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A step forward towards personalised immunosuppressive therapy in neuromyelitis optica spectrum disorder
  1. Su-Hyun Kim,
  2. Ho Jin Kim
  1. Department of Neurology, Research Institute and Hospital of National Cancer Center, Goyang, Korea
  1. Correspondence to Dr Ho Jin Kim, Department of Neurology, Research Institute and Hospital of National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang-si 410-769, Korea; hojinkim{at}ncc.re.kr

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In neuromyelitis optica spectrum disorder (NMOSD), early initiation of effective immunosuppressive therapy to prevent further relapse is imperative because even a single relapse can have devastating consequences. Several immunosuppressive treatments have been shown to be effective in preventing relapse. However, not all patients respond favourably to each treatment, possibly owing to several factors including variability in disease activity and differences in pharmacokinetics and pharmacodynamics of drugs among patients. Thus, identification of predictors of the most suited treatment regimens for individual patients with NMOSD may help guide treatment decisions.

In their Journal of Neurology, Neurosugery & Psychiatry study, Stellmann et al 1 report retrospective multicenter cohort study from Germany on the efficacy of immunotherapy and predictors for NMOSD attacks in patients undergoing immunotherapy. Azathioprine and rituximab reduced the risk of NMOSD attacks more than interferon β (IFN-β) did, while mitoxantrone and glatiramer acetate did not. Age, antibody status and previous attacks during the same treatment period predicted further attacks during immunosuppressive therapy. This study provides a rationale to switch medication if a patient relapsed despite adequate duration and dose of the administered drug.

They also investigated predictors of response for each type of treatment and showed different predictors between the treatments. The presence of aquaporin-4 antibody was associated with higher attack risk under rituximab and glatiramer acetate, but it did not predict attacks under azathioprine, mitoxantrone and IFNb. For azathioprine, neither age, disease duration, previous attacks nor aquaporin-4 antibody were predictive for attacks, probably small sample size for their subgroup analysis might be underpowered to detect predictors of response. While this is a good first step, future studies are required with larger sample size to determine predictors for each type of treatment for well-informed clinical decision-making for individual patients. Additionally, more information on the profile of each patient’s clinical phenotype and disease activity may help predict which patients are most likely to benefit from specific treatments. Finally, as discontinuation of drug owing to adverse events can associate with disease recurrence, future studies are required to access predictors of safety and tolerability for each patient to a given treatment.

The comparison between the treatments should be interpreted with caution owing to following limitations. First, annualised relapse rates (ARRs) during immunosuppressive therapies were compared with that during IFN-β therapy as a reference. However, the ARR during IFN-β treatment in this study (0.75) was aberrantly lower than that among untreated patients in many previous studies (mean/median 1.5–2.4).2–7 Second, as the authors indicated, there was a selection bias of disease activity favouring the azathioprine-treated patients.

Despite limitations, the study by Stellmann et al expands current knowledge on potential response predictors in NMOSD and highlights the need for further prospective studies involving larger databases on NMOSD. Advancing knowledge on predictors of therapeutic response and risk of side effects will enable us to implement personalised therapy in NMOSD.

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Footnotes

  • Contributors S-HK and HJK: Drafting and critical revision of manuscript.

  • Competing interests None declared.

  • Provenance and peer review Commissioned; internally peer reviewed.

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