Should Upcoming Pivotal Trials in Multiple Sclerosis Choose “No-Evidence-of Disease Activity” as Outcome Measurement for the Primary Endpoint?

Author: Manolo E. Beelke

Email: [email protected]

Web: manolobeelke.com

Abstract

The evolution of multiple sclerosis (MS) therapies has driven a need for more comprehensive outcome measures to accurately gauge therapeutic success. Traditional metrics such as relapse rates, Expanded Disability Status Scale (EDSS) progression, and MRI markers face scrutiny for their limitations. This paper explores the potential of "No Evidence of Disease Activity" (NEDA) as a primary endpoint in MS clinical trials. NEDA, which integrates clinical and imaging-based outcomes, promises a more sensitive measure of therapeutic efficacy. This review discusses the definition and challenges of NEDA, its prognostic value, implications for study design, and potential applications in real-world settings. It also examines the relationship between current MS metrics and composite endpoints, providing a comprehensive analysis of NEDA’s role in future MS trials.

Introduction

The introduction of new and potent therapies for the treatment of relapsing-remitting multiple sclerosis (RRMS) has heightened the demand for robust measures of therapeutic success. Traditional outcome metrics such as relapse rates, EDSS progression, and MRI markers, while useful, have notable limitations. The need for more comprehensive and sensitive measures has led to the proposal of "No Evidence of Disease Activity" (NEDA) as a potential primary endpoint in clinical trials. This paper aims to explore the viability of NEDA in upcoming pivotal trials, examining its definition, challenges, prognostic value, and implications for study design.

Definition and Challenges of NEDA

NEDA status is classically defined by the absence of:

• any new or enlarging T2 lesions or T1 gadolinium-enhancing lesions on MRI,
• no sustained Expanded Disability Status Scale (EDSS) score progression, and
• no clinical relapses.

However, There is growing skepticism about the adequacy of solely using relapse rate reduction, Expanded Disability Status Scale (EDSS) progression, and magnetic resonance imaging (MRI) markers to monitor the new outcome measurement of 'no evidence of disease activity' (NEDA).

In addition, this composite measure brings several challenges:

• The parameters used to define NEDA may not be independent, as a new MRI lesion can predict future clinical relapses or EDSS progression.
• Combining multiple parameters can also lead to statistical challenges, such as multiplicity, which must be carefully managed to avoid false-positive results.
• Additionally, there is ongoing debate about which parameters should be included in NEDA and how each should be weighted to reflect their clinical importance accurately.

As a consequence, despite its potential, there is no universally accepted definition for NEDA. The parameters defining NEDA can vary, leading to different classifications such as NEDA-3, which considers absence of new MRI lesions, new clinical relapses, and EDSS progression, or NEDA-4, which also includes the absence of brain volume reduction. Some researchers propose incorporating additional neuropsychological factors (Stangel et al., 2015).

The selection of relevant parameters for assessing disease activity requires careful evaluation. Since some parameters are not independent of others, issues of multiplicity may arise. Thus, NEDA with its overlapping measurements can prevent the creation of a true composite parameter, necessitating a more nuanced approach to defining and using NEDA in clinical trials.

NEDA in Different Stages in the Disease Course of MS

NEDA's sensitivity as an outcome measure varies across different stages of MS, including Radiologically Isolated Syndrome (RIS), Clinically Isolated Syndrome (CIS), Relapsing-Remitting MS (RRMS), Secondary Progressive MS (SPMS), and potentially Primary Progressive MS (PPMS).

In RIS, characterized by MRI findings suggestive of MS without clinical symptoms, the application of NEDA is challenging because the condition is often asymptomatic. Achieving NEDA in RIS could potentially delay or prevent progression to CIS or RRMS, although the clinical relevance of NEDA in RIS requires further validation (Szilasiová et al., 2021).

CIS, which represents the first clinical episode suggestive of MS, in therory there would be potential benefits from using NEDA as it could provide early insights into the effectiveness of treatment and may predict the likelihood of progression to definite MS. However, CIS is characterized by the first-ever clinical event in the absence of the fulfillment of the diagnostic criteria for MS, which requires clinical or imaging proof for dissemination in space and time. Studies have shown that achieving NEDA in CIS can delay the transition to RRMS by preventing new clinical attacks and MRI activity (Rotstein et al., 2015).

