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Ocrelizumab vs Ofatumumab: Relapse and Disability Outcomes (public)

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September 4, 2025

What is the annualized relapse rate and confirmed disability progression with ocrelizumab vs ofatumumab in registry data?

In registry studies, ocrelizumab and ofatumumab show comparable annualized relapse rates (0.059 vs 0.038, p = 0.185) and both achieve 0% confirmed disability progression at 12 months.

Abstract

Registry studies in multiple sclerosis report that ocrelizumab and ofatumumab yield comparable outcomes. In one large, multicenter, propensity‐matched study (Zanghì et al., 2024), the annualized relapse rate was 0.059 with ocrelizumab versus 0.038 with ofatumumab (p = 0.185), and both treatments showed 0% confirmed disability progression over 12 months. A small post–natalizumab cohort (Cunha et al., 2025) likewise observed no significant change in relapse rate or in Expanded Disability Status Scale scores between ocrelizumab and ofatumumab. Other registry reports of ocrelizumab document relapse rates ranging from 0.014 to 0.11, with very low rates of confirmed disability progression over follow-up intervals from 6 months to several years.

These findings indicate that, based on available registry data, ocrelizumab and ofatumumab produce similar outcomes in annualized relapse rate and short-term disability progression among patients with multiple sclerosis.

Methods

We analyzed 40 sources from an initial pool of 999, using 8 screening criteria. Each paper was reviewed for 7 key aspects that mattered most to the research question. More on methods

Papers identified with Elicit search

n = 999

Papers screened using: Multiple Sclerosis Population, Target Medications, Real-World Data Source, Relevant Outcomes, Appropriate Study Design, MS-Focused Study, Adequate Study Type, Adult or Mixed Population

n = 999

Papers screened out

n = 959

Papers included for extraction

n = 40

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Paper search

Using your research question “What is the annualized relapse rate and confirmed disability progression with ocrelizumab vs ofatumumab in registry data?”, we searched across over 126 million academic papers from the Semantic Scholar corpus. We retrieved the 999 papers most relevant to the query.

Screening

We screened in sources based on their abstracts that met these criteria:

• Multiple Sclerosis Population: Does this study include patients with multiple sclerosis (any subtype)?
• Target Medications: Does this study report outcomes for patients treated with ocrelizumab and/or ofatumumab, allowing for direct or indirect comparison between these treatments?
• Real-World Data Source: Does this study utilize registry data, real-world databases, or observational cohorts (rather than randomized controlled trials)?
• Relevant Outcomes: Does this study report annualized relapse rate and/or confirmed disability progression?
• Appropriate Study Design: Is this study an observational study (cohort study, case-control study), systematic review, or meta-analysis?
• MS-Focused Study: Is this study NOT focusing exclusively on conditions other than multiple sclerosis?
• Adequate Study Type: Is this study NOT a case report, case series, editorial, letter, or conference abstract?
• Adult or Mixed Population: Is this study NOT focusing exclusively on pediatric populations?

We considered all screening questions together and made a holistic judgement about whether to screen in each paper.

Data extraction

We asked a large language model to extract each data column below from each paper. We gave the model the extraction instructions shown below for each column.

• Study Design:

Identify and extract the specific type of study design. Look in the methods section for details such as:

• Retrospective or prospective
• Observational (registry, cohort) or interventional
• Multicenter or single-center
• Matching method used (e.g., propensity score matching)

If multiple design characteristics are present, list all. If unclear, note “design not clearly specified”. Prioritize the most specific description of the study design.

• Patient Population Characteristics:

Extract key patient demographic and clinical characteristics:

• Total number of patients
• Mean/median age
• Gender distribution
• Multiple sclerosis type (RRMS, PPMS, aSPMS)
• Mean disease duration
• Baseline Expanded Disability Status Scale (EDSS) score
• Treatment-naive status vs. previous treatment history

If ranges or confidence intervals are provided, include those. If data is missing for any characteristic, note “not reported”.

• Interventions Compared:

List the specific treatments being compared:

• Drug names
• Dosage (if specified)
• Treatment duration
• Number of patients in each treatment group

If multiple comparisons were made, list all. Ensure the interventions match the research question (ocrelizumab vs ofatumumab).

• Annualized Relapse Rate (ARR):

Extract ARR data:

• Baseline ARR
• On-treatment ARR
• Confidence intervals
• Statistical significance of differences between groups

Record the exact numerical values and confidence intervals. If ARR is reported differently (e.g., percentage of relapse-free patients), note this explicitly.

• Disability Progression:

Extract confirmed disability progression data:

• Method of measuring disability progression (e.g., 12-week confirmed disability progression)
• Percentage of patients with disability progression
• Changes in EDSS score
• Statistical significance of differences between groups

If multiple time points are reported, prioritize the primary follow-up period specified in the study.

• Follow-up Duration:

Record:

• Total follow-up period
• Median follow-up time
• Range of follow-up times

If multiple follow-up periods are reported, note the primary analysis period. If not clearly specified, note “follow-up duration not clearly reported”.

• Safety Outcomes:

Extract information on:

• Treatment-related side effects
• Infection rates
• Infusion-related reactions
• Any serious adverse events

If no safety issues are reported, explicitly note “no significant safety concerns reported”. Quantify side effects if possible (percentage of patients affected).

Results

Characteristics of Included Studies

Study

Study Design

Registry Source

Population Size

Follow-up Duration

Full text retrieved

Zanghì et al., 2024

Retrospective cohort, multicenter, propensity-matched

Italian multiple sclerosis centers

396 (ocrelizumab: 216, ofatumumab: 180)

Mean 13.2 months

Yes

Zhu et al., 2022

Retrospective, multicenter, inverse probability of treatment weighting, registry

MSBase

1045

ocrelizumab: median 1.8 years; cladribine: 1.1 years; natalizumab: 3.6 years

Yes

Ghajarzadeh et al., 2025

Systematic review/meta-analysis

Multiple

No mention found

No mention found

No

Cunha et al., 2025

Retrospective cohort

No mention found

59

No mention found

No

Epstein et al., 2021

Retrospective chart review

No mention found

56

2 years

No

Ellwardt et al., 2020

Retrospective, multicenter, observational

3 neurology centers

210

Median 200 days (range 30–1674)

No

Cellerino et al., 2021

Prospective, single-center, observational

No mention found

153

Median 1.9 years (1.3–2.7)

Yes

Muros-Le Rouzic et al., 2024

Retrospective, registry, multicenter, propensity score matching

OPERA, NTD

611 (OPERA), 7141 (NTD)

5.5 years

No

Zhu et al., 2023

Retrospective, multicenter, inverse probability of treatment weighting, registry

MSBase

1386

Median 2.7 years

Yes

Schuldesz et al., 2025

Prospective, single-center, cohort

No mention found

98

2 years

No

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Summary of study characteristics:

• Study design:
  • 28 studies were retrospective.
  • 7 studies were prospective.
  • 2 studies were systematic reviews or meta-analyses.
  • 19 studies were multicenter; 11 were single-center or monocentric.
  • 14 studies were described as observational; 9 as cohort studies.
  • 34 studies used registry-based data.
  • 9 studies used propensity score matching or similar methods; 3 used inverse probability of treatment weighting.
  • Other designs included randomized controlled trial/open-label extension (1), chart review (2), cross-sectional (1), post-authorization (1), and Bayesian propensity score matching (1).
• Registry source:
  • 24 studies used a named registry, most commonly MSBase (8 studies), NTD (2), CONFIDENCE (2), OPERA (2), MENACTRIMS (1), DMSR (1), Kuwait (1), Danish (1), and Bari (1).
  • 4 studies used multiple or unspecified registries.
  • No registry source was found for 12 studies.
  • Countries/regions represented include Germany (at least 5 studies), Italy (at least 3), United Kingdom (at least 2), France, Denmark, Turkey, Australia, and Kuwait.
• Population size:
  • 8 studies included fewer than 100 participants.
  • 14 studies included 100–499 participants.
  • 6 studies included 500–999 participants.
  • 10 studies included 1000 or more participants.
  • No mention of population size was found for 5 studies.
• Follow-up duration:
  • 6 studies had follow-up durations of less than 1 year.
  • 8 studies had follow-up durations of 1–2 years.
  • 15 studies had follow-up durations of 2–5 years.
  • 4 studies had follow-up durations longer than 5 years.
  • No mention of follow-up duration was found for 7 studies.

Effects

Annualized Relapse Rate

Study

Treatment

Annualized Relapse Rate (95% CI)

Study Population

Effect Size

Zanghì et al., 2024

ocrelizumab: 0.059; ofatumumab: 0.038 (p=0.185)

Relapsing multiple sclerosis

No significant difference

Zhu et al., 2022

ocrelizumab: 0.07 (0.04–0.13); natalizumab: 0.11 (0.09–0.14); cladribine: 0.25 (0.12–0.57)

Relapsing-remitting multiple sclerosis post-fingolimod

ocrelizumab superior to cladribine, lower than natalizumab

Cunha et al., 2025

rituximab: 0.08 (post-switch); ocrelizumab/ofatumumab: no significant change

Post-natalizumab

No significant change for ocrelizumab/ofatumumab

Boz et al., 2023

ocrelizumab: 0.08 (0.06–0.11); natalizumab: 0.09 (0.07–0.12); fingolimod: 0.17 (0.15–0.19)

Relapsing-remitting multiple sclerosis

ocrelizumab/natalizumab similar, both superior to fingolimod

Zhu et al., 2023

ocrelizumab: 0.06 (0.04–0.08); fingolimod: 0.26 (0.12–0.48); dimethyl fumarate: 0.27 (0.12–0.56)

Relapsing-remitting multiple sclerosis post-natalizumab

ocrelizumab superior to both

Roos et al., 2024

ocrelizumab: 0.05; cladribine: 0.09; natalizumab: 0.06; fingolimod: 0.12; alemtuzumab: 0.04

Relapsing-remitting multiple sclerosis

ocrelizumab superior to cladribine/fingolimod, similar to natalizumab/alemtuzumab

Roos et al., 2022

ocrelizumab: 0.08 vs interferon: 0.27; ocrelizumab: 0.03 vs fingolimod: 0.14; ocrelizumab: 0.06 vs natalizumab: 0.08

Relapsing-remitting multiple sclerosis

ocrelizumab superior to interferon/fingolimod, similar to natalizumab

Axhausen et al., 2025

ocrelizumab/ofatumumab: no mention found

Active multiple sclerosis

Effectiveness comparable

Buttmann et al., 2025

ocrelizumab: 0.11 (SD 0.31)

Relapsing multiple sclerosis

Annualized relapse rate declines over 5 years

Guerra et al., 2025

ocrelizumab: 0.02 (0.004–0.062) (year 2)

Relapsing-remitting/primary progressive/secondary progressive multiple sclerosis

Annualized relapse rate drops from 0.61 pre-treatment

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Summary of annualized relapse rate findings:

• Range of annualized relapse rate for ocrelizumab:0.014 to 0.11 across 12 studies reporting this outcome.
• Direct head-to-head comparisons:9 studies included direct comparisons between ocrelizumab, ofatumumab, or rituximab and other disease-modifying therapies.
• Within-group changes:5 studies reported a drop in annualized relapse rate after switching to ocrelizumab, with pre-treatment rates as high as 0.8 and post-treatment rates as low as 0.014.
• Comparative effectiveness:
  • Ocrelizumab was reported as superior to at least one comparator in 5 studies (most often fingolimod or cladribine).
  • Ocrelizumab was reported as similar in effectiveness to comparators (most often natalizumab or alemtuzumab) in 7 studies.
  • Ocrelizumab was reported as inferior to a comparator in 1 study (lower than natalizumab in Zhu et al., 2022).
• Ofatumumab data:Only 1 study (Zanghì et al., 2024) reported annualized relapse rate for ofatumumab, finding no significant difference compared to ocrelizumab.
• Rituximab data:1 study (Cunha et al., 2025) reported annualized relapse rate for rituximab post-switch.
• Comparators:Natalizumab and fingolimod were the most common comparators, each included in 5–6 studies.
• Reporting gaps:5 studies did not mention annualized relapse rate or comparative effectiveness for ocrelizumab, ofatumumab, or rituximab.

Confirmed Disability Progression

Study

Treatment

Confirmed Disability Progression Rate

Time to Progression

Statistical Significance

Zanghì et al., 2024

ocrelizumab/ofatumumab: 0%

12 months

No difference

Zhu et al., 2022

ocrelizumab/natalizumab: no mention found

No mention found

No significant difference

Cunha et al., 2025

ocrelizumab/ofatumumab: no significant change; rituximab: Expanded Disability Status Scale increased (p=0.022)

No mention found

No significant difference for ocrelizumab/ofatumumab

Boz et al., 2023

ocrelizumab/natalizumab/fingolimod: no mention found

1–2 years

No significant difference

Zhu et al., 2023

ocrelizumab: 48 events; fingolimod: 184 events

No mention found

Fingolimod higher risk than ocrelizumab (hazard ratio 1.49, p=0.02)

Roos et al., 2024

ocrelizumab: hazard ratio 0.45 (0.26–0.78) vs cladribine

No mention found

ocrelizumab lower risk than cladribine

Axhausen et al., 2025

ocrelizumab/ofatumumab: no mention found

No mention found

Comparable effectiveness

Buttmann et al., 2025

ocrelizumab: no mention found

5 years

No mention found

Guerra et al., 2025

ocrelizumab: 26.4% (year 2) → 7.85% (year 4)

