Functional impairment in patients with myotonic dystrophy type 1 can be assessed by an ataxia rating scale (SARA)

Giovanni DiPaolo, Cecilia Jimenez-Moreno, Nikoletta Nikolenko, Antonio Atalaia, Darren G. Monckton, Michela Guglieri, Hanns Lochmüller

Myotonic dystrophy type 1 (DM1) is not characterised by ataxia per se; however, DM1 and ataxia patients show similar disturbances in movement coordination often experiencing walking and balance difficulties, although caused by different underlying pathologies. This study aims to investigate the use of a scale previously described for the assessment and rating of ataxia (SARA) with the hypothesis that it could have utility in DM1 patients as a measure of disease severity and risk of falling. Data from 54 DM1 patients were pulled from the PHENO-DM1 natural history study for analysis. Mean SARA score in the DM1 population was 5.45 relative to the maximum score of eight. A flooring effect (score 0) was observed in mild cases within the sample. Inter-rater and test-retest reliability was high with intraclass coefficients (ICC) of 0.983 and 1.00, respectively. Internal consistency was acceptable as indicated by a Cronbach's alpha of 0.761. Component analysis revealed two principle components. SARA correlated with: (1) all measures of muscle function tested, including quantitative muscle testing of ankle dorsiflexion (r = -0.584*), the 6 min walk test (r = -0.739*), 10 m walk test (r = 0.741*), and the nine hole peg test (r = 0.602*) and (2) measures of disease severity/burden, such as MIRS (r = 0.718*), MDHI (r = 0.483*), and DM1-Activ (r = -0.749*) (*p < 0.001). The SARA score was predicted by an interaction between modal CTG repeat length and age at sampling (r = 0.678, p = 0.003). A score of eight or above predicted the use of a walking aid with a sensitivity of 100% and a specificity of 85.7%. We suggest that further research is warranted to ascertain whether SARA or components of SARA are useful outcome measures for clinical trials in DM1. As a tool, it can be used for gathering information about disease severity/burden and helping to identify patients in need of a walking aid, and can potentially be applied in both research and healthcare settings.