In RRMS, NEDA's sensitivity is highest, making it a robust indicator of effective disease control. Achieving NEDA in RRMS is associated with better long-term outcomes. High-efficacy disease-modifying therapies (DMTs) such as Ocrelizumab and Natalizumab significantly increase the likelihood of achieving NEDA, reducing the risk of relapses and progression (Signoriello et al., 2024).

Figure 1 illustrates how disease activity varies across different stages of MS. In early stages like CIS, clinical or imaging proof is required for diagnosis, making NEDA less sensitive. As the disease progresses, the sensitivity of NEDA increases, particularly in RRMS with high baseline activity.

Within the stage of RRMS, the sensitivity of NEDA depends however also on the disease activity (Figure 2):

• High Disease Activity: In populations with high baseline disease activity, NEDA is more likely to detect meaningful changes.
• Low Disease Activity: In low disease activity populations, achieving NEDA may be more common, potentially masking the true efficacy of the treatment being tested.

For SPMS, achieving NEDA is more challenging due to the progressive nature of the disease. The focus in SPMS shifts towards preventing further disability progression and MRI activity. High-efficacy therapies may help in maintaining NEDA, but their effectiveness may vary based on the stage of SPMS (Prosperini et al., 2021).

In PPMS, characterized by continuous neurological decline from onset without distinct relapses, the concept of NEDA is less well-defined. Instead, NEDA in PPMS would focus on preventing MRI activity and halting disability progression. Achieving NEDA in PPMS is particularly challenging, and ongoing research is needed to better define and measure disease activity in this subtype (Arnold et al., 2014).

Relationship to the Concept of Remission

Achieving a 'disease activity free' (DAF) status is a key treatment goal for MS patients, suggesting the absence of any disease activity. However, since no outcome measurement can completely exclude disease activity, it is proposed to describe this status as 'no evidence of disease activity' (NEDA). Including MS-related brain shrinkage as a fourth measure captures underlying damage that begins early in MS and is associated with loss of function (Giovannoni et al., 2011).

Prognostic Value of NEDA

NEDA is valuable not only as an immediate measure of disease control but also as a prognostic marker. Studies have shown that achieving NEDA at two years can predict disability outcomes at seven years almost as well as at five years (Rotstein et al., 2015). This long-term prognostic value makes NEDA an attractive endpoint for clinical trials, providing early indicators of long-term treatment success.

Additionally, Prosperini et al. (2021) found that achieving NEDA-3 in the initial years of treatment predicts better long-term outcomes in RRMS patients, including reduced risk of relapse-associated worsening and sustained disease stability.

Current MS Metrics for Efficacy and Challenges

The traditional metrics for measuring MS treatment efficacy include the occurrence of relapses, EDSS progression, and MRI lesions. These metrics have inherent limitations when used individually. Relapses indicate acute inflammation and demyelination but are relatively rare events. EDSS measures sustained disability progression but is insensitive, particularly in its lower ranges. MRI is highly sensitive to detecting subclinical disease activity but has a weak correlation with clinical outcomes. As such, these metrics may not fully capture the efficacy of a treatment.

A significant challenge in decision-making for multiple sclerosis (MS) treatment is the lack of a comprehensive understanding that differentiates the meanings among current MS efficacy metrics. These metrics include:

• Occurrence of relapses
• EDSS progression
• MRI lesions
• Gd-enhancing lesions
• T2 lesions
• Brain volume reduction

Achieving freedom from any of these metrics is the therapeutic aim of all MS treatments to date. However, to improve upon current study designs, statistical power can no longer rely solely on demonstrating a difference in relapse rates. A multifaceted approach that considers the complexity and interrelation of these metrics is essential for advancing MS treatment efficacy evaluations.

Implications for Study Design

The concept of Disease Activity Free (DAF) status, or as recently proposed, No-Evidence of Disease Activity (NEDA) status, offers a more sensitive efficacy measurement than traditional parameters alone. This sensitivity is critical given the current landscape of multiple sclerosis (MS) trials, which often see very low event rates, particularly relapses. This statistical challenge is compounded by the fact that actual populations are treating subjects very early after MS diagnosis.

