognosis in patients with clinically isolated syndrome. Neurology. 2021; 97(17): e1641–e1652, doi: 10.1212/WNL.0000000000012726, indexed in Pubmed: 34521693.
  15. Sormani MP, Tintorè M, Rovaris M, et al. Will Rogers phenomenon in multiple sclerosis. Ann Neurol. 2008; 64(4): 428–433, doi: 10.1002/ana.21464, indexed in Pubmed: 18688811.
  16. Inusah S, Sormani MP, Cofield SS, et al. Assessing changes in relapse rates in multiple sclerosis. Mult Scler. 2010; 16(12): 1414–1421, doi: 10.1177/1352458510379246, indexed in Pubmed: 20810517.
  17. Manouchehri N, Stüve O. Trials and therapies in secondary progressive MS, simplified. Nat Rev Neurol. 2019; 15(8): 431–432, doi: 10.1038/s41582-019-0233-x, indexed in Pubmed: 31285578.
  18. Lublin FD, Reingold SC, Cohen JA, et al. Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology. 2014; 83(3): 278–286, doi: 10.1212/WNL.0000000000000560, indexed in Pubmed: 24871874.
  19. Miller H, Newell DJ, Ridley A. Multiple sclerosis treatment of acute exacerbations with corticotrophin (a.c.t.h.). The Lancet. 1961; 278(7212): 1120–1122, doi: 10.1016/s0140-6736(61)91030-3.
  20. Rose AS, Kuzma JW, Kurtzke JF, et al. Cooperative study in the evaluation of therapy in multiple sclerosis: ACTH vs placebo in acute exacerbation. Trans Am Neurol Assoc. 1969; 94: 126–133, indexed in Pubmed: 4313957.
  21. Kurtzke JF. A new scale for evaluating disability in multiple sclerosis. Neurology. 1955; 5(8): 580–583, doi: 10.1212/wnl.5.8.580, indexed in Pubmed: 13244774.
  22. Ciccone A, Beretta S, Brusaferri F, et al. Corticosteroids for the long-term treatment in multiple sclerosis. Cochrane Database Syst Rev. 2008(1): CD006264, doi: 10.1002/14651858.CD006264.pub2, indexed in Pubmed: 18254098.
  23. Arkin H, Sherman IC, Weinberg SL. Tetraethylammonium chloride in the treatment of multiple sclerosis. AMA Arch Neurol Psychiatry. 1950; 64(4): 536–545, doi: 10.1001/archneurpsyc.1950.02310280048005, indexed in Pubmed: 14770597.
  24. Alexander L. New concept of critical steps in course of chronic debilitating neurologic disease in evaluation of therapeutic response; a longitudinal study of multiple sclerosis by quantitative evaluation of neurologic involvement and disability. AMA Arch Neurol Psychiatry. 1951; 66(3): 253–271, doi: 10.1001/archneurpsyc.1951.02320090002001, indexed in Pubmed: 14867990.
  25. Cutter GR, Baier ML, Rudick RA, et al. Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain. 1999; 122 (Pt 5): 871–882, doi: 10.1093/brain/122.5.871, indexed in Pubmed: 10355672.
  26. Giovannoni G, Bermel R, Phillips T, et al. A brief history of NEDA. Mult Scler Relat Disord. 2018; 20: 228–230, doi: 10.1016/j.msard.2017.07.011, indexed in Pubmed: 29579628.
  27. Giovannoni G, Tomic D, Bright JR, et al. “No evident disease activity”: The use of combined assessments in the management of patients with multiple sclerosis. Mult Scler. 2017; 23(9): 1179–1187, doi: 10.1177/1352458517703193, indexed in Pubmed: 28381105.
  28. Cree BAC, Gourraud PA, Oksenberg JR, et al. University of California, San Francisco MS-EPIC Team. Long-term evolution of multiple sclerosis disability in the treatment era. Ann Neurol. 2016; 80(4): 499–510, doi: 10.1002/ana.24747, indexed in Pubmed: 27464262.
