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  • Review Article
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Predicting responders to therapies for multiple sclerosis

Nature Reviews Neurology volume 5, pages 553–560 (2009)Cite this article

Abstract

Therapies for relapsing–remitting multiple sclerosis (RRMS) are only partially effective, and, in most patients receiving such treatment, clinical activity persists. Accurately assessing the treatment response to disease-modifying agents enables non-responder patients to be identified at an early stage into therapy. Patients can then be switched to another, potentially more effective, therapy before too much neurological damage has occurred. Several criteria based on relapses, disability progression or both have been proposed for clinical evaluation of the treatment response to disease-modifying agents. These criteria have not been independently validated, however, and no consensus over which are the best to use currently exists among investigators. MRI can also be employed to detect disease activity in patients treated with disease-modifying agents. Changes on MRI can provide subclinical data relating to disease activity that can be of great benefit in patients monitoring, as inflammatory events occur more often than clinical events. Pharmacogenomic approaches are in the early stages of development for MS, but hold great promise for the eventual development of individually tailored therapies. In this Review, we discuss the proposed approaches for monitoring and predicting treatment responses to disease-modifying agents in patients with RRMS. We evaluate the roles of clinical measures, MRI and pharmacogenomics in these processes.

Key Points

  • Relapses and progression of disability are the clinical features of relapsing–remitting multiple sclerosis (RRMS) that are monitored when determining a patient's clinical response to treatment

  • The proportion of non-responders varies depending on the definition of treatment response used

  • Criteria based on relapse measures have poor sensitivity and poor positive predictive value for assessing treatment response

  • Accumulation of new lesions on serial MRI might be a good marker of a poor response to treatment

  • Combining clinical measures of disease activity (relapses and/or progression of disability) with MRI assessment might improve our ability to identify patients who respond poorly to treatment

  • Pharmacogenomics holds great promise for developing individually tailored therapies for patients with RRMS

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Figure 1: Relationship between active lesions on MRI and treatment response.
Figure 2: Proposed algorithm for evaluating the treatment response in patients with relapsing–remitting multiple sclerosis.

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Authors and Affiliations

  1. Multiple Sclerosis Centre of Catalonia, Vall d'Hebron University Hospital, Barcelona, Spain

    Jordi Río, Manuel Comabella & Xavier Montalban

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  1. Jordi Río
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Correspondence to Xavier Montalban.

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Competing interests

X. Montalban has acted as a consultant and on the speaker's bureau for Almirall, Bayer Schering Pharma, Biogen Idec, Merck Serono, Novartis, Sanofi-aventis, Teva and UCB Pharma. He has also received research support from these companies. J. Río and M. Comabella have received honoraria for speaking from Bayer Schering Pharma, Biogen Idec, Merck Serono, Novartis, Sanofi-aventis and Teva.

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Río, J., Comabella, M. & Montalban, X. Predicting responders to therapies for multiple sclerosis. Nat Rev Neurol 5, 553–560 (2009). https://doi.org/10.1038/nrneurol.2009.139

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