However, several questions remain open:

• Is DAF (or NEDA) more sensitive to changes over time?
• Are these measures as clinically useful as others proposed?
• Should they be used in conjunction with other traditional measures, or ranked in importance?
• Are patient eligibility criteria different from those historically requested?
• Will we require fewer patients to see differences?
• Will we need less time to see those differences compared to other endpoints?

Composite Endpoints in Clinical Trials: Regulatory Perspectives and Requirements

Composite endpoints have been useful in clinical trials for providing a more comprehensive measure of treatment effects. The ICH E9 guideline and EMA's "Points to Consider on Multiplicity Issues in Clinical Trials" provide a framework for their use.

According to this document, the use of a composite endpoint in a clinical trial is justified if the following assumptions are respected:

• Clinical Meaningfulness and Importance: The individual components of the composite must be clinically meaningful and of similar importance to the patient (Freemantle et al., 2003).
• Expected Effects and Biological Plausibility: The expected effects on each component should be similar, based on biological plausibility (Montori and Miralda, 2005). Regulatory guidelines also require that the components should be those for which it can be assumed the treatment will beneficially influence in a similar way.
• Impact on Clinically Important Components: The clinically more important components of composite endpoints should at least not be negatively affected (CPMP, "Points to Consider on Multiplicity Issues in Clinical Trials," 2005).

As a consequence of the third assumption, regulatory authorities mandate that all components of a composite endpoint be analyzed separately (ICH E9, 2005; CPMP, 2005). This separate analysis is crucial to determine whether a treatment affects all components or merely a single outcome (Montori and Miralda, 2005). This approach ensures a comprehensive understanding of the treatment's impact and supports informed decision-making in the development and approval of new pharmaceuticals.

Disease Activity Parameters in Conducted Studiess

Evidence of disease activity depends directly on the parameter used for measurement. Disease disability, as measured by the Expanded Disability Status Scale (EDSS), develops very slowly, and a duration of two years is often insufficient to show confirmed disease progression. Consequently, this parameter is less sensitive to treatment-related changes and has the lowest likelihood of showing disease activity within two years.

Relapse rates and related variables are rare events, occurring only if specific cortical or subcortical brain areas are involved, producing clinically visible symptoms or signs. Similar to disability progression measurement, relapse rates highlight only the surface of MS activity.

Data from various studies underscore the utility of NEDA in different stages of MS.

High-efficacy therapies such as Ocrelizumab and Natalizumab significantly enhance the likelihood of achieving NEDA-3 in early MS stages. A study by Signoriello et al. (2024) indicates that these therapies are superior to traditional treatments in controlling disease activity, reducing the risk of relapses, and progression.

Another study by Saied et al. (2019) reviews the long-term effects of corticosteroids in MS in terms of the NEDA domains, highlighting their role in managing acute relapses but questioning their contribution to sustained NEDA status. The limitations of long-term corticosteroid use underscore the need for comprehensive therapeutic strategies.

The Ponesimod versus Teriflunomide comparison in the OPTIMUM study by Kappos et al. (2021) demonstrates comparable efficacy of both treatments in achieving NEDA-3, highlighting their suitability as oral DMTs for managing relapsing MS.

A phase 2 study of ublituximab by Fox et al. (2021) highlights the high efficacy of this novel therapy in achieving NEDA status, supporting its potential as a promising treatment option for relapsing MS.

Moreover, Szilasiová et al. (2021) demonstrated that plasma neurofilament light chain levels correlate with disease activity as defined by NEDA status, suggesting their utility as biomarkers for monitoring disease progression.

In pediatric MS, a study by Palavra et al. (2023) identified clinical predictors of achieving NEDA-3 within the first year of diagnosis, offering insights into early disease management strategies. Early use of therapies like natalizumab and the absence of certain antibodies were significant predictors.