  29. Viñuela FV, Fox AJ, Debrun GM, et al. New perspectives in computed tomography of multiple sclerosis. AJR Am J Roentgenol. 1982; 139(1): 123–127, doi: 10.2214/ajr.139.1.123, indexed in Pubmed: 6979846.
  30. Young IR, Hall AS, Pallis CA, et al. Nuclear magnetic resonance imaging of the brain in multiple sclerosis. Lancet. 1981; 2(8255): 1063–1066, doi: 10.1016/s0140-6736(81)91273-3, indexed in Pubmed: 6118521.
  31. Simon JH, Jacobs LD, Wende K, et al. Magnetic resonance studies of intramuscular interferon beta-1a for relapsing multiple sclerosis. The Multiple Sclerosis Collaborative Research Group. Ann Neurol. 1998; 43(1): 79–87, doi: 10.1002/ana.410430114, indexed in Pubmed: 9450771.
  32. Grossman RI, Gonzalez-Scarano F, Atlas SW, et al. Multiple sclerosis: gadolinium enhancement in MR imaging. Radiology. 1986; 161(3): 721–725, doi: 10.1148/radiology.161.3.3786722, indexed in Pubmed: 3786722.
  33. Sormani MP, Filippi M, de Stefano N, et al. MAGNIMS Steering Committee. MRI as an outcome in multiple sclerosis clinical trials. Neurology. 2009; 73(22): author reply 1932-3., doi: 10.1212/WNL.0b013e3181bd6b8f, indexed in Pubmed: 19949043.
  34. Guo AC, MacFall JR, Provenzale JM. Multiple sclerosis: diffusion tensor MR imaging for evaluation of normal-appearing white matter. Radiology. 2002; 222(3): 729–736, doi: 10.1148/radiol.2223010311, indexed in Pubmed: 11867792.
  35. Harrison DM, Roy S, Oh J, et al. Association of cortical lesion burden on 7-T magnetic resonance imaging with cognition and disability in multiple sclerosis. JAMA Neurol. 2015; 72(9): 1004–1012, doi: 10.1001/jamaneurol.2015.1241, indexed in Pubmed: 26192316.
  36. Manouchehri N, Stüve O. Choroid plexus volumetrics and brain inflammation in multiple sclerosis. Proc Natl Acad Sci U S A. 2021; 118(40), doi: 10.1073/pnas.2115221118, indexed in Pubmed: 34583997.
  37. Fleischer V, Gonzalez-Escamilla G, Ciolac D, et al. Translational value of choroid plexus imaging for tracking neuroinflammation in mice and humans. Proc Natl Acad Sci U S A. 2021; 118(36), doi: 10.1073/pnas.2025000118, indexed in Pubmed: 34479997.
  38. Reich DS, Lucchinetti CF, Calabresi PA. Multiple Sclerosis. N Engl J Med. 2018; 378(2): 169–180, doi: 10.1056/NEJMra1401483, indexed in Pubmed: 29320652.
  39. Absinta M, Sati P, Schindler M, et al. Persistent 7-tesla phase rim predicts poor outcome in new multiple sclerosis patient lesions. J Clin Invest. 2016; 126(7): 2597–2609, doi: 10.1172/JCI86198, indexed in Pubmed: 27270171.
  40. Wattjes MP, Ciccarelli O, Reich DS, et al. Magnetic Resonance Imaging in Multiple Sclerosis study group, Consortium of Multiple Sclerosis Centres, North American Imaging in Multiple Sclerosis Cooperative MRI guidelines working group. 2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol. 2021; 20(8): 653–670, doi: 10.1016/S1474-4422(21)00095-8, indexed in Pubmed: 34139157.
  41. Giovannoni G, Popescu V, Wuerfel J, et al. Smouldering multiple sclerosis: the ‘real MS’. Ther Adv Neurol Disord. 2022; 15: 17562864211066751, doi: 10.1177/17562864211066751, indexed in Pubmed: 35096143.