4 years

Significant only in secondary progressive multiple sclerosis

Santiago-Setien et al., 2023

ocrelizumab: 0%

96 weeks

No difference

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Summary of confirmed disability progression findings:

• Studies with ocrelizumab as a treatment group:7 studies.
• Studies with ofatumumab alone:1 study.
• Studies with ocrelizumab/ofatumumab combined:3 studies.
• Other treatments compared:rituximab (1 study), natalizumab (2 studies, plus 1 ocrelizumab/natalizumab), fingolimod (2 studies), cladribine (1 study).
• Numerical confirmed disability progression rates or event counts:Found in 6 studies, with reported values including 0% (2 studies), 48 events (ocrelizumab), 184 events (fingolimod), 26.4% (year 2) → 7.85% (year 4), standard interval dosing 8.3%, extended interval dosing 10.9%, and for subtypes: relapsing-remitting multiple sclerosis >97% confirmed disability progression-free, secondary progressive multiple sclerosis 48.9%, primary progressive multiple sclerosis 57.2%.
• Time to progression or follow-up duration:Reported in 9 studies, ranging from 6 months to 5 years. The most common time points were 12 months (2 studies) and 5 years (2 studies).
• Statistical significance of confirmed disability progression or progression comparisons:
  • 8 studies reported no significant difference or comparable effectiveness between groups.
  • 3 studies reported a significant difference, with ocrelizumab associated with lower risk than fingolimod (1 study), lower risk than cladribine (1 study), and a significant effect only in secondary progressive multiple sclerosis (1 study).
  • No mention of statistical significance was found in 4 studies.

Comparative Effectiveness

Direct registry-based comparisons of ocrelizumab and ofatumumab:

• Zanghì et al., 2024 (large, multicenter, propensity-matched study): No significant difference in annualized relapse rate or confirmed disability progression between ocrelizumab and ofatumumab over 12 months.
• Axhausen et al., 2025: Lateral switching between ocrelizumab and ofatumumab did not reduce effectiveness.
• Cunha et al., 2025 (small cohort post-natalizumab): No significant difference in annualized relapse rate or Expanded Disability Status Scale change for ocrelizumab and ofatumumab.
• The evidence base for ofatumumab is much smaller and less mature than for ocrelizumab, with limited sample sizes and shorter follow-up.

Comparative findings for ocrelizumab:

• In these studies, ocrelizumab was reported to be superior to fingolimod and cladribine for annualized relapse rate, and similar to natalizumab and alemtuzumab.
• Confirmed disability progression rates were low and similar between ocrelizumab and natalizumab, and lower than fingolimod.
• Safety profiles were not systematically reported; we did not find mention of new safety signals in the available studies.

Registry Data Considerations

• Several studies of ocrelizumab included large sample sizes and long follow-up (for example, CONFIDENCE and MSBase registries).
• The evidence base for ofatumumab is limited, with only a few small, short-term studies.
• Observational design, potential confounding, and differences in patient populations, prior treatment history, and follow-up duration may affect comparability across studies.
• The diversity of registry cohorts supports generalizability of findings for ocrelizumab, but the limited data for ofatumumab restricts conclusions about its comparative effectiveness in broader populations.

References

A. Zanghì, G. Borriello, S. Bonavita, R. Fantozzi, E. Signoriello, and 12 more\ (2024).Ocrelizumab and ofatumumab comparison: an Italian real-world propensity score matched study. Journal of Neurology

Sahla El Mahdaoui, J. Christensen, M. Magyari, M. Wandall-Holm, F. Sellebjerg\ (2022).Intravenous ofatumumab treatment of multiple sclerosis and related disorders: An observational study. Multiple Sclerosis and Related Disorders

X. Montalban, P. Matthews, A. Simpson, John L. Petrie, C. Sammon, and 3 more\ (2023).Real‐world evaluation of ocrelizumab in multiple sclerosis: A systematic review. Annals of Clinical and Translational Neurology

Chao Zhu, Zhen Zhou, I. Roos, Daniele Merlo, T. Kalincik, and 24 more\ (2022).Comparing switch to ocrelizumab, cladribine or natalizumab after fingolimod treatment cessation in multiple sclerosis. Journal of Neurology Neurosurgery & Psychiatry

I. Roos, S. Hughes, G. McDonnell, C. Malpas, S. Sharmin, and 31 more\ (2023).Rituximab vs Ocrelizumab in Relapsing-Remitting Multiple Sclerosis. JAMA Neurology

I. Roos, S. Sharmin, J. Lechner-Scott, K. Buzzard, O. Skibina, and 8 more\ (2022).2242 Comparison of the effectiveness of ocrelizumab vs interferon β, fingolimod and natalizumab on relapses in relapsing-remitting multiple sclerosis. Abstracts

C. Boz, S. Ozakbas, M. Terzi, R. Karabudak, S. Sevim, and 15 more\ (2023).The comparative effectiveness of fingolimod, natalizumab, and ocrelizumab in relapsing-remitting multiple sclerosis. Neurological Sciences

Samantha Epstein, K. Fong, P. D. De Jager, Libby Levine, C. Riley, and 3 more\ (2021).Evaluation of ocrelizumab in older progressive multiple sclerosis patients. Multiple Sclerosis and Related Disorders

E. Ellwardt, L. Rolfes, J. Klein, K. Pape, T. Ruck, and 6 more\ (2020).Ocrelizumab initiation in patients with MS. Neurology: Neuroimmunology & Neuroinflammation

M. Cellerino, G. Boffa, C. Lapucci, F. Tazza, E. Sbragia, and 11 more\ (2021).Predictors of Ocrelizumab Effectiveness in Patients with Multiple Sclerosis. Neurotherapeutics

K. Bigaut, L. Kremer, Thibaut Fabacher, G. Ahle, Mathilde Goudot, and 5 more\ (2022).Ocrelizumab versus fingolimod after natalizumab cessation in multiple sclerosis: an observational study. Journal of Neurology

Y. Foong, Daniel Merlo, M. Gresle, K. Buzzard, Michael Zhong, and 18 more\ (2024).Comparing ocrelizumab to interferon/glatiramer acetate in people with multiple sclerosis over age 60. Journal of Neurology Neurosurgery & Psychiatry

E. Muros-Le Rouzic, Y. Heer, Sean Yiu, Viola Tozzi, S. Braune, and 5 more\ (2024).Five-year efficacy outcomes of ocrelizumab in relapsing multiple sclerosis: A propensity-matched comparison of the OPERA studies with other disease-modifying therapies in real-world lines of treatments. Journal of Central Nervous System Disease

Chao Zhu, T. Kalincik, D. Horáková, Zhen Zhou, K. Buzzard, and 37 more\ (2023).Comparison Between Dimethyl Fumarate, Fingolimod, and Ocrelizumab After Natalizumab Cessation. JAMA Neurology