Finally, Rotstein et al. (2022) conducted a systematic review and meta-analysis comparing NEDA-4 with NEDA-3, finding that NEDA-4, which includes brain volume loss, shows promise in predicting long-term disability progression and may be a more stringent treatment target.

MRI as a Sensitive Parameter

MRI appears to be the most sensitive parameter, detecting disease activity even in clinically silent cases. Due to its higher sensitivity, attempts to correlate MRI lesions with clinical evidence of disease activity have produced lower correlation values compared to clinical parameters. Therefore, health authorities have not accepted MRI as a surrogate marker for clinical disease activity (see Guideline on Clinical Investigation of Medicinal Products for the Treatment of Multiple Sclerosis, section 6.3).

However, MRI lesion load has shown prognostic value for clinical outcomes after several months (e.g., Sormani et al., 2010). The correlation is stronger between relapse rate and EDSS than between MRI and EDSS progression. Despite this, MRI is still not accepted as a surrogate marker for clinical development in MS, and its prognostic value exists only at the trial level, not on an individual level. Thus, MRI parameters cannot be used in the individual management of MS patients.

Patient Selection and Sensitivity of DAF/NEDA

During the screening period, a population with high disease activity can be specifically selected. This can be achieved using a prolonged screening period, or run-in period, where disease activity is measured through monthly MRI scans over 1-3 months. In a population with low baseline disease activity, the number of subjects achieving NEDA would be higher compared to a population with high disease activity, independent of the study drug's effect.

In clinically isolated syndrome (CIS), NEDA is not a sensitive outcome measurement. Therefore, time-to-event analysis is standard, with efficacy endpoints traditionally being time-to-clinical diagnosis of MS (CDMS), and later time-to-diagnosis of MS according to the updated McDonald criteria (McDonald 2010).

Figure 3 represents the percnetage of patients with absence of key disease activity parameters across four significant multiple sclerosis studies: PRISMS, CLARITY, AFFIRM, and FREEDOM. The parameters analyzed include relapse rates, EDSS progression, new MRI lesions, Gd-enhancing lesions, T2 lesions, and brain volume reduction.

As shown in Figure 2, the evidence of disease activity is directly dependent on the choice of parameter used to measure it. Disease disability, as measured by the Expanded Disability Status Scale (EDSS), develops very slowly over time, and a duration of two years is often insufficient to show confirmed disease progression. Consequently, EDSS is the least sensitive parameter for showing disease activity changes related to treatment with a disease-modifying drug (DMD). This parameter also has the lowest likelihood of showing disease activity within two years. The absence of disease activity does not necessarily indicate that the effect is due to the action of an investigational medicinal product (IMP).

Relapse rates and any variables derived from this parameter are rare events. The occurrence of a relapse is measured only if specific cortical or subcortical areas of the brain, capable of producing clinically visible symptoms or signs, are involved. Similar to disability progression measurement, relapse rates highlight only the surface of MS activity.

MRI appears to be the most sensitive parameter, detecting disease activity even in clinically silent cases. Due to its higher sensitivity, attempts to correlate MRI lesions with clinical evidence of disease activity have produced lower correlation values compared to clinical parameters. Consequently, health authorities have not accepted MRI as a surrogate marker for clinical disease activity (see Guideline on Clinical Investigation of Medicinal Products for the Treatment of Multiple Sclerosis, section 6.3). However, MRI lesion load has shown prognostic value for clinical outcomes after several months (Sormani et al., 2010). The correlation is stronger between relapse rate and EDSS than between MRI and EDSS progression. Despite this, MRI is still not accepted as a surrogate marker for clinical development in MS. Furthermore, the prognostic value of MRI as a surrogate marker exists only at the trial level, not at the individual level. Thus, MRI parameters cannot be used in the individual management of MS patients.

The findings are summerized in Table 1

While the absence of disease acitivy parameter might focus only on a subpopulation that reaches an ideal condition, the limitations in extrapolating results to the generalized population might be acceptable. This concept is also used in other conditions to imply "remission." The meaning of this concept is driven by the risk of continued activity in comparators, making it a probabilistic approach to maintain disease activity-free status. Examples come from other therapeutic areas such as migraine, epilepsy, and inflammatory bowel disease.

