Treatment response scoring systems to assess long term prognosis

DMTs may influence the natural history of MS [1]. “It is important to provide our patients information about long-term prognosis, during the first months of therapy”, Dr Jordi Río (University Hospital Vall d’Hebron, Barcelona, Spain) advised.

Although different scoring systems have been used in the assessment of response in the short-term, little data exists regarding the long-term predictive power of these scores [2,3]. There is evidence that MRI activity, relapses, and EDSS worsening are good predictors of short-term treatment response, i.e. during the first 2-3 years after initiation of therapy [4]. Based on these clinical and imaging parameters, several scoring systems have been developed. Dr Río and colleagues compared different treatment response scoring systems to assess long-term prognosis in treated relapsing-remitting MS patients (n=319), and to describe diagnostic properties of the different scores.

Prediction model analysis showed that all scoring systems could significantly identify patients with an EDSS of 6 after 10 years of follow-up. Survival analysis showed that patients with a Rio score >1, modified Rio score >0, ROAD score >3, and MAGNIMS score >0 had a significant probability of achieving an EDSS of 6.0. The ROAD score showed the best sensitivity (85%), whereas the modified Rio score showed the best specificity (88%). The Rio score showed the best positive predictive value (42%), and the ROAD score the best negative predictive value (94%). Finally, the Rio score demonstrated the best accuracy (81%) [5].

These data reinforce the concept of early treatment optimisation in order to minimise the risk of long-term disability. Data regarding the role of these sources in patients receiving non-injectable drugs are needed.

1. Trojano M, et al. Ann Neurol. 2007;61:300-6.
2. Río J, et al. Mult Scler. 2018;24:322-330.
3. Gasperini C, et al. Neurology. 2019;92:180-192.
4. Río J, et al. Mult Scler. 2009;15:848-53.
5. Río J, et al. ECTRIMS 2019, abstract 305.

Posted on 8 November, 201922 March, 2021