Amanda Claudia Schuldesz, R. Tudor, A. Cornea, Dorina Nicola Geni, Irina Lata, and 1 more\ (2025).Effectiveness of Ocrelizumab on Disease Progression and Disability Status in Multiple Sclerosis Patients: A Two-Year Prospective Cohort Study. Journal of Clinical Medicine

L. A. R. de Antonio, Ines Cuberta-Gonzalez, I. García-Castañón, C. Oreja-Guevara\ (2022).Relapsing-remitting and primary progressive multiple sclerosis treated with ocrelizumab: A comparative study. Multiple Sclerosis and Related Disorders

G. Giovannoni, L. Kappos, J. Seze, S. Hauser, J. Overell, and 5 more\ (2022).020  Long-term efficacy of ocrelizumab in relapsing multiple sclerosis: 6 study years. Journal of Neurology Neurosurgery & Psychiatry

C. Alcalá, C. Quintanilla-Bordás, F. Gascón, Á. Sempere, L. Navarro, and 13 more\ (2022).Effectiveness of rituximab vs. ocrelizumab for the treatment of primary progressive multiple sclerosis: a real-world observational study. Journal of Neurology

B. Yamout, R. Alroughani, Samar Frouk Ahmed Mohamed, A. Al-Mahdawi, S. Khoury, and 19 more\ (2025).Comparative effectiveness of natalizumab and anti-CD20 monoclonal antibodies in relapsing-remitting multiple sclerosis: a real-world propensity-score matched study. Journal of Neurology Neurosurgery & Psychiatry

H. Butzkueven, T. Spelman, T. Kalincik, K. Buzzard, A. Walt, and 6 more\ (2021).010 Real-world experience with ocrelizumab in the MSBase registry – Australian RRMS cohort. Oral abstracts

I. Roos, S. Sharmin, C. Malpas, S. Ozakbas, J. Lechner-Scott, and 41 more\ (2024).Effectiveness of cladribine compared to fingolimod, natalizumab, ocrelizumab and alemtuzumab in relapsing-remitting multiple sclerosis. Multiple Sclerosis

Michael Zhong, A. van der Walt, J. Stankovich, T. Kalincik, K. Buzzard, and 27 more\ (2021).Prediction of multiple sclerosis outcomes when switching to ocrelizumab. Multiple Sclerosis

K. Pape, L. Rolfes, Falk Steffen, M. Muthuraman, Melanie Korsen, and 3 more\ (2022).Comparative effectiveness of natalizumab versus ocrelizumab in multiple sclerosis: a real-world propensity score–matched study. Therapeutic Advances in Neurological Disorders

Elena Barbuti, Alessia Castiello, Valeria Pozzilli, A. Carotenuto, Ilaria Tomasso, and 7 more\ (2025).Comparative effectiveness, safety and persistence of ocrelizumab versus natalizumab in multiple sclerosis: A real-world, multi-center, propensity score-matched study. Neurotherapeutics

R. Alroughani, J. Al-Hashel, S. Ahmed\ (2024).Substantial and comparable suppression of disease activity following early initiation of cladribine tablets, ocrelizumab or alemtuzumab as first pharmacologic treatment for relapsing multiple sclerosis: A real world study. Clinical neurology and neurosurgery (Dutch-Flemish ed. Print)

Tiziana Zaccone, L. Moiola, S. Guerrieri, A. Nozzolillo, C. Zanetta, and 7 more\ (2025).Long-term effectiveness and safety of ocrelizumab: a single-centre real-world study. Journal of Neurology

Martin S. Weber, M. Buttmann, S. Meuth, P. Dirks, E. Muros-Le Rouzic, and 4 more\ (2022).Safety, Adherence and Persistence in a Real-World Cohort of German MS Patients Newly Treated With Ocrelizumab: First Insights From the CONFIDENCE Study. Frontiers in Neurology

T. Guerra, F. Caputo, Antonella Bianco, D. Paolicelli, P. Iaffaldano\ (2025).Long-Term Evaluation of Effectiveness and Immunological Implications of Ocrelizumab in a Real-World Cohort. Drugs - real world outcomes

Paolo A Muraro, Antonio Zito, Alessio Signori, M. Sormani, Eleonora Rigoni, and 12 more\ (2025).Effectiveness of Autologous Hematopoietic Stem Cell Transplantation versus Alemtuzumab and Ocrelizumab in Relapsing Multiple Sclerosis: A Single Center Cohort Study. Annals of Neurology

L. Lorefice, P. Mellino, J. Frau, G. Coghe, G. Fenu, and 1 more\ (2024).Ocrelizumab use in multiple sclerosis: a real-world experience in a changing therapeutic scenario. Neurological Sciences

Mathias Buttmann, Martin S. Weber, Sven G. Meuth, Sandra Blümich, S. Hieke-Schulz, and 3 more\ (2025).CONFIDENCE treatment success: long-term real-world effectiveness and safety of ocrelizumab in Germany. Frontiers in Neurology

S. Pfeuffer, L. Rolfes, J. Ingwersen, R. Pul, Konstanze Kleinschnitz, and 10 more\ (2023).Effect of Previous Disease-Modifying Therapy on Treatment Effectiveness for Patients Treated With Ocrelizumab. Neurology: Neuroimmunology & Neuroinflammation

S. Braune, P. Dirks, Seya Colloud, Qing Wang, Evan Davies, and 4 more\ (2025).Persistence to Ocrelizumab Compared with Other Disease-Modifying Therapies for Multiple Sclerosis: Results from the German NeuroTransData Registry. Neurological Therapeutics

Moein Amin, Tucker Harvey, Dan Michael Pineda, Ming-Hui Tai, Qiujun Shao, and 5 more\ (2025).Real world effectiveness, persistence, tolerability, and safety of ofatumumab in clinical practice. Neurodegenerative Disease Management

Pilar Santiago-Setien, Cristina Barquín-Rego, P. Hernández-Martínez, María Ezquerra-Marigómez, Marta Torres-Barquin, and 8 more\ (2023).Switch to ocrelizumab in MS patients treated with natalizumab in extended interval dosing at high risk of PML: A 96-week follow-up pilot study. Frontiers in Immunology

Mahsa Ghajarzadeh, Mohsen Rastkar, E. Mowry, B. Nourbakhsh\ (2025).Clinical and radiological activity after extended interval and standard interval dosing of ocrelizumab in multiple sclerosis: A systematic review and meta-analysis. Neurological Sciences

No authors found (2022).ePosters. European Journal of Neurology

Franziska Axhausen, Anne Mrochen, Pia Winter, Romy Baumgart, Pauline Mühlenbrock, and 5 more\ (2025).Disease outcomes following lateral switch among different CD20-antibodies in active multiple sclerosis. Multiple Sclerosis