Though the DAF/NEDA parameter might apply only to a subpopulation that reaches an ideal condition, this limitation in extrapolating results to the generalized population might be acceptable. This concept is used in other conditions to imply "remission," driven by the risk of continued activity in comparators, making it a probabilistic approach to maintaining disease-free status. Examples come from other therapeutic areas such as migraine, epilepsy, and inflammatory bowel disease.

Optimizing study design for MS trials by incorporating DAF/NEDA status involves addressing several critical questions and considerations regarding patient selection, sensitivity of parameters, and statistical challenges. The adoption of MRI as a sensitive measure, despite its current limitations, and the comparison to other therapeutic areas, highlight the evolving landscape of MS research and the potential for improved patient outcomes.

Data from the CLARITY study show in Figure 4 that approximately 2/3 of treated patients who achieved NEDA at 24 weeks remained free from disease activity at 96 weeks, highlighting the stability and prognostic value of NEDA (Giovannoni et al., 2011).

Additionally, a study by Prosperini et al. (2021) found that achieving NEDA-3 in the initial years of treatment predicts better long-term outcomes in RRMS patients.

Potential Applications in Real-World Settings with Examples from Other Therapeutic Areas

Real-world data from Bazzurri et al. (2023) show varying prevalence rates of NEDA-3 and NEDA-4 over two years in RRMS patients, reflecting the effectiveness of DMTs in clinical practice. This study underscores the importance of incorporating brain volume loss as an additional measure in NEDA-4 to provide a more comprehensive assessment of treatment efficacy.

The concept of DAF (or NEDA) has potential applications in real-world settings beyond MS, particularly in other therapeutic areas such as cardiovascular disease. In cardiovascular disease, achieving a status free from disease activity involves maintaining blood pressure within target ranges, preventing the occurrence of new cardiovascular events, and avoiding hospitalizations related to heart failure or other complications.

Hypertension Management

For example, in the management of hypertension, the goal is to achieve and maintain target blood pressure levels without the need for medication escalation. This involves:

• Regular monitoring of blood pressure.
• Lifestyle modifications such as diet and exercise.
• Medications to maintain blood pressure within the target range. Achieving these targets without requiring increased medication doses or hospital visits could be considered a "no evidence of disease activity" status for hypertension.

Coronary Artery Disease Management

In the context of coronary artery disease, the objective is to prevent new myocardial infarctions and manage existing conditions to avoid progression. This involves:

• Regular cardiac evaluations.
• Medications such as statins and antiplatelets to manage cholesterol and prevent clot formation.
• Lifestyle changes to improve heart health. A composite endpoint approach could integrate these measures, providing a comprehensive assessment of disease activity similar to NEDA in MS.

Diabetes Management

In diabetes, achieving a disease activity-free status would involve maintaining glycemic control within target ranges without the need for increased medication. This could include:

• Regular monitoring of blood glucose levels.
• Maintaining HbA1c levels within the target range.
• Avoiding episodes of hyperglycemia or hypoglycemia.
• Implementing lifestyle changes such as diet and exercise.

This composite measure could help in evaluating the overall management of diabetes, similar to the NEDA approach in MS.

Conclusion

NEDA represents a promising composite endpoint for future MS clinical trials, potentially offering a more sensitive measure of therapeutic efficacy than traditional metrics alone. Its application could improve the assessment of new treatments, although challenges such as statistical power, parameter independence, and placebo response rates must be addressed. The potential application of the NEDA concept to other therapeutic areas further underscores its utility in clinical research.

NEDA has proven to be a useful tool in both clinical practice and clinical trials. Recent studies highlight its significance. For instance, a narrative review by Newsome et al. (2023) emphasizes the value of NEDA from both clinician and patient perspectives, noting how high-efficacy therapies are driving a shift in MS management towards achieving NEDA. Achieving NEDA can lead to better long-term outcomes and improved quality of life for patients.