  42. Filippini G, Brusaferri F, Sibley WA, et al. Corticosteroids or ACTH for acute exacerbations in multiple sclerosis. Cochrane Database Syst Rev. 2000(4): CD001331, doi: 10.1002/14651858.CD001331, indexed in Pubmed: 11034713.
  43. Optic Neuritis Study Group. The 5-year risk of MS after optic neuritis. Experience of the optic neuritis treatment trial. Neurology. 1997; 49(5): 1404–1413, doi: 10.1212/wnl.49.5.1404, indexed in Pubmed: 9371930.
  44. Krieger S, Sorrells SF, Nickerson M, et al. Mechanistic insights into corticosteroids in multiple sclerosis: war horse or chameleon?. Clin Neurol Neurosurg. 2014; 119: 6–16, doi: 10.1016/j.clineuro.2013.12.021, indexed in Pubmed: 24635918.
  45. Paty DW, Li DK. Interferon beta-1b is effective in relapsing-remitting multiple sclerosis. I. Clinical results of a multicenter, randomized, double-blind, placebo-controlled trial. The IFNB Multiple Sclerosis Study Group. Neurology. 1993; 43(4): 655–661, doi: 10.1212/wnl.43.4.655, indexed in Pubmed: 8469318.
  46. Paty DW, Li DK. Interferon beta-1b is effective in relapsing-remitting multiple sclerosis. II. MRI analysis results of a multicenter, randomized, double-blind, placebo-controlled trial. UBC MS/MRI Study Group and the IFNB Multiple Sclerosis Study Group. Neurology. 1993; 43(4): 662–-667, doi: 10.1212/wnl.43.4.662, indexed in Pubmed: 8469319.
  47. Paty DW, McFarland H. Magnetic resonance techniques to monitor the long term evolution of multiple sclerosis pathology and to monitor definitive clinical trials. J Neurol Neurosurg Psychiatry. 1998; 64(Suppl 1): S47–51, indexed in Pubmed: 9647285.
  48. Johnson KP, Brooks BR, Cohen JA, et al. Copolymer 1 reduces relapse rate and improves disability in relapsing-remitting multiple sclerosis: results of a phase III multicenter, double-blind placebo-controlled trial. The Copolymer 1 Multiple Sclerosis Study Group. Neurology. 1995; 45(7): 1268–1276, doi: 10.1212/wnl.45.7.1268, indexed in Pubmed: 7617181.
  49. Dubey D, Kieseier BC, Hartung HP, et al. Dimethyl fumarate in relapsing-remitting multiple sclerosis: rationale, mechanisms of action, pharmacokinetics, efficacy and safety. Expert Rev Neurother. 2015; 15(4): 339–346, doi: 10.1586/14737175.2015.1025755, indexed in Pubmed: 25800129.
  50. O’Connor P, Wolinsky JS, Confavreux C, et al. TEMSO Trial Group. Randomized trial of oral teriflunomide for relapsing multiple sclerosis. N Engl J Med. 2011; 365(14): 1293–1303, doi: 10.1056/NEJMoa1014656, indexed in Pubmed: 21991951.
  51. Stüve O, Warnke C, Deason K, et al. CD19 as a molecular target in CNS autoimmunity. Acta Neuropathol. 2014; 128(2): 177–190, doi: 10.1007/s00401-014-1313-z, indexed in Pubmed: 24993505.
  52. Forsthuber TG, Cimbora DM, Ratchford JN, et al. B cell-based therapies in CNS autoimmunity: differentiating CD19 and CD20 as therapeutic targets. Ther Adv Neurol Disord. 2018; 11: 1756286418761697, doi: 10.1177/1756286418761697, indexed in Pubmed: 29593838.
  53. Calabresi PA, Radue EW, Goodin D, et al. Safety and efficacy of fingolimod in patients with relapsing-remitting multiple sclerosis (FREEDOMS II): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet Neurol. 2014; 13(6): 545–556, doi: 10.1016/S1474-4422(14)70049-3, indexed in Pubmed: 24685276.