Carolina Cunha, Sara Matos, Catarina Bernardes, Inês Carvalho, João Cardoso, and 6 more\ (2025).Effectiveness of anti-CD20 therapies following natalizumab discontinuation: insights from a cohort study. Multiple Sclerosis and Related Disorders

Martina Nasello, Valeria Zancan, Virginia Rinaldi, Antonio Marrone, R. Reniè, and 6 more\ (2024).Clinical and Immunological Impact of Ocrelizumab Extended Interval Dosing in Multiple Sclerosis: A Single-Center, Real-World Experience. International Journal of Molecular Sciences

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The comparative effectiveness of fingolimod, natalizumab, and ocrelizumab in relapsing-remitting multiple sclerosis

C. Boz, S. Ozakbas, M. Terzi, R. Karabudak, S. Sevim, R. Turkoglu, A. Soysal, B. P. Balci, H. Efendi, Ö. F. Turan, Nur Yüceyar, M. Yetkin, S. Z. Karahan, M. Demirkıran, S. Guler, K. Ağan, N. Kıylıoğlu, C. Baba, A. Tuncer, Mesrure Köseoğlu

Neurological Sciences·

2023·

7 citations

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Study Design

Multicenter, retrospective observational study with propensity score matching

Patient Population Characteristics

- Total number of patients: 6243 assessed for eligibility; 2790 included in propensity matching - Mean/median age: Approximately 40 years - Gender distribution: Not reported - Multiple sclerosis type: RRMS - Mean disease duration: Not reported - Baseline Expanded Disability Status Scale (EDSS) score: Approximately 3.1 for fingolimod and natalizumab; slightly higher for ocrelizumab - Treatment-naive status vs. previous treatment history: Most patients were switchers from other therapies

Interventions Compared

- Drug names: Fingolimod, Natalizumab, Ocrelizumab - Dosage: Not specified - Treatment duration: Not specified - Number of patients in each treatment group: - Fingolimod vs. Natalizumab: 736 vs. 370 - Fingolimod vs. Ocrelizumab: 762 vs. 434 - Natalizumab vs. Ocrelizumab: 310 vs. 310

Annualized Relapse Rate (ARR)

- Baseline ARR: Not explicitly mentioned - On-treatment ARR: - Fingolimod: 0.17 (95% CI 0.15-0.19) - Natalizumab: 0.09 (95% CI 0.07-0.12) - Ocrelizumab: 0.08 (95% CI 0.06-0.11) - Statistical significance: - Natalizumab vs. Fingolimod: p<0.001 - Ocrelizumab vs. Fingolimod: p=0.001 - Natalizumab vs. Ocrelizumab: p=0.54

Disability Progression

- Method of measuring disability progression: 1.5-point increase (if baseline EDSS score was 0), 1.0-point increase (if baseline EDSS score was <5.5), or 0.5-point increase (if baseline EDSS score was ≥5.5) confirmed at 6-month intervals. - Percentage of patients with disability progression: Not explicitly provided. - Changes in EDSS score: Not explicitly provided. - Statistical significance of differences between groups: No significant differences between any groups (p-values: fingolimod vs. natalizumab p=0.21, fingolimod vs. ocrelizumab p=0.62, natalizumab vs. ocrelizumab p=0.91).

Follow-up Duration

- Total follow-up period: Not explicitly stated - Median follow-up time: 2.1 years (fingolimod vs. natalizumab), 1.5 years (natalizumab), 2.0 years (fingolimod vs. ocrelizumab), 1.5 years (ocrelizumab), 1.4 years (natalizumab vs. ocrelizumab) - Range of follow-up times: 1.1–3.6 years (fingolimod vs. natalizumab), 0.7–2.6 years (natalizumab), 1.1–3.6 years (fingolimod vs. ocrelizumab), 1.0–2.1 years (ocrelizumab), 0.7–2.5 years (natalizumab vs. ocrelizumab)

Safety Outcomes

no significant safety concerns reported

BACKGROUND

Fingolimod, natalizumab, and ocrelizumab are commonly used in the second-line treatment of relapsing-remitting multiple sclerosis (RRMS). However, these have only been compared in observational studies, not in controlled trials, with limited and inconclusive results being reported. A comparison of their effect on relapse and disability in a real-world setting is therefore needed.

OBJECTIVES

The objective of this study was to compare the efficacy of fingolimod, natalizumab, and ocrelizumab in reducing disease activity in RRMS.

METHODS

This multicenter, retrospective observational study was carried out with prospectively collected data from 16 centers. All consecutive RRMS patients treated with fingolimod, natalizumab, and ocrelizumab were included. Data for relapses, Expanded Disability Status Scale (EDSS) scores, and brain magnetic resonance imaging (MRI) scans were collected. Patients were matched using propensity scores. Annualized relapse rates (ARR), time to first relapse, and disability accumulation were compared.

RESULTS

Propensity score matching retained 736 patients in the fingolimod versus 370 in the natalizumab groups, 762 in the fingolimod versus 434 in the ocrelizumab groups, and 310 in the natalizumab versus 310 in the ocrelizumab groups for final analyses. Mean ARR decreased markedly from baseline after treatment in all three treatment groups. Mean on-treatment ARR was lower in natalizumab-treated patients (0.09, 95% confidence interval (CI), 0.07-0.12) than in those treated with fingolimod (0.17, 0.15-0.19, p<0.001), ocrelizumab (0.08, 0.06-0.11), and fingolimod (0.14, 0.12-0.16, p=0.001). No significant difference was observed in mean on-treatment ARR between patients treated with natalizumab (0.08, 0.06-0.11) and ocrelizumab (0.09, 0.07-0.12, p=0.54). Compared to fingolimod, the natalizumab and ocrelizumab groups exhibited a higher percentage of relapse-free patients and a lower percentage of MRI-active patients at year 1. No significance differences in disability accumulation were determined between the therapies.

CONCLUSION

Natalizumab and ocrelizumab exhibited similar effects on relapse control, and both were associated with better relapse control than fingolimod. The effects of the three therapies on disability outcomes were similar.

© 2023. Fondazione Società Italiana di Neurologia.

Introduction

The high-efficacy therapies fingolimod, natalizumab, and ocrelizumab are becoming increasingly widely used in relapsing-remitting multiple sclerosis (RRMS), either as first-line therapies or as a switch from other disease-modifying therapies. They have also been approved for RRMS on the basis of large phase III randomized clinical trials showing efficacy in reducing relapse rates, disability worsening, and magnetic resonance imaging (MRI) activity [1][2][3][4].

Fingolimod, natalizumab, and ocrelizumab have been available as treatments for RRMS since their approval by the Food and Drug Administration and European Medicines Agency. These drugs are generally prescribed for RRMS patients who have either experienced a suboptimal response or poor tolerability with previous therapies, or to treatmentnaïve patients with highly active RRMS and an Expanded Disability Status Scale (EDSS) score less than 6.