These results and insights collectively underscore the evolving role of NEDA in MS management, emphasizing the importance of early intervention with high-efficacy therapies and the use of biomarkers to monitor disease activity and treatment response effectively.Implications for Study Design

The concept of NEDA as a primary endpoint has several implications for study design. Patient selection is critical, with a focus on identifying high disease activity populations during the screening period. NEDA is more sensitive to changes in populations with higher baseline disease activity. The combined nature of NEDA may require fewer patients to detect significant differences, but careful consideration of statistical power is necessary to account for the complexity of the endpoint.

By incorporating a broader range of disease activity markers and patient-centered outcomes, NEDA could provide a more comprehensive and meaningful measure of treatment success. Continued research and refinement of this composite endpoint will be crucial to fully realize its potential in improving clinical trial outcomes and patient care in multiple sclerosis and beyond.

FAQs

What is NEDA in multiple sclerosis?

NEDA stands for "No Evidence of Disease Activity" and is a composite measure used in multiple sclerosis to indicate the absence of relapses, MRI activity, and disability progression.

How is NEDA measured?

NEDA is measured by assessing the absence of new or enlarging T2 lesions or T1 gadolinium-enhancing lesions on MRI, no sustained EDSS score progression, and no clinical relapses over a specified period.

Why is NEDA important in MS clinical trials?

NEDA is important in MS clinical trials because it provides a comprehensive measure of disease activity, helping to evaluate the efficacy of new therapies more accurately than individual metrics alone.

What are the limitations of using NEDA as an endpoint?

The limitations of using NEDA as an endpoint include its dependence on multiple parameters that may not be entirely independent of each other, issues with statistical power, and the increasing rate of NEDA in placebo populations.

Can NEDA be applied to other diseases?

Yes, the concept of NEDA can potentially be applied to other diseases, such as cardiovascular disease, where a composite endpoint of disease activity-free status could be used to gauge therapeutic efficacy.

What is the prognostic value of NEDA in MS?

Research indicates that achieving NEDA status can predict disability outcomes at 7 years almost as well as at 5 years, suggesting it has significant midterm prognostic value.

