The evolution of “No Evidence of Disease Activity” in multiple sclerosis
The availability of effective therapies for patients with relapsing-remitting multiple sclerosis (RRMS) has prompted a re-evaluation of the most appropriate way to measure treatment response, both in clinical trials and clinical practice. Traditional parameters of treatment efficacy such as annualiz...
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Veröffentlicht in: | Multiple sclerosis and related disorders 2018-02, Vol.20, p.231-238 |
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Sprache: | eng |
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Zusammenfassung: | The availability of effective therapies for patients with relapsing-remitting multiple sclerosis (RRMS) has prompted a re-evaluation of the most appropriate way to measure treatment response, both in clinical trials and clinical practice. Traditional parameters of treatment efficacy such as annualized relapse rate, magnetic resonance imaging (MRI) activity, and disability progression have an important place, but their relative merit is uncertain, and the role of other factors such as brain atrophy is still under study. More recently, composite measures such as “no evidence of disease activity” (NEDA) have emerged as new potential treatment targets, but NEDA itself has variable definitions, is not well validated, and may be hard to implement as a treatment goal in a clinical setting. We describe the development of NEDA as an outcome measure in MS, discuss definitions including NEDA-3 and NEDA-4, and review the strengths and limitations of NEDA, indicating where further research is needed.
•“No evidence of disease activity” (NEDA) has emerged as a potential treatment target in patients with RRMS.•NEDA-3 consists of a composite of clinical relapse, EDSS, and MRI outcomes, and has been shown to be predictive of long term disability.•Whole brain atrophy has been integrated into NEDA-4 in order to provide a more comprehensive assessment of disease activity and progression.•NEDA-3 is becoming integrated into clinical decision-making models, however, the implementation of NEDA-4 in clinical practice is currently hindered by logistical and technical difficulties. |
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ISSN: | 2211-0348 2211-0356 |
DOI: | 10.1016/j.msard.2017.12.016 |