  54. Shirani A, Stüve O. Natalizumab for multiple sclerosis: a case in point for the impact of translational neuroimmunology. J Immunol. 2017; 198(4): 1381–1386, doi: 10.4049/jimmunol.1601358, indexed in Pubmed: 28167648.
  55. Shirani A, Stüve O. Natalizumab: perspectives from the bench to bedside. Cold Spring Harb Perspect Med. 2018; 8(12), doi: 10.1101/cshperspect.a029066, indexed in Pubmed: 29500304.
  56. Salzer J, Svenningsson R, Alping P, et al. Rituximab in multiple sclerosis: A retrospective observational study on safety and efficacy. Neurology. 2016; 87(20): 2074–2081, doi: 10.1212/WNL.0000000000003331, indexed in Pubmed: 27760868.
  57. Hauser SL, Bar-Or A, Cohen JA, et al. ASCLEPIOS I and ASCLEPIOS II Trial Groups. Ofatumumab versus Teriflunomide in Multiple Sclerosis. N Engl J Med. 2020; 383(6): 546–557, doi: 10.1056/NEJMoa1917246, indexed in Pubmed: 32757523.
  58. Hauser SL, Bar-Or A, Comi G, et al. OPERA I and OPERA II Clinical Investigators. Ocrelizumab versus interferon beta-1a in relapsing multiple sclerosis. N Engl J Med. 2017; 376(3): 221–234, doi: 10.1056/NEJMoa1601277, indexed in Pubmed: 28002679.
  59. Kappos L, Bar-Or A, Cree BAC, et al. EXPAND Clinical Investigators. Siponimod versus placebo in secondary progressive multiple sclerosis (EXPAND): a double-blind, randomised, phase 3 study. Lancet. 2018; 391(10127): 1263–1273, doi: 10.1016/S0140-6736(18)30475-6, indexed in Pubmed: 29576505.
  60. Montalban X, Hauser SL, Kappos L, et al. ORATORIO Clinical Investigators. Ocrelizumab versus Placebo in Primary Progressive Multiple Sclerosis. N Engl J Med. 2017; 376(3): 209–220, doi: 10.1056/NEJMoa1606468, indexed in Pubmed: 28002688.
  61. Manouchehri N, Stüve O. Should ocrelizumab be used in non-active primary progressive multiple sclerosis? Time for a re-assessment. Ther Adv Neurol Disord. 2021; 14, doi: 10.1177/1756286421990500, indexed in Pubmed: 33796142.
  62. Lublin FD, Reingold SC. Placebo-controlled clinical trials in multiple sclerosis: ethical considerations. National Multiple Sclerosis Society (USA) Task Force on Placebo-Controlled Clinical Trials in MS. Ann Neurol. 2001; 49(5): 677–681, indexed in Pubmed: 11357961.
  63. Polman CH, Reingold SC, Barkhof F, et al. Ethics of placebo-controlled clinical trials in multiple sclerosis: a reassessment. Neurology. 2008; 70(13 Pt 2): 1134–1140, doi: 10.1212/01.wnl.0000306410.84794.4d, indexed in Pubmed: 18362273.
  64. Solomon AJ, Bernat JL. A review of the ethics of the use of placebo in clinical trials for relapsing-remitting multiple sclerosis therapeutics. Mult Scler Relat Disord. 2016; 7: 109–112, doi: 10.1016/j.msard.2016.03.019, indexed in Pubmed: 27237770.
  65. Calabresi PA, Kieseier BC, Arnold DL, et al. ADVANCE Study Investigators. Pegylated interferon β-1a for relapsing-remitting multiple sclerosis (ADVANCE): a randomised, phase 3, double-blind study. Lancet Neurol. 2014; 13(7): 657–665, doi: 10.1016/S1474-4422(14)70068-7, indexed in Pubmed: 24794721.
  66. Cohen JA, Coles AJ, Arnold DL, et al. CARE-MS I investigators. Alemtuzumab versus interferon beta 1a as first-line treatment for patients with relapsing-remitting multiple sclerosis: a randomised controlled phase 3 trial. Lancet. 2012; 380(9856): 1819–1828, doi: 10.1016/S0140-6736(12)61769-3, indexed in Pubmed: 23122652.