References

• Arnold, D. L., Calabresi, P. A., Kieseier, B. C., Sheikh, S. I., Deykin, A., Zhu, Y., ... & Hung, S. (2014). Effect of peginterferon beta-1a on MRI measures and achieving no evidence of disease activity: results from a randomized controlled trial in relapsing-remitting multiple sclerosis. BMC Neurology, 14(1), 1058. [PubMed](https://pubmed.ncbi.nlm.nih.gov/25551571/)
• Bazzurri, V., Fiore, A., Curti, E., Tsantes, E., Franceschini, A., & Granella, F. (2023). Prevalence of 2-year "No evidence of disease activity" (NEDA-3 and NEDA-4) in relapsing-remitting multiple sclerosis. A real-world study. Mult Scler Relat Disord, 79, 105015. https://doi.org/10.1016/j.msard.2023.105015
• CPMP (2005). Points to Consider on Multiplicity Issues in Clinical Trials. European Medicines Agency. Retrieved from EMA website.
• De Stefano, N., Giorgio, A., Battaglini, M., Rovaris, M., Sormani, M. P., Barkhof, F., ... & Filippi, M. (2010). Assessing brain atrophy rates in a large population of untreated multiple sclerosis subtypes. Neurology, 74(23), 1868-1876. [PubMed](https://pubmed.ncbi.nlm.nih.gov/20530323/)
• Fox, E., Lovett-Racke, A. E., Gormley, M., Liu, Y., Petracca, M., Cocozza, S., Shubin, R., Wray, S., Weiss, M. S., Bosco, J. A., Power, S. A., Mok, K., Inglese, M. (2021). A phase 2 multicenter study of ublituximab, a novel glycoengineered anti-CD20 monoclonal antibody, in patients with relapsing forms of multiple sclerosis. Mult Scler, 27(3), 420-429. https://doi.org/10.1177/1352458520918375
• Freemantle, N., Calvert, M., Wood, J., Eastaugh, J., & Griffin, C. (2003). Composite outcomes in randomized trials: Greater precision but with greater uncertainty? Journal of the American Medical Association, 289(19), 2554-2559. [PubMed](https://pubmed.ncbi.nlm.nih.gov/12759327/)
• Giovannoni, G., Cook, S., Rammohan, K., Rieckmann, P., S?rensen, P. S., Vermersch, P., ... & Greenberg, S. (2011). Sustained disease-activity-free status in patients with relapsing-remitting multiple sclerosis treated with cladribine tablets in the CLARITY study: a post-hoc and subgroup analysis. Lancet Neurology, 10(4), 329-37. [PubMed](https://pubmed.ncbi.nlm.nih.gov/21397565/)
• Harrison, D. M., Gladstone, D. E., Hammond, E., Cheng, J., Jones, R. J., Brodsky, R. A., ... & Kaplin, A. (2012). Treatment of relapsing-remitting multiple sclerosis with high-dose cyclophosphamide induction followed by glatiramer acetate maintenance. Multiple Sclerosis Journal, 18(2), 202-209. [PubMed](https://pubmed.ncbi.nlm.nih.gov/21865410/)
• Havrdova, E., Giovannoni, G., Stefoski, D., Forster, S., Umans, K., Mehta, L., ... & Elkins, J. (2014). Disease-activity-free status in patients with relapsing-remitting multiple sclerosis treated with daclizumab high-yield process in the SELECT study. Multiple Sclerosis Journal, 20(4), 464-470. [PubMed](https://pubmed.ncbi.nlm.nih.gov/24022270/)
• Imitola, J., & Racke, M. K. (2015). Is no evidence of disease activity a realistic goal for patients with multiple sclerosis? JAMA Neurology, 72(2), 145-147. [PubMed](https://pubmed.ncbi.nlm.nih.gov/25531742/)
• Inusah, S., Sormani, M. P., Cofield, S. S., Aban, I. B., Musani, S. K., Srinivasasainagendra, V., & Cutter, G. R. (2010). Assessing changes in relapse rates in multiple sclerosis. Multiple Sclerosis Journal, 16(12), 1414-1421. [PubMed](https://pubmed.ncbi.nlm.nih.gov/20810517/)
• Kappos, L., Fox, R. J., Burcklen, M., Freedman, M. S., Havrdová, E. K., Hennessy, B., Hohlfeld, R., Lublin, F., Montalban, X., Pozzilli, C., Scherz, T., D'Ambrosio, D., Linscheid, P., Vaclavkova, A., Pirozek-Lawniczek, M., Kracker, H., & Sprenger, T. (2021). Ponesimod Compared With Teriflunomide in Patients With Relapsing Multiple Sclerosis in the Active-Comparator Phase 3 OPTIMUM Study: A Randomized Clinical Trial. JAMA Neurol, 78(5), 558-567. https://doi.org/10.1001/jamaneurol.2021.0405
• Massey, J. C., Sutton, I. J., Ma, D. D. F., & Moore, J. J. (2018). Regenerating Immunotolerance in Multiple Sclerosis with Autologous Hematopoietic Stem Cell Transplant. Frontiers in Immunology, 9. https://doi.org/10.3389/fimmu.2018.00410. ISSN: 1664-3224.
