Natural history of most common spinocerebellar ataxia: a systematic review and meta-analysis.

Background: Spinocerebellar ataxias (SCAs) are rare dominantly inherited neurodegenerative disorders that lead to severe disability and premature death.

Objective: To better characterize the natural history of the most common SCAs, SCA1, SCA2, SCA3 and SCA6, we performed a meta-analysis of literature to determine disease progression, provide data for sample-sizes calculations for interventional trials and study the impact of geographical locations and study follow-up on disease progression.

Methods: A systematic literature search from MEDLINE and EMBASE databases for longitudinal natural history studies of SCA patients was conducted. Studies using the Scale for the Assessment and Rating Ataxia (SARA) as outcome measure were considered. Random-effect (RE) meta-analysis was applied to estimate pooled disease progression.

Results: Six studies with 1215 SCA patients enrolled between 2005 and 2016 were finally selected. Annual pooled SARA score increase was 1.83 (1.46-2.20) in patients with SCA1, 1.40 (1.19-1.61) in patients with SCA2, 1.41 (0.97-1.84) in patients with SCA3, and 0.81 (0.66-0.97) in patients with SCA6. For patients with SCA3, disease progression was faster in studies located in Asia and Europe than in the US. Two-arm interventional trials of 1-year duration to achieve 80% power and α level of 5% would require 92 patients per group with SCA1, 97 with SCA2, 115 with SCA3, and 430 with SCA6 to detect a 50% reduction in disease progression.

Conclusion: This meta-analysis provides quantitative data on the progression of the most common spinocerebellar ataxias based on patient numbers that exceed those of previous studies and confirms that disease progression is faster in SCA1, intermediate in SCA2 and SCA3 and slower in SCA6, with similar rates of disease progression in SCA2 and SCA3 between different populations, suggesting a possibility of international collaborative studies. Nevertheless, individual-patient data meta-analysis is needed to better understand the risk factors that influence disease progression and improve patient stratification in interventional trials.