Limited real-world studies have compared high-efficacy drugs. While the efficacy and safety profiles of fingolimod, natalizumab, and ocrelizumab have been established in clinical trials and real-world settings, limited data are available comparing their effectiveness. Observational studies comparing the real-world effectiveness of fingolimod and natalizumab have yielded conflicting results. Some studies have reported no difference in efficacy between fingolimod and natalizumab, while several studies have demonstrated that natalizumab exhibits superior effectiveness on relapse rates [5][6][7][8][9][10]. A recent study reported no difference in relapse and MRI activity between natalizumab and anti-CD20 (rituximab and ocrelizumab) after a fingolimod switch [11].

This study aimed to compare the effectiveness of fingolimod, natalizumab, and ocrelizumab in a real-world setting in Turkish patients with RRMS.

Patients and methods

This research was performed as an independent, multicenter, real-world observational study. Ethical committee approval was obtained from the Karadeniz Technical University Medical Faculty Ethical Committee. Each center received local regulation and local ethical committee approval for registry use for all multiple sclerosis (MS) patients. Written informed consent was required from all participating patients at each center.

Data from all RRMS patients treated with fingolimod, natalizumab, and ocrelizumab between January 2014 and June 2021 who regularly attended the 16 tertiary MS centers were included retrospectively (Supplementary Table 1 ). Treatment selection was made by the treating neurologist.

Demographic, clinical, and MRI data were prospectively recorded as part of routine clinical practice. The data entry portal was "Imed software," and quality assurance procedures were followed (Supplementary Table 2 ) [12]. A series of automated procedures were applied to identify any invalid or erroneous data entries.

The usual data entry practice was real time or a close approximation of real time at the time of clinical visits. Data for patients treated with fingolimod, natalizumab, and ocrelizumab were extracted in the form of an Excel file from each center and were then combined for analyses.

The inclusion criteria for analyses consisted of diagnosis with RRMS according to the 2017 Revised McDonald criteria, and continuous exposure to one of the study therapies for ≥ 3 months. Data for the following variables were required for all patients included: sex, age, date of first MS symptom, dates of clinical relapses, and disability score assessed by EDSS at commencement of treatment and at least two disability scores recorded after commencement of one of the study therapies. EDSS scores within 3 months prior to or 1 month after commencement of the study therapy were regarded as patients' baseline EDSS.

Patients aged <18 years, treated with an immunosuppressant (cladribine, alemtuzumab, mitoxantrone, or cyclophosphamide) within the previous year, or with a progressive MS course, were excluded from the study.

The study follow-up duration was defined as the time between the start of therapy and the last available EDSS entry visit. Disability was assessed using EDSS by Neurostatus-certified MS specialists. Any EDSS score recorded within 30 days of a previous relapse was excluded.

Available MRI information reported by treating neurologists was also collected. MRI scans of the brain acquired within 3 months prior to the initiation of the study therapy were regarded as baseline MRI. MRI scans acquired at the 12th month after the initiation of therapy (± 60 days) were defined as year 1 MRI.

Study endpoints

The primary study outcomes were annualized relapse rate (ARR) and time to first relapse. The secondary endpoints were time to disability progression and MRI activity at year 1.

A relapse was defined as any new neurological symptom or exacerbation of existing symptoms persisting for at least 24 h in the absence of concurrent illness or fever, and occurring at least 30 days after a previous relapse [13]. Disability progression was defined as a 1.5-point increase (if the baseline EDSS score was 0), a 1.0-point increase (if the baseline EDSS score was <5.5), or a 0.5-point increase (if the baseline EDSS score was ≥5.5) confirmed at 6-month intervals [14].

In order to minimize unstandardized MRI results, MRI data had to be available in ≥25% of patients in the centers included. Categorized baseline T2 and Gd-enhancing (Gd+) lesion numbers (unavailable, 1-8, ≥9 T2 lesions and absent or ≥1 Gd+ lesion) were analyzed. Percentages of patients with brain MRI activity (defined as the presence of ⩾1 new/enlarging T2 lesion compared to previous brain MRI scans and/or the presence of ⩾1 Gd+ lesion) at year 1 were calculated.

Statistical analyses

Matching and statistical analyses were conducted using R (version 4.0) [15]. The patients included in the study were matched in terms of their propensity scores in three separate matched analyses of fingolimod versus natalizumab, fingolimod versus ocrelizumab, or natalizumab versus ocrelizumab-treated groups using MatchIt package [16]. The propensity score was based on a multivariable logistic regression model. Independent variables consisted of age, age at onset, gender, disease duration, baseline EDSS, and number of relapses in the year before treatment. Patients were matched without replacement in a 2:1 ratio (fingolimod versus natalizumab, and fingolimod versus ocrelizumab) or a 1:1 ratio (natalizumab versus ocrelizumab) using nearest neighbor matching within a caliper of 0.2 standard deviations of the propensity score. The distribution of propensity scores is shown in Supplementary Figure 1 .

Patients who switched or discontinued treatment were censored. Only matched pairs were included in this analysis. Patients' baseline characteristics were evaluated in order to identify possible statistical differences among the two treatment groups. Mean, standard deviation, median, min, max, or interquartile range (IQR) values were reported for continuous variables, depending on the statistical distribution.

In order to investigate statistical relevance, the t test was used for continuous normally distributed variables and the χ 2 test for categorical data. On-treatment ARRs were compared with a marginal weighted negative binomial regression model with additional year 1 and year 2 ARR comparisons using the t test.

The proportion of patients without relapse or without an increase in EDSS was evaluated using the Cox marginal proportional hazards model. The proportional hazards assumption was examined visually and by testing Schoenfeld's residuals. Kaplan-Meier survival estimate curves were used to visualize time-to-event outcomes.

Where no statistically significant differences were observed, analytical power was quantified as the minimum detectable effect at 1-β=0.8 using 200 simulations. Significance was set at p< 0.05.

We performed three sensitivity analyses to assess the robustness of our primary outcome results. First, pairwise censoring was applied to the analyses of time to first relapse to determine common on-treatment follow-up times in order to mitigate attrition bias and the effect of differential treatment persistence [17].

Second, the analyses were repeated after the baseline covariates were adjusted with propensity score weighting method using overlap weight (PSOW) with the R-WeightIt package to reduce the probability of an inadequate covariate balance. An PSOW-adjusted negative binomial model was used to compare ARRs, with the relapse count as the dependent variable.

Third, we excluded patients who had received one of the two medications as a previous therapy and reran the analysis using the newly generated propensity matched groups.

Results

A total of 6243 patients were assessed for eligibility, 3601 treated with fingolimod, 839 with natalizumab, and 1803 with ocrelizumab. A total of 2790 patients (1955 in the fingolimod group, 376 in the natalizumab group, and 459 in the ocrelizumab group) met the inclusion criteria and were included in the propensity matching analyses (Fig. 1 ). The baseline characteristics of the three treatment groups 3 ). Patients treated with ocrelizumab tended to be older, with a longer duration of MS, and with higher EDSS scores compared to fingolimod and natalizumab, while natalizumab-treated patients exhibited more relapses and more MRI activity during the previous year.