  67. Coles AJ, Twyman CL, Arnold DL, et al. CARE-MS II investigators. Alemtuzumab for patients with relapsing multiple sclerosis after disease-modifying therapy: a randomised controlled phase 3 trial. Lancet. 2012; 380(9856): 1829–1839, doi: 10.1016/S0140-6736(12)61768-1, indexed in Pubmed: 23122650.
  68. Kappos L, Wiendl H, Selmaj K, et al. Daclizumab HYP versus interferon beta-1a in relapsing multiple sclerosis. N Engl J Med. 2015; 373(15): 1418–1428, doi: 10.1056/NEJMoa1501481, indexed in Pubmed: 26444729.
  69. Comi G, Kappos L, Selmaj KW, et al. SUNBEAM Study Investigators. Safety and efficacy of ozanimod versus interferon beta-1a in relapsing multiple sclerosis (SUNBEAM): a multicentre, randomised, minimum 12-month, phase 3 trial. Lancet Neurol. 2019; 18(11): 1009–1020, doi: 10.1016/S1474-4422(19)30239-X, indexed in Pubmed: 31492651.
  70. Hu C, Dignam JJ. Biomarker-Driven oncology clinical trials: key design elements, types, features, and practical considerations. JCO Precis Oncol. 2019; 3, doi: 10.1200/PO.19.00086, indexed in Pubmed: 32923854.
  71. Sormani MP, Bruzzi P. MRI lesions as a surrogate for relapses in multiple sclerosis: a meta-analysis of randomised trials. Lancet Neurol. 2013; 12(7): 669–676, doi: 10.1016/S1474-4422(13)70103-0, indexed in Pubmed: 23743084.
  72. Cocozza S, Petracca M, Mormina E, et al. Cerebellar lobule atrophy and disability in progressive MS. J Neurol Neurosurg Psychiatry. 2017; 88(12): 1065–1072, doi: 10.1136/jnnp-2017-316448, indexed in Pubmed: 28844067.
  73. Bergsland N, Zivadinov R, Dwyer MG, et al. Localized atrophy of the thalamus and slowed cognitive processing speed in MS patients. Mult Scler. 2016; 22(10): 1327–1336, doi: 10.1177/1352458515616204, indexed in Pubmed: 26541795.
  74. Drexler W, Fujimoto JG. State-of-the-art retinal optical coherence tomography. Prog Retin Eye Res. 2008; 27(1): 45–88, doi: 10.1016/j.preteyeres.2007.07.005, indexed in Pubmed: 18036865.
  75. Manouchehri N, Zhang Y, Salter A, et al. Clinical trials in multiple sclerosis: potential future trial designs. Ther Adv Neurol Disord. 2019; 12, doi: 10.1177/1756286419847095, indexed in Pubmed: 31205492.
  76. Li V, Leurent B, Barkhof F, et al. Designing Multi-arm Multistage Adaptive Trials for Neuroprotection in Progressive Multiple Sclerosis. Neurology. 2022; 98(18): 754–764, doi: 10.1212/WNL.0000000000200604, indexed in Pubmed: 35321926.
  77. Barro C, Leocani L, Leppert D, et al. Fluid biomarker and electrophysiological outcome measures for progressive MS trials. Mult Scler. 2017; 23(12): 1600–1613, doi: 10.1177/1352458517732844, indexed in Pubmed: 29041870.
  78. Barro C, Benkert P, Disanto G, et al. Serum neurofilament as a predictor of disease worsening and brain and spinal cord atrophy in multiple sclerosis. Brain. 2018; 141(8): 2382–2391, doi: 10.1093/brain/awy154, indexed in Pubmed: 29860296.
  79. Novakova L, Zetterberg H, Sundström P, et al. Monitoring disease activity in multiple sclerosis using serum neurofilament light protein. Neurology. 2017; 89(22): 2230–2237, doi: 10.1212/WNL.0000000000004683, indexed in Pubmed: 29079686.