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MULTIPLE SCLEROSIS

Assessing long-term effectiveness of MS treatment — a matter of debate

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Assessment of the long-term effectiveness of disease-modifying therapies in multiple sclerosis is plagued by methodological issues, but statistical methods continue to evolve. Use of a novel approach has highlighted the importance of accounting for cumulative exposure to disease-modifying therapies when assessing the long-term effects of treatment on disability accumulation.

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References

  1. Rollot, F. et al. Cumulative effects of therapies on disability in relapsing multiple sclerosis. Mult. Scler. https://doi.org/10.1177/1352458520980366 (2021).

    Article  PubMed  Google Scholar 

  2. Cohen, J. A. et al. Leveraging real-world data to investigate multiple sclerosis disease behavior, prognosis, and treatment. Mult. Scler. 26, 23–37 (2020).

    Article  Google Scholar 

  3. Trojano, M. et al. Treatment decisions in multiple sclerosis - insights from real-world observational studies. Nat. Rev. Neurol. 13, 105–118 (2017).

    Article  Google Scholar 

  4. Abrahamowicz, M. et al. Modeling cumulative dose and exposure duration provided insights regarding the associations between benzodiazepines and injuries. J. Clin. Epidemiol. 59, 393–403 (2006).

    Article  Google Scholar 

  5. Sylvestre, M.-P. & Abrahamowicz, M. Flexible modeling of the cumulative effects of time-dependent exposures on the hazard. Stat. Med. 28, 3437–3453 (2009).

    Article  Google Scholar 

  6. Vukusic, S. et al. Observatoire Français de la Sclérose en Plaques (OFSEP): A unique multimodal nationwide MS registry in France. Mult. Scler. 26, 118–122 (2020).

    Article  Google Scholar 

  7. Robins, J. M., Hernán, M. A. & Brumback, B. Marginal structural models and causal inference in epidemiology. Epidemiology 11, 550–560 (2000).

    Article  CAS  Google Scholar 

  8. Karim, M. E. et al. Marginal structural Cox models for estimating the association between beta-interferon exposure and disease progression in a multiple sclerosis cohort. Am. J. Epidemiol. 180, 160–171 (2014).

    Article  Google Scholar 

  9. Kalincik, T. et al. Effect of disease-modifying therapy on disability in relapsing-remitting multiple sclerosis over 15 years. Neurology 96, e783–e797 (2021).

    Article  Google Scholar 

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Correspondence to Maria Trojano.

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Competing interests

M.T. has received research grants for her Institution from Biogen, Merck, Novartis and Roche, and honoraria as a speaker and advisory board member from Biogen, Merck, Novartis, Roche and Sanofi Genzyme. P.I. has served on advisory boards for Biogen, Bayer, Genzyme, Merck Serono, Novartis, Roche and Teva and has received honoraria as a speaker from Biogen Idec, Genzyme, Merck Serono, Novartis, Sanofi Aventis and Teva.

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Trojano, M., Iaffaldano, P. Assessing long-term effectiveness of MS treatment — a matter of debate. Nat Rev Neurol 17, 197–198 (2021). https://doi.org/10.1038/s41582-021-00476-x

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