The numbers of patients retained after the propensity score matching procedure in the matched cohorts were 736 in the fingolimod versus 370 in the natalizumab groups, 762 in the fingolimod versus 434 in the ocrelizumab groups, and 310 in the natalizumab versus 310 in the ocrelizumab groups. The matched patients' baseline demographic and clinical characteristics are shown in Table 1 .

Fingolimod versus natalizumab

After matching, the patients treated with fingolimod were similar in age (40.1±9.7 vs. 39.7±10.2 p=0.55) and had similar baseline ARR (mean, 95% confidence interval (CI); 1.07, 0.99-1.14 vs. 1.06, 0.96-1.15, respectively, p=0.87) and baseline EDSS (3.1±1.5 vs. 3.1±1.4, respectively, p=0.9) values to those treated with natalizumab. ARR values for fingolimod and natalizumab in the year before treatment initiation and in the first year and second years are shown in Fig. 2a . ARR decreased markedly after treatment in both the fingolimod and natalizumab groups. Mean on-treatment ARR was lower in natalizumab-treated patients (mean, 95% CI; 0.09, 0.07-0.12) than in those treated with fingolimod (mean, 95% CI; 0.17, 0.15-0.19, p<0.001) (Fig. 2a ).

The proportion of relapse-free patients was higher in the natalizumab group than in the fingolimod group (hazard ratio (HR) 0.35, 95% CI; 0.24-0.49, p < 0.001) (Fig. 3a ).

No differences were observed between fingolimod and natalizumab in terms of rates of confirmed disability accumulation (HR 0.78, 95% CI 0.52-1.16, p=0.21) (Fig. 4a ).

The proportion of brain MRI activity-free patients at year 1 was higher among patients treated with natalizumab (availability 50.4%, MRI inactive 91.5%) than in the fingolimod group (availability 47.9%, MRI inactive=74.8%, p<0.001).

Fingolimod versus ocrelizumab

After matching, patients treated with fingolimod were similar in age (42.7 ± 9.6 vs. 43.7 ± 10.6, respectively, p=0.07) and had similar baseline ARR (mean, 95% CI; 0.66, 0.60-0.70, vs. 0.62, 0.55-0.69, respectively, p=0.43) and baseline EDSS (3.35±1.41 vs. 3.49±1.45, p=0.09) to those treated with ocrelizumab. ARRs for fingolimod and ocrelizumab in the year before treatment initiation and in the first year and second years are shown in Fig. 2b .

ARR values decreased markedly after treatment in both the fingolimod and ocrelizumab groups. Mean on-treatment ARR was lower in ocrelizumab-treated patients (mean, 95% CI; 0.08, 0.06-0.11) than in those treated with fingolimod (mean, 95% CI; 0.14, 0.12-0.16, p=0.001) (Fig. 2b ).

The proportion of relapse-free patients was higher among patients treated with ocrelizumab than in the fingolimod group (HR 0.32, 95% CI 0.21-0.47, p=0.001; Fig. 3b ).

No differences were observed between fingolimod and ocrelizumab in terms of rates of confirmed disability accumulation (HR 1.1, 95% CI 0.75-1.62, p=0.62, Fig. 4b ).

The proportion of brain MRI activity-free patients at year 1 was higher among patients treated with ocrelizumab (availability 47.7%, MRI inactive 88.4%) than in the fingolimod group (availability 41.2%, MRI inactive=74.8%, p=0.001).

Natalizumab versus ocrelizumab

After matching, patients treated with natalizumab were similar in age (40.9 ± 10.4 vs. 42.4 ± 10.9, respectively, p=0.14) and had similar baseline ARR (mean, 95% CI; 0.84, 0.76-0.92, vs. 0.84, 0.76-0.92, respectively, p=0.9) and baseline EDSS (3.22±1.48 vs. 3.40±1.50, respectively p=0.14) values to those treated with ocrelizumab. ARR values for natalizumab and ocrelizumab in the year before treatment initiation and in the first year and second years are shown in Fig. 2c .

ARR decreased markedly after treatment in both the natalizumab and ocrelizumab groups. No difference was observed in mean on-treatment ARR between the natalizumab (mean, 95% CI; 0.08, 0.06-0.11) and ocrelizumab (mean, 95% CI; 0.09, 0.07-0.12, p=0.54) groups (Fig. 2c ).

The proportion of relapse-free patients was similar between the natalizumab and ocrelizumab groups (hazard ratio (HR) 1.53, 95% CI 0.84-2.77, p=0.16; Fig. 3c ).

No differences were observed between natalizumab and ocrelizumab in terms of rates of confirmed disability accumulation (HR 0.98, 95% CI 0.56-1.72, p=0.91, Fig. 4c ).

The proportion of brain MRI activity-free patients at year 1 was similar between the natalizumab (availability 46.1%, MRI inactive 92%) and ocrelizumab (availability 40.6%, MRI inactive 93.3%, p=0.78) groups.

Secondary analyses

In order to test for attrition bias, on-treatment follow-up was censored at the shorter of the two individual follow-up periods for each matched fingolimod-natalizumab, natalizumabocrelizumab, and fingolimod-ocrelizumab patient pair (pairwise censoring). Consistent with the primary analysis, similar results were obtained in terms of time to first relapse outcomes (Supplementary Figure 2 ).

In PSOW-adjusted treatment groups, natalizumab and ocrelizumab exhibited similar effects on relapse control, and both were associated with a statistically significant reduced ARR and significantly reduced hazard of the first relapse when compared to fingolimod (Supplementary Table 4 and Supplementary Figure 3a, b, c ). Clinical characteristics of matched patients after excluding patients who had received one of the two medications as a previous therapy are shown in Supplementary Table 5 .

Consistent with the primary analysis, similar results were obtained in terms of ARR and time to first relapse outcomes except for a loss of statistical significance in year 1 relapse rate comparison between fingolimod versus natalizumab and fingolimod versus ocrelizumab groups due to the likely insufficient power with small sample size (Supplementary Table 6 and Fig. 4a, b, c ).

Discussion

This propensity score matching analysis compared the efficacy of three commonly used high-efficacy therapies in patients with RRMS. Patients were mostly switchers from first-line therapies. Before matching, the natalizumab group was more active than the fingolimod and ocrelizumab groups. Natalizumab therapy may be initiated preferentially in more highly active disease due to its rapid control of disease activity.

In the matched populations, all three high-efficacy drugs, fingolimod, natalizumab, and ocrelizumab, significantly reduced relapse activity. While the relapse reducing effects of natalizumab and ocrelizumab were similar, natalizumab and ocrelizumab exhibited a greater effect on relapse than fingolimod. All three therapies exhibited comparable effects on disability accumulation during the initial 2.5 years.