• Montori, V. M., & Miralda, G. (2005). Selecting composite endpoints for clinical trials. Journal of Clinical Epidemiology, 58(11), 1103-1111. [PubMed](https://pubmed.ncbi.nlm.nih.gov/16223626/)
• Newsome, S. D., Binns, C., Kaunzner, U. W., Morgan, S., & Halper, J. (2023). No Evidence of Disease Activity (NEDA) as a Clinical Assessment Tool for Multiple Sclerosis: Clinician and Patient Perspectives. Neurol Ther, 12(6), 1909-1935. https://doi.org/10.1007/s40120-023-00549-7
• Nixon, R., Bergvall, N., Tomic, D., Sfikas, N., Cutter, G., & Giovannoni, G. (2014). No evidence of disease activity: indirect comparisons of oral therapies for the treatment of relapsing-remitting multiple sclerosis. Advances in Therapy, 31(11), 1134-1154. [PubMed](https://pubmed.ncbi.nlm.nih.gov/25414048/)
• Palavra, F., Silva, D., Fernandes, C., Faustino, R., Vasconcelos, M., Pereira, C., Costa, C., Ribeiro, J. A., Amaral, J., & Robalo, C. (2023). Clinical predictors of NEDA-3 one year after diagnosis of pediatric multiple sclerosis: an exploratory single-center study. Front Neurosci, 17, 1259306. https://doi.org/10.3389/fnins.2023.1259306
• Prosperini, L., Ruggieri, S., Haggiag, S., Tortorella, C., Pozzilli, C., & Gasperini, C. (2021). Prognostic Accuracy of NEDA-3 in Long-term Outcomes of Multiple Sclerosis. Neurol Neuroimmunol Neuroinflamm, 8(6), e1059. https://doi.org/10.1212/NXI.0000000000001059
• Rotstein, D. L., Healy, B. C., Malik, M. T., Chitnis, T., & Weiner, H. L. (2015). Evaluation of no evidence of disease activity in a 7-year longitudinal multiple sclerosis cohort. JAMA Neurology, 72(2), 152-158. [PubMed](https://pubmed.ncbi.nlm.nih.gov/25531931/)
• Rotstein, D., Solomon, J. M., Sormani, M. P., Montalban, X., Ye, X. Y., Dababneh, D., Muccilli, A., Saab, G., & Shah, P. (2022). Association of NEDA-4 With No Long-term Disability Progression in Multiple Sclerosis and Comparison With NEDA-3: A Systematic Review and Meta-analysis. Neurol Neuroimmunol Neuroinflamm, 9(6), e200032. https://doi.org/10.1212/NXI.0000000000200032
• Saied, A., Elsaid, N., & Azab, A. (2019). Long term effects of corticosteroids in multiple sclerosis in terms of the "no evidence of disease activity" (NEDA) domains. Steroids, 149, 108401. https://doi.org/10.1016/j.steroids.2019.04.006
• Signoriello, E., Signori, A., Lus, G., Romano, G., Marfia, G. A., Landi, D., Napoli, F., D' Amico, E., Zanghí, A., Di Filippo, P. S., Caliendo, D., Carotenuto, A., Spiezia, A. L., Fantozzi, R., Centonze, D., Lucchini, M., Mirabella, M., Cocco, E., Frau, J., Maniscalco, G. T., Di Battista, M. E., Foschi, M., Surcinelli, A., Bonavita, S., Abbadessa, G., Pasquali, L., Di Gregorio, M., Ferrò, M. T., Sormani, M. P., & Schiavetti, I. (2024). NEDA-3 achievement in early highly active relapsing remitting multiple sclerosis patients treated with Ocrelizumab or Natalizumab. Mult Scler Relat Disord, 87, 105594. https://doi.org/10.1016/j.msard.2024.105594
• Sormani, M. P., Bonzano, L., Roccatagliata, L., Mancardi, G. L., Uccelli, A., & Bruzzi, P. (2010). Surrogate endpoints for EDSS worsening in multiple sclerosis: A meta-analytic approach. Neurology, 75(4), 302-309. [PubMed](https://pubmed.ncbi.nlm.nih.gov/20574036/)
• Stangel, M., Penner, I. K., Kallmann, B. A., Lukas, C., & Kieseier, B. C. (2015). Towards the implementation of “no evidence of disease activity” in multiple sclerosis treatment: the multiple sclerosis decision model. Therapeutic Advances in Neurological Disorders, 8(1), 3-13. [PubMed](https://pubmed.ncbi.nlm.nih.gov/25414048/)
• Szilasiová, J., Mikula, P., Rosenberger, J., Fedi?ová, M., Gdovinová, Z., Urban, P., & Frigová, L. (2021). Plasma neurofilament light chain levels are predictors of disease activity in multiple sclerosis as measured by four-domain NEDA status, including brain volume loss. Mult Scler, 27(13), 2023-2030. https://doi.org/10.1177/1352458521998039
• Uitdehaag, B. M., Barkhof, F., Coyle, P. K., Gardner, J. D., Jeffery, D. R., & Mikol, D. D. (2011). The changing face of multiple sclerosis clinical trial populations. Current Medical Research and Opinion, 27(8), 1529-1537. [PubMed](https://pubmed.ncbi.nlm.nih.gov/21671851/)