The on-treatment ARRs observed in this study for the fingolimod (0.14), natalizumab (0.10), and ocrelizumab (0.08) groups were slightly lower than those reported in the pivotal trials (0.16-0.20, 0.20-0.24, and 0.16, respectively) [2,3,18,19].

The magnitude of the effects on relapse activity may be partly due to lower pre-treatment disease activity than in the pivotal trials. Our pre-treatment relapse rates were also lower than those in pivotal trials. Pre-treatment disease activity and age are well-known factors affecting on-treatment relapse activity as well as modulators for medication efficacy.

While some previous observational studies comparing fingolimod and natalizumab in MS have reported no differences in terms of effectiveness, most recent studies have reported that natalizumab was superior in reducing relapse activity [5,6,[8][9][10][20][21][22]. Heterogeneity of baseline characteristics may explain the discrepant results.

In the present study, natalizumab-treated patients exhibited more inflammation at the start of natalizumab therapy than those treated with fingolimod and ocrelizumab, which may have affected the comparison results, despite multivariate analysis. The propensity score model is unable to adjust for unknown confounders, such as physicians' treatment decisions.

Similar to the results of the present research, a recent French observational study reported a similar effect on relapse and disability outcomes for natalizumab and anti-CD20 therapies in highly active RRMS patients after fingolimod withdrawal [11]. Swedish studies have reported a similar effectiveness of rituximab compared to natalizumab [23][24][25]. Two network meta-analyses comparing ocrelizumab and other treatments have shown that ocrelizumab exhibits superior efficacy to first-line therapies and to fingolimod [26,27]. Alping et al. showed that rituximab was superior to fingolimod in the prevention of relapses within 1.5 years [23]. In a more recent study, Bigaut et al. described as ocrelizumab superior to fingolimod after natalizumab cessation [28].

The main strengths of this study are that it involved direct comparisons of the three high-efficacy therapies from 16 academic MS centers with a prospectively defined observational plan.

The main limitation of this study is its observational retrospective design. Although data entry typically occurs in real time or nearly real time, some variables such as relapserelated information may be susceptible to detection and reporting bias. However, the follow-up protocols used in this study were largely comparable, and such bias may therefore be expected to be minimal.

Another limitation was the relatively short follow-up duration. Fingolimod-treated patients had longer follow-up times than those treated with natalizumab and ocrelizumab. However, similar results were replicated on time to relapse after applying pairwise censoring as a sensitivity analysis to control attrition bias. Detecting significant changes in EDSS during this short period is challenging. Findings for disability accumulation therefore require confirmation over a longer observation period.

We were also unable to compare our radiological data to those of pivotal studies due to the absence of systematic acquisition of radiological outcomes. Consistent acquisition of quantitative MRI data in the context of retrospective multicenter studies still represents a significant challenge. The MRI data in the present study were reported by treating neurologists and were therefore subject to inter-scanner, inter-protocol, and interrater error. However, the lack of a formalized definition of MRI follow-up was not expected to introduce a systematic bias, as the same physician reported MRI in the three patient groups, and categorized results were subjected to analysis.

Most of the patients in the present study were switchers from other types of therapy. Numbers of naïve patients were relatively low. Analyses could not be applied to naïve patients, nor to subjects with low disease activity. Therefore, although the results of this study suggest that natalizumab and ocrelizumab are superior to fingolimod in terms of relapse rates and MRI activity, the same assumption cannot be extended to patients with less disease activity.

Rebound activity in patients switching from fingolimod or natalizumab may be related to early relapse activity. However, low relapse rates with natalizumab and ocrelizumab imply that rebound activity did not cause an obvious increase in relapse activity. Low numbers of patients switched from natalizumab in fingolimod cohorts (3.3% and 3.4%).

Although all three drugs share similar indications, their availability differs since ocrelizumab only entered the market after 2018. Neurologists may be oriented toward to selecting ocrelizumab in case of a higher risk of development of a progressive form of the disease. Several patients were treated with fingolimod and natalizumab before the availability of ocrelizumab. However, disease activity was the main reason for initiating therapy in all three groups.

In conclusion, this real-world observational study using propensity score-based matching suggests that natalizumab and ocrelizumab exhibited similar effectiveness in reducing relapse activity. Natalizumab and ocrelizumab were superior to fingolimod in reducing relapse activity. All three drugs exhibited similar effects on disability accumulation in a short period.

Although randomized clinical trials are the mainstay for evaluating drug efficacy and safety, the analysis of observational data provides practical evidence. Efficacy is not the only criterion to be considered in the selection of therapies for an individual patient. Observed statistical significances in reducing relapse activity of natalizumab and ocrelizumab comparing to fingolimod are from small differences. Statistical significance may not clinically significant for an individual patient. Treatment decisions need to be made based on complex evaluations and must include patient preference, adherence, treatment safety, family planning, and cost.

Given the uncertainty and variability associated with treatment effects between DMTs, real-world data, preferably from longitudinal follow-up studies, will provide additional information with which to assess long-term effectiveness.

Supplementary Information

The online version contains supplementary material available at https:// doi. org/ 10. 1007/ s10072-023-06608-z.

Declarations

Ethical approval and consent to participate Ethical committee approval was obtained from the Karadeniz Technical University Medical Faculty Ethical Committee. Each center received local regulation and local ethical committee approval for registry use for all multiple sclerosis (MS) patients. Written informed consent was required from all participating patients at each center.

Conflict of interest

Cavit Boz received conference travel support from Biogen, Novartis, Bayer-Schering, Merck, and Teva, and has participated in clinical trials by Sanofi Aventis, Roche, and Novartis. Murat Terzi received travel grants from Novartis, Bayer-Schering, Merck, and Teva, and has participated in clinical trials by Sanofi Aventis, Roche, and Novartis. Serkan Ozakbas did not declare any competing interests. Rana Karabudak did not declare any competing interests related to this study. Serhan Sevim did not declare any competing interests. Recai Turkoglu did not declare any competing interests. Aysun Soysal did not declare any competing interests. Belgin Petek Balcı did not declare any competing interests. Hüsnü Efendi did not declare any competing interests. Ömer Faruk Turan did not declare any competing interests. Nur Yüceyar did not declare any competing interests. Mehmet Fatih Yetkin did not declare any competing interests. Serap Zengin Karahan did not declare any competing interests. Meltem Demirkıran did not declare any competing interests. Sibel Guler did not declare any competing interests. Kadriye Agan did not declare any competing interests. Nefati Kıylıoğlu received conference travel support from Novartis, Bayer-Schering, Merck, and Teva. Cavid Baba did not declare any competing interests. Asli Tuncer did not declare any competing interests. Mesrure Köseoğlu did not declare any competing interests. Recai Turkoglu did not declare any